FORM 2
THE PATENTS ACT, 1970 THE PATEN (39 o 1970) 003
COMPLETE SPECIFICATION
NETWORKS
APPLICANT
JIO PLATFORMS LIMITED
of Office-101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad - 380006, Gujarat, India; Nationality: India
The following specification particularly describes
the invention and the manner in which
it is to be performed

RESERVATION OF RIGHTS
[0001] A portion of the disclosure of this patent document contains
material, which is subject to intellectual property rights such as, but are not 5 limited to, copyright, design, trademark, integrated circuit (IC) layout design, and/or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or 10 records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner.
TECHNICAL FIELD
[0002] The embodiments of the present disclosure generally relate to
communication networks. In particular, the present disclosure relates to a system 15 and a method for determining channel quality in a spectrum sharing network.
DEFINITION
[0003] As used in the present disclosure, the following terms are generally
intended to have the meaning as set forth below, except to the extent that the
context in which they are used to indicate otherwise.
20
[0004] The expression ‘Sounding reference signals’ used hereinafter in the
specification refers to uplink physical signals employed by user equipment (UE).
These are transmitted on the uplink and allow the network to estimate the quality
of the channel at different frequencies.
[0005] The expression ‘Sounding reference signals (SRS) pool’ used
25 hereinafter in the specification refers to a collection or group of SRS resources that
2

are available for use by User Equipments (UEs) in a wireless communication system. The SRS pool implies that there is a defined set of SRS resources that UEs can utilize. This pool may be dynamically managed and allocated by the network based on factors such as UE requirements, network conditions, and scheduling 5 algorithms. The size and characteristics of the SRS pool can vary depending on the specific deployment and configuration of the wireless network.
[0006] The expression ‘Sounding reference signals (SRS) resources’ used
hereinafter in the specification refers to specific resources within a wireless communication system that are allocated for the transmission of SRS by user 10 equipments (UEs).
[0007] The expression ‘resource grid’ used hereinafter in the specification
refers to an arrangement of resource elements (such as symbols, subcarriers, and antennas) in both the time and frequency domains, forming the foundation for data transmission and reception in the system.
15 [0008] The expression ‘Swapping of the sounding reference signals (SRS)
resources’ used hereinafter in the specification refers to a process of reallocating or reassigning the resources used for transmitting SRS signals. This swapping can occur for various reasons, such as optimizing resource utilization, mitigating interference, or adapting to changing network conditions.
20 [0009] The expression ‘Physical resource blocks (PRBs)’ used hereinafter
in the specification refers to a fundamental unit of resource allocation in the frequency-time domain. PRBs represent a specific amount of bandwidth in the frequency domain and a duration in the time domain.
[0010] These definitions are in addition to those expressed in the art.
25 BACKGROUND
[0011] The following description of related art is intended to provide
background information pertaining to the field of the disclosure. This section may
3

include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
5 [0012] Rollout of 5G networks takes a standalone approach or a non-
standalone approach (NSA). In the NSA, existing 4G infrastructure is used for providing 5G services essentially by causing the 4G network to operate under 5G specifications. Since 4G Long-Term Evolution (LTE) and 5G New Radio (NR) LTE-NR core networks/radio access technologies (RATs) share the same band, 10 dynamic sharing spectrum (DSS) technologies may be used to dynamically allocate frequencies to user equipment (UE) requesting services from the networks. While NSA does not provide much-touted 5G capabilities such as near-zero latency and unparalleled speed, it is considered a cost-effective way to deploy a 5G network across the globe.
15 [0013] Sounding Reference Signals (SRS) are uplink physical signals
transmitted by UE in wireless communication systems, such as LTE and 5G. By transmitting SRS, the UE may allow the base station, or the DSS therein, to estimate channel quality and adjust for optimal signal transmission.
[0014] Typically, the base station, such as a gNB, can perform channel
20 condition quality estimation from physical uplink shared channel (PUSCH) demodulation reference signal (DMRS), but PUSCH DMRS is transmitted only when PUSCH is scheduled and only with the bandwidth associated with the PUSCH. On the contrary, SRS can be transmitted independently of PUSCH’s scheduling and bandwidth. SRS signals are typically provisioned 2 to 4 blocks in 25 NR and 1 to 2 blocks in LTE.
[0015] However, RATs, or the DSS therein, provide a limited number of
physical resource blocks (PRBs) for SRS messages. This implies that only a few UEs are allocated for PRBs based on buffer occupancy, bearer types, etc. Consequently, only a limited number of UEs can be provided functionalities
4

associated with SRS, such as a use of multi-user Multiple-Input-Multiple-Output (MIMO) that can enhance a throughput and robustness of connections. Existing SRS resources in RATs are also underutilized.
[0016] There is, therefore, a need in the art to provide a method and a system
5 that can overcome the shortcomings of the existing prior arts.
OBJECTS OF THE PRESENT DISCLOSURE
[0017] Some of the objects of the present disclosure, which at least one
embodiment herein satisfies are as listed herein below.
[0018] An object of the present disclosure is to provide a system and a
10 method for channel quality estimation in spectrum-sharing networks.
[0019] Another object of the present disclosure is to provide a system and a
method for efficient management of Sounding Reference Signals (SRS) resources.
[0020] Another object of the present disclosure is to provide a system and a
method that estimates channel quality with improved accuracy.
15 [0021] Another object of the present disclosure is to provide a system and a
method that periodically adjusts for an offset between estimated and actual channel quality value.
[0022] Another object of the present disclosure is to provide a system and a
method that allows for utilization of massive Multiple-Input-Multiple-Output 20 (MIMO) based on channel quality estimation.
[0023] Another object of the present disclosure is to provide a system and a
method that increases the number of user equipment (UE) available in an SRS pool, thereby providing an increased number of candidates for an SRS-based Multi-User MIMO.
25 SUMMARY
5

[0024] The present disclosure discloses a system for determining channel
quality in a spectrum sharing network. The system is configured to determine channel quality in a spectrum-sharing network. The system includes a processor, an allocation engine, and an estimation engine. The processor is configured to receive 5 a set of service requesting signals from one or more user equipments (UEs) via a base station. The allocation engine, operable by the processor, is configured to generate a list of the one or more UEs based on a set of parameters associated with each service requesting signal and allocate a first set of Sounding Reference Signal (SRS) resources to a first set of UEs and a second set of SRS resources to a second
10 set of UEs based on a ranking order of the generated list. The estimation engine, operable by the processor, is configured to determine an actual channel condition value for each UE corresponding to the first set of SRS resources, estimate a channel condition value for each UE corresponding to the second set of SRS resources. and determine a delta value indicative of a difference between the actual
15 channel condition value and the estimated channel condition value.
[0025] In an embodiment, the system further includes a dynamic resource
management module configured to adjust the allocation of SRS resources to the one or more UEs based on the determined delta value.
[0026] In an embodiment, the first set of SRS resources includes New Radio
20 (NR) SRS resources, and the second set of SRS resources includes Long-Term Evolution (LTE) SRS resources.
[0027] In an embodiment, the first set of SRS resources is associated with a
first radio access technology (RAT) and the second set of SRS resources is associated with a second RAT.
25 [0028] In an embodiment, the first RAT and the second RAT belong to
different generations of a communication network.
[0029] In an embodiment, the allocation engine is configured to determine
channel correlation and orthogonality by driving a relationship between the one or
6

more UEs of the generated list and is further configured to select a plurality of UE pairs for employing multiple-input-multiple-output (MIMO) based on the determined channel correlation and orthogonality.
[0030] In an embodiment, the estimation engine is configured to
5 periodically enable swapping of the SRS resources among the one or more UEs to refine an estimation of channel conditions.
[0031] In an embodiment, the set of parameters includes bearer type, radio
bearer type, UE data rate, and UE buffer occupancy.
[0032] The present disclosure discloses a method of determining channel
10 quality in a spectrum-sharing network. The method includes receiving, by a processor, a set of service requesting signals from one or more user equipments (UEs) via a base station. The method includes generating, by the processor, a list of the one or more UEs based on a set of parameters associated with each service requesting signal. The method includes allocating, by an allocation engine, a first 15 set of Sounding Reference Signal (SRS) resources to a first set of UEs and a second set of SRS resources to a second set of UEs based on a ranking order of the generated list. The method includes determining, by an estimation engine, an actual channel condition value for each UE corresponding to the first set of SRS resources. The method includes estimating, by the estimation engine, a channel condition 20 value for each UE corresponding to the second set of SRS resources. The method includes determining, by the estimation engine, a delta value indicative of the difference between the actual channel condition value and the estimated channel condition value.
[0033] In an embodiment, the method includes adjusting, by a dynamic
25 resource management module, the allocation of the SRS resources to the one or more user equipments (UEs) based on the determined delta value.
7

[0034] In an embodiment, the method includes prioritizing the one or more
UEs based on a combination of factors including data rate requirements and network congestion levels.
[0035] In an embodiment, the method includes determining channel
5 correlation and orthogonality by driving a relationship between the one or more UEs of the generated list and selecting a plurality of UE pairs for employing multiple-input-multiple-output (MIMO) based on the determined channel correlation and orthogonality.
[0036] In an embodiment, the method includes periodically swapping of the
10 SRS resources among the one or more UEs to refine an estimation of channel conditions.
[0037] The present disclosure discloses a computer program product
comprising a non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors
15 to receive a set of service requesting signals from one or more user equipments (UEs) via a base station. The one or more processors are configured to generate, by an allocation engine, a list of the one or more UEs based on a set of parameters associated with each service requesting signal and allocating a first set of Sounding Reference Signal (SRS) resources to a first set of UEs and a second set of SRS
20 resources to a second set of UEs based on a ranking order of the generated list. The one or more processors are configured to determine, by an estimation engine, an actual channel condition value for each UE corresponding to the first set of SRS resources. The one or more processors are configured to estimate, by the estimation engine, a channel condition value for each UE corresponding to the second set of
25 SRS resources. The one or more processors are configured to determine, by the estimation engine, a delta value indicative of the difference between the actual channel condition value and the estimated channel condition value.
[0038] The present disclosure further discloses a user equipment
communicatively coupled with a system. The coupling comprises steps of receiving
8

a connection request from the system. The coupling comprises steps of sending an acknowledgment of the connection request to the system. The coupling comprises steps of transmitting a plurality of signals in response to the connection request, wherein the system is configured for determining channel quality in a spectrum 5 sharing network. The system includes a processor, an allocation engine, and an estimation engine. The processor is configured to receive a set of service requesting signals from one or more user equipments (UEs) via a base station. The allocation engine, operable by the processor, is configured to generate a list of the one or more UEs based on a set of parameters associated with each service requesting signal and
10 allocate a first set of Sounding Reference Signal (SRS) resources to a first set of UEs and a second set of SRS resources to a second set of UEs based on a ranking order of the generated list. The estimation engine, operable by the processor, is configured to determine an actual channel condition value for each UE corresponding to the first set of SRS resources, estimate a channel condition value
15 for each UE corresponding to the second set of SRS resources, and determine a delta value indicative of a difference between the actual channel condition value and the estimated channel condition value.
BRIEF DESCRIPTION OF THE DRAWINGS
[0039] The accompanying drawings, which are incorporated herein, and
20 constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components 25 using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes the disclosure of electrical components, electronic components or circuitry commonly used to implement such components.
9

[0040] FIG. 1 illustrates an exemplary network architecture for implanting
a system for determining channel quality in a spectrum sharing network, in accordance with embodiments of the present disclosure.
[0041] FIG. 2 illustrates a block diagram of the system for determining
5 channel quality in the spectrum sharing network, in accordance with embodiments of the present disclosure.
[0042] FIG. 3 illustrates a flow chart of a method for determining channel
quality in the spectrum sharing network, in accordance with embodiments of the present disclosure.
10 [0043] FIG. 4 illustrates a flow chart of a method for estimating channel
quality, in accordance with embodiments of the present disclosure.
[0044] FIG. 5 illustrates a flow chart of a method for creating a plurality of
user equipment (UE) pairs from a sounding reference signal (SRS) pool, in accordance with embodiments of the present disclosure.
15 [0045] FIG. 6 illustrates an exemplary computer system in which or with
which embodiments of the present disclosure may be implemented.
[0046] The foregoing shall be more apparent from the following more
detailed description of the disclosure.
LIST OF REFERENCE NUMERALS
20 100 - Network Architecture
102-1, 102-2…102-N - Users
104-1, 104-2…104-N - User Equipments (UEs)
106 - Network
108 - System 25 110 - Network Entities, including Network Entity 1 (110-1) and Network Entity 2
(110-2)
10

112 - Base Stations
202 - Processor(s)
204 - Memory
206 - Interface(s) 5 208 - Processing Unit/Engine(s)
210 - Database
212 - Receiving Engine
214 - Allocation Engine
216 - Estimation Engine 10 218 - Other Engines
220 - Dynamic Resource Management Module
600 - Computer System
610 - External Storage Device
620 - Bus 15 630 - Main Memory
640 - Read Only Memory
650 - Mass Storage Device
660 - Communication Port
670 - Processor
20 DETAILED DESCRIPTION OF THE INVENTION
[0047] In the following description, for the purposes of explanation, various
specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific
25 details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein. Example embodiments of
30 the present disclosure are described below, as illustrated in various drawings in
11

which like reference numerals refer to the same parts throughout the different drawings.
[0048] The ensuing description provides exemplary embodiments only, and
is not intended to limit the scope, applicability, or configuration of the disclosure. 5 Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.
10 [0049] Specific details are given in the following description to provide a
thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to
15 obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
[0050] Also, it is noted that individual embodiments may be described as a
process that is depicted as a flowchart, a flow diagram, a data flow diagram, a
20 structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a
25 procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0051] The word “exemplary” and/or “demonstrative” is used herein to
mean serving as an example, instance, or illustration. For the avoidance of doubt,
12

the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques 5 known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive like the term “comprising” as an open transition word without precluding any additional or other elements.
10 [0052] Reference throughout this specification to “one embodiment” or “an
embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout
15 this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0053] The terminology used herein is to describe particular embodiments
only and is not intended to be limiting the disclosure. As used herein, the singular
20 forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other
25 features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any combinations of one or more of the associated listed items. It should be noted that the terms “mobile device”, “user equipment”, “user device”, “communication device”, “device” and similar terms are used interchangeably for the purpose of describing the invention. These terms
30 are not intended to limit the scope of the invention or imply any specific
13

functionality or limitations on the described embodiments. The use of these terms is solely for convenience and clarity of description. The invention is not limited to any particular type of device or equipment, and it should be understood that other equivalent terms or variations thereof may be used interchangeably without 5 departing from the scope of the invention as defined herein.
[0054] As used herein, an “electronic device”, or “portable electronic
device”, or “user device” or “communication device” or “user equipment” or “device” refers to any electrical, electronic, electromechanical, and computing device. The user device is capable of receiving and/or transmitting one or
10 parameters, performing function/s, communicating with other user devices, and transmitting data to the other user devices. The user equipment may have a processor, a display, a memory, a battery, and an input-means such as a hard keypad and/or a soft keypad. The user equipment may be capable of operating on any radio access technology including but not limited to IP-enabled communication, Zig Bee,
15 Bluetooth, Bluetooth Low Energy, Near Field Communication, Z-Wave, Wi-Fi, Wi-Fi direct, etc. For instance, the user equipment may include, but not limited to, a mobile phone, smartphone, virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other device as may be obvious to a
20 person skilled in the art for implementation of the features of the present disclosure.
[0055] Further, the user device may also comprise a “processor” or
“processing unit” includes processing unit, wherein processor refers to any logic circuitry for processing instructions. The processor may be a general-purpose processor, a special purpose processor, a conventional processor, a digital signal 25 processor, a plurality of microprocessors, one or more microprocessors in association with a digital signal processing (DSP) core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The processor may perform signal coding data processing, input/output processing, and/or any other
14

functionality that enables the working of the system according to the present disclosure. More specifically, the processor is a hardware processor.
[0056] As portable electronic devices and wireless technologies continue to
improve and grow in popularity, the advancing wireless technologies for data 5 transfer are also expected to evolve and replace the older generations of technologies. In the field of wireless data communications, the dynamic advancement of various generations of cellular technology are also seen. The development, in this respect, has been incremental in the order of second generation (2G), third generation (3G), fourth generation (4G), and now fifth generation (5G), 10 and more such generations are expected to continue in the forthcoming time.
[0057] While considerable emphasis has been placed herein on the
components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the 15 disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation.
20 [0058] In the fast-evolving world of telecommunications, the deployment
of 5G networks is a major milestone. However, many regions and service providers are leveraging existing 4G/LTE (Long-Term Evolution) infrastructure to roll out what is known as Non-Standalone (NSA) 5G networks. While these NSA networks incorporate 5G radio antennas, they rely on the 4G LTE core (Evolved Packet Core,
25 EPC) for their base station operations. This approach, while cost-effective, does not fully leverage the core capabilities of 5G, such as minimal latency and high-speed connectivity.
[0059] The present disclosure addresses the above challenges by
estimating/determining channel quality in a dynamic spectrum sharing (DSS)
15

environment. The present disclosure relies on reusing LTE or NR (New Radio) Sounding Reference Signals (SRS) for channel condition estimation in a DSS scenario, implementing a mechanism to periodically fetch actual NR SRS and assess the difference between actual and estimated channel conditions, utilizing 5 SRS-based Multiple-Input Multiple-Output (MIMO) technology. The SRS in 5G networks is composed of orthogonal frequency division multiplexing (OFDM) symbols.
[0060] The present disclosure operates in the DSS environment, where it
leverages the Sounding Reference Signal (SRS) as a key tool for uplink channel
10 quality estimation. In examples, DSS environment refers to a wireless communication system where spectrum resources (radio frequencies) are allocated and managed dynamically, based on real-time demand and usage conditions. This approach allows multiple wireless technologies, such as 4G LTE and 5G, to share the same frequency bands efficiently, optimizing the use of available spectrum and
15 improving overall network performance. The SRS, which can be transmitted independently of uplink scheduling and bandwidth, especially in TDD (Time Division Duplex) modes is predominantly used in 5G networks. In such environments, the channel estimation from SRS is not only useful for uplink scheduling but also for downlink scheduling due to channel reciprocity in TDD.
20 [0061] The process involves spectrum sharing between LTE and NR, where
both technologies share the same frequency span. The SRS, transmitted by the UE and measured by the Base Transceiver Station (BTS), is utilized to estimate uplink channel propagation. This estimation is pivotal in a DSS context, where LTE and NR coexist in the same spectrum. Indeed, the use of wideband Sounding Reference
25 Signals (SRS) can significantly improve the estimation of channel conditions for both Radio Access Technologies (RATs) in a multi-RAT network, thereby enhancing overall network efficiency and performance. Wideband SRS enables the simultaneous estimation of channel conditions across a broad frequency range, providing a comprehensive view of the radio channel characteristics. This broad
30 coverage is particularly beneficial in multi-RAT environments where UEs may
16

operate across different frequency bands or utilize multiple RATs. By accurately estimating channel conditions for both RATs, wideband SRS facilitates better resource allocation, interference management, and optimization strategies across the network. It enables more informed decisions regarding beamforming, power 5 control, and scheduling, leading to improved spectral efficiency and user experience.
[0062] The various embodiments throughout the disclosure will be
explained in more detail with reference to FIG. 1- FIG. 6.
[0063] FIG. 1 illustrates an exemplary network architecture (100) for
10 implanting a system (108) for determining or estimating channel quality in the spectrum sharing network, in accordance with embodiments of the present disclosure. Referring to FIG. 1, the network architecture (100) may include one or more computing devices or user equipments (104-1, 104-2…104-N) associated with one or more users (102-1, 102-2…102-N) in an environment. A person of
15 ordinary skill in the art will understand that one or more users (102-1, 102-2…102-N) may be individually referred to as the user (102) and collectively referred to as the users (102). Similarly, a person of ordinary skill in the art will understand that one or more user equipments (104-1, 104-2…104-N) may be individually referred to as the user equipment (104) and collectively referred to as the user equipment
20 (104). A person of ordinary skill in the art will appreciate that the terms “computing device(s)” and “user equipment” may be used interchangeably throughout the disclosure. Although three user equipments (104) are depicted in FIG. 1, however any number of the user equipments (104) may be included without departing from the scope of the ongoing description. In an embodiment, each of the user equipment
25 may have a unique identifier attribute associated therewith. In an embodiment, the unique identifier attribute may be indicative of Mobile Station International Subscriber Directory Number (MSISDN), International Mobile Equipment Identity (IMEI) number, International Mobile Subscriber Identity (IMSI), Subscriber Permanent Identifier (SUPI) and the like.
17

[0064] In an embodiment, the user equipment (104) may include, but is not
limited to, a handheld wireless communication device (e.g., a mobile phone, a smart phone, a phablet device, and so on), a wearable computer device(e.g., a head-mounted display computer device, a head-mounted camera device, a wristwatch 5 computer device, and so on), a Global Positioning System (GPS) device, a laptop computer, a tablet computer, or another type of portable computer, a media playing device, a portable gaming system, and/or any other type of computer device with wireless communication capabilities, and the like. In an embodiment, the user equipment (104) may include, but is not limited to, any electrical, electronic,
10 electro-mechanical, or an equipment, or a combination of one or more of the above devices such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, wherein the user equipment (104) may include one or more in-built or externally coupled accessories
15 including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, a keyboard, and input devices for receiving input from the user (102) or the entity such as touch pad, touch-enabled screen, electronic pen, and the like. A person of ordinary skill in the art will appreciate that the user equipment (104) may not be restricted to the mentioned devices and various other devices may be
20 used.
[0065] Referring to FIG. 1, the user equipment (104) may communicate
with a system (108) via a base station (112) in a network (106). In an embodiment, the network (106) may include at least one of a 5G network, 4G network, 6G network, or the like, but not limited thereto. The network (106) may enable the user
25 equipment (104) to communicate with other devices in the network architecture (100) and/or with the system (108). The network (106) may include a wireless card or some other transceiver connection to facilitate this communication. In another embodiment, the network (106) may be implemented as, or include any of a variety of different communication technologies such as a wide area network (WAN), a
30 local area network (LAN), a wireless network, a mobile network, a Virtual Private
18

Network (VPN), the Internet, the Public Switched Telephone Network (PSTN), or the like. In an embodiment, the network (106) may include one or more base stations (112) for facilitating communication between the one or more UEs (104). The network (106) may be formed by a set of base stations (112) communicatively 5 coupled to enable telecommunication exchanges between one or more UEs (104).
[0066] The base station (112) may be a network infrastructure that provides
wireless access through one or more terminals associated therewith. The base station (112) may have coverage defined to be a predetermined geographic area based on the distance over which a signal may be transmitted. The base station
10 (112) may include, but not be limited to, a wireless access point, evolved NodeB (eNodeB), 5G node or next generation NodeB (gNB), wireless point, transmission/reception point (TRP), and the like. In an embodiment, the base station (112) may include one or more operational units that enable telecommunication between two or more UEs (104). In an embodiment, the one or more operational
15 units may include, but not be limited to, transceivers, baseband unit (BBU), remote radio unit (RRU), antennae, mobile switching centres, radio network control units, one or more processors associated thereto. In an embodiment, the base station (112) may include one or more network entities (110) depicted by network entity 1 (110-1) and network entity 2 (110-2) in FIG. 1. In an embodiment, the network entities
20 (110) may include, but not limited to, Serving Gateway (SGW), Packet Data Network (PDN) Gateway (PGW), Mobility Management Entity (MME), and the like.
[0067] In an embodiment, the base station (112) is enabled with dynamic
spectrum sharing (DSS). In an embodiment, the DSS may enable the base station
25 (112) associated thereto to provide services or functionalities of a plurality of RATs belonging to different generations of networks. In an embodiment, the DSS enabled base station (112) may include an antenna that allows 4G LTE and 5G cellular wireless technologies to be used in the same frequency band, while dynamically allocating bandwidth based on user demand. In some examples, DSS may allow
30 operators to dynamically allocate or share some existing 4G LTE with a 5G network
19

NR to deliver 5G services using the shared spectrum. In an embodiment, DSS may use SRS signals from the UE (104) to dynamically allocate spectral resources. Sounding Reference Signal (SRS) is a signal transmitted on the uplink channel in 5G. SRS can be used to estimate channel state information and eigenmodes of the 5 radio channel, which are used for signal transmission. The SRS is a fixed periodic transmission in the downlink, a signal that is sent by the eNB to all of its UEs. It allows UEs equipped with an SRS capability to measure channel quality; UEs then use this information to configure and adjust transmit power levels, optimize duplex configurations, and select transmission modes. In an embodiment, the SRS may
10 indicate the quality of the wireless channel between the UE (104) and the base station (112). In an embodiment, SRS may provide information about the quality of the channel condition at different frequencies. For example, by providing information on channel condition quality between the UE (104) and the base station (112), the DSS may be able to allocate spectral resources to the UEs (104)
15 optimally.
[0068] In an embodiment, the base station (112) may include a multi-input-
multi-output (MIMO) that utilizes multiple antennae to transmit and receive signals via a plurality of channels simultaneously. In an embodiment, information in SRS signals may be used for optimizing the beamforming, precoding, and spatial 20 multiplexing processes of MIMO.
[0069] In accordance with embodiments of the present disclosure, the
system (108) may be designed and configured for channel quality estimation in spectrum sharing networks. In an embodiment, the system (108) may optimize SRS resource allocation between a first RAT and a second RAT in the base station (112),
25 where the first RAT is associated with a different generation of networks than the second RAT. SRS resource means a location of SRS in the time and frequency domain in a resource grid. SRS are signals transmitted by UEs to allow the base station (gNB) to estimate the characteristics of the radio channel. These signals are essential for tasks such as beamforming, channel quality estimation, and
30 interference management. SRS resources are the frequency, time, and spatial
20

resources within the wireless spectrum that are designated for transmitting these signals. The allocation of SRS resources is typically managed by the network and is subject to various factors such as UE requirements, network conditions, and scheduling algorithms. These resources need to be carefully managed to ensure 5 efficient utilization of the wireless spectrum and optimal performance of the communication system. The allocation of SRS resources may be dynamic and can vary over time based on the changing requirements of the network and the UEs.
[0070] The system (108) is configured to determine channel quality in the
spectrum sharing network. The spectrum sharing network refers to a
10 telecommunications infrastructure where multiple users or services share the same radio frequency spectrum. Traditionally, spectrum allocation has been based on exclusive licensing, where specific bands of the spectrum are assigned to individual users or services for their exclusive use. However, as demand for wireless communication services grows, traditional allocation methods have become
15 increasingly inefficient. The spectrum sharing network aims to address this inefficiency by dynamically allocating spectrum resources among multiple users or services based on their varying needs and usage patterns. In an aspect, the spectrum sharing network may employ various technologies and techniques, including dynamic spectrum access (DSA), licensed shared access (LSA), and dynamic
20 spectrum sharing (DSS). DSA allows users to access spectrum bands opportunistically when primary license holders are not using them. This can be implemented using cognitive radio technology, where devices can sense their environment and adapt their transmission parameters to avoid interference with licensed users. LSA enables multiple users to share spectrum bands that are licensed
25 to a primary user. Secondary users can access the spectrum on a non-interfering basis with the primary user, typically through the use of databases and coordination mechanisms. DSS allows different wireless technologies, such as 4G LTE and 5G NR, to dynamically share spectrum resources in the same frequency band based on demand and network conditions.
21

[0071] FIG. 2 illustrates a block diagram (200) of the system (108), in
accordance with embodiments of the present disclosure.
[0072] The one or more processor(s) (202) (also may be referred to as a
processor (202)) may be implemented as one or more microprocessors, 5 microcomputers, microcontrollers, edge or fog microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the processor (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the system (108). The memory (204) may
10 be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (204) may include any non-transitory storage device including, for example, volatile memory such as Random Access Memory (RAM), or non-volatile memory such as
15 Erasable Programmable Read-Only Memory (EPROM), flash memory, and the like.
[0073] Referring to FIG. 2, the system (108) may include an interface(s)
(206). The interface(s) (206) may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage 20 devices, and the like. The interface(s) (206) may facilitate communication to/from the system (108). The interface(s) (206) may also provide a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, processing unit/engine(s) (208) and a database (210).
25 [0074] In an embodiment, the processing unit/engine(s) (208) may be
implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) (208). In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For
22

example, the programming for the processing engine(s) (208) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (208) may include a processing resource (for example, one or more processors), to execute such 5 instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (208). In such examples, the system (108) may include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may 10 be separate but accessible to the system (108) and the processing resource. In other examples, the processing engine(s) (208) may be implemented by electronic circuitry.
[0075] In an embodiment, the database (210) may include data that may be
either stored or generated as a result of functionalities implemented by any of the 15 components of the processor (202) or the processing engines (208). In an embodiment, the database (210) may be separate from the system (108). In an embodiment, the database (210) may be indicative of including, but not limited to, a relational database, a distributed database, a cloud-based database, or the like.
[0076] In an exemplary embodiment, the processing engine (208) may
20 include one or more engines selected from any of a receiving engine (212), an allocation engine (214), an estimation engine (216), and other engines (218) having functions that may include, but are not limited to, testing, storage, and peripheral functions, such as wireless communication unit for remote operation, audio unit for alerts and the like.
25 [0077] The processor (202) is configured to receive a set of service
requesting signals from the user equipments (UEs) via the base station. In an example, the set of service requesting signals includes Sounding Reference Signals (SRS). In an embodiment, the receiving engine (212) is configured to receive the set of signals (service requesting signals) indicative of request for services from
23

each of one or more UE (104) via the base station (112). The base stations (112) are allowed for spectrum sharing between networks (106) belonging to a plurality of RATs. In an embodiment, the SRS may occupy one or more symbols in the time domain. In an example, the SRS may occupy either 1, 2 or 4 symbols in the time 5 domain. In an embodiment, the symbols occupied by the SRS may be indicative of the last 6 symbols of the uplink (UL) slot. In an embodiment, the SRS may occupy one or more resource blocks (RB) in the frequency domain. In an embodiment, the UE (104) may be configured to transmit the SRS on subcarriers (SC) selected based on a transmission comb (TC) type. In an example, the NR SRS may be more flexible 10 when compared to LTE SRS as the latter occupies only one symbol and uses TC type 2 while the former can occupy up to 4 symbols and uses TC type 2 or 4.
[0078] The allocation engine (214), operable by the processor (202), is
configured to generate a list of the one or more UEs based on a set of parameters associated with each service requesting signal. The allocation engine (214) analyzes
15 the service requesting signals received from the UEs and generates a list based on certain parameters associated with each signal. These parameters could include factors such as signal strength, requested service type, quality of service requirements, or any other relevant metrics. After generating the list, the allocation engine (214) allocates a first set of SRS resources to a first set of UEs and a second
20 set of SRS resources to a second set of UEs. The allocation is performed based on a ranking order established from the generated list. In an aspect, the ranking order may be a descending order, implying that resources are allocated first to the UEs with the highest priority or ranking in the list and then to those with lower priorities. Typically, UEs with higher priority or better performance based on the specified
25 parameters will be allocated the first set of resources, while others will receive the second set.
[0079] In an operative embodiment, the allocation engine (214) is
configured to rank the one or more UE (104) based on a set of parameters and
allocate the SRS resources to the UEs across different radio access technologies
30 (RATs). In an embodiment, the set of parameters may include, but not be limited
24

to, bearer type (whether of Guaranteed Bit Rate (GBR) or non GBR), Radio Bearer type, UE data rate, UE buffer occupancy, and the like. Bearer type describes a type of bearer associated with the service request, indicating the specific communication characteristics and quality of service requirements. Different bearers may have 5 varying priorities or QoS levels, influencing the allocation of SRS resources. Radio bearer type specifies a type of radio bearer used for communication. It may include categories such as Voice over LTE (VoLTE), Enhanced Multimedia Broadcast Multicast Service (eMBMS), or other data services, each with distinct requirements and priorities. UE Data Rate represents the data rate or throughput requirements of
10 the UE, indicating the amount of data to be transmitted or received within a given time frame. UEs with higher data rate requirements may be allocated more SRS resources to ensure adequate bandwidth and performance. UE Buffer Occupancy reflects the buffer occupancy level of the UE, indicating the amount of data waiting to be transmitted. UEs with higher buffer occupancy may require more frequent
15 communication or higher priority resource allocation to prevent buffer overflow and ensure timely data delivery.
[0080] In an embodiment, the allocation engine (214) may be configured to
rank pairs of UEs (104) based on the orthogonality of beams of the pairs of UEs (104). In an embodiment, since the allocation engine (214) estimates channel 20 condition values of the second set of UEs, which would otherwise not have access to the first RAT, the allocation engine (214) may be able to form an increased number of pairs of UEs compared to traditional solutions. Further, the increased number of UE pairs may increase the probability of obtaining UE pairs having an orthogonality value above a predetermined threshold.
25 [0081] The allocation engine (214) is configured to determine channel
correlation and orthogonality by establishing a relationship between the UEs in the generated list. Additionally, the allocation engine (214) is further configured to select a plurality of UE pairs for employing multiple-input-multiple-output (MIMO) based on the determined channel correlation and orthogonality. To
30 determine channel correlation and orthogonality, the allocation engine analyzes the
25

characteristics of the radio channels between the UEs in the generated list. It assesses the correlation and orthogonality of these channels. Correlation refers to the similarity or relationship between channel responses of different UEs, while orthogonality implies the independence or lack of interference between channels. 5 Based on the determined channel correlation and orthogonality, the allocation engine selects the plurality of UE pairs suitable for employing MIMO techniques. These UE pairs are chosen to maximize the benefits of spatial multiplexing and diversity offered by the MIMO systems. By selecting pairs with low correlation and high orthogonality, the system can achieve better MIMO performance, such as 10 increased data rates, improved reliability, and enhanced spectral efficiency.
[0082] In an overall aspect, the allocation engine (214) ranks the one or
more UEs based on the set of parameters and allocate the first set of SRS resources to the first set of UEs and is further configured to allocate the second set of SRS resources to the second set of UEs. In an example, the first set of SRS resources is
15 associated with a first radio access technology (RAT) and the second set of SRS resources is associated with a second RAT. In an aspect, the first RAT and the second RAT belong to a different generation of networks. In an example, the first set of SRS resources includes New Radio (NR) SRS resources, and the second set of SRS resources includes Long-Term Evolution (LTE) SRS resources. The
20 allocation engine is further configured to select a plurality of UE pairs for multiple-input-multiple-output (MIMO). In such embodiments, the selected pairs of UEs have a channel correlation below a predetermined threshold or channels that are substantially orthogonal to the other.
[0083] The estimation engine (216), operable by the processor (202), is
25 configured to determine an actual channel condition value for each UE corresponding to the first set of SRS resources. The estimation engine (216) is configured to estimate a channel condition value for each UE corresponding to the second set of SRS resources. and determine a delta value indicative of a difference between the actual channel condition value and the estimated channel condition 30 value. For UEs corresponding to the first set of SRS resources, the estimation
26

engine determines the actual channel condition value. This value reflects the real-time characteristics of the radio channel between each UE and the base station. It is obtained by analyzing feedback or measurements from the SRS signals transmitted by these UEs. For UEs corresponding to the second set of SRS resources, the 5 estimation engine estimates the channel condition value. This estimation is based on available information such as historical data, statistical models, or interpolation techniques. It provides an approximation of the channel condition for UEs in this set. After obtaining both the actual and estimated channel condition values, the estimation engine calculates the delta value for each UE. This delta value represents
10 the difference or discrepancy between the actual channel condition and the estimated channel condition. The delta value serves as an indicator of how closely the estimated value aligns with the reality of the channel conditions experienced by each UE. By analyzing the delta values, the system can assess the accuracy of its channel condition estimation techniques and refine them as needed. This
15 information is valuable for optimizing resource allocation, adaptive modulation and coding schemes, and other aspects of the communication system to improve overall performance and reliability.
[0084] In an operative embodiment, the estimation engine (216) may update
the estimated channel condition value with the delta value, thereby periodically
20 correcting the offset between the estimated channel condition value and the actual channel condition value. In one aspect, the estimation engine (216) periodically enables the swapping of the SRS resources among UEs to refine the estimation of channel conditions. In an embodiment, the estimation engine (216) is configured to reassign SRS resources among the UEs within the network periodically. By
25 swapping SRS assignments, the system can gather additional data points and measurements from different UEs, allowing for a more comprehensive understanding of the channel conditions. As SRS resources are swapped among UEs, the estimation engine continuously collects feedback and measurements to refine its estimation of channel conditions. By analyzing the variations in channel
30 responses observed through different SRS configurations, the system can improve
27

the accuracy and reliability of its channel condition estimation algorithms. The periodic swapping of SRS resources enables adaptive resource allocation based on real-time channel dynamics and network conditions. This approach ensures that SRS resources are efficiently utilized to capture variations in channel conditions 5 and adapt to changes in the environment.
[0085] In one embodiment, the system (108) further includes a dynamic
resource management module for adjusting the allocation of SRS resources to the one or more UEs based on the determined delta value to optimize network performance.
10 [0086] The dynamic resource management module operates based on the
delta values, which indicate a gap between the actual and estimated channel conditions for each UE. In an aspect, the dynamic resource management module is configured to monitor the delta values calculated by the estimation engine continuously. These delta values provide insights into the accuracy of the channel
15 condition estimations for each UE. Based on the monitored delta values, the dynamic resource management module dynamically adjusts the allocation of SRS resources to the UEs. If the delta value for a particular UE indicates a significant discrepancy between the actual and estimated channel conditions, the module may consider reallocating SRS resources to improve the accuracy of channel estimation
20 for that UE. By adapting the allocation of SRS resources in response to the observed channel condition discrepancies, the dynamic resource management module optimizes resource utilization and enhance overall system performance. The dynamic resource management module ensures that SRS resources are efficiently allocated to UEs based on their real-time channel conditions, leading to improved
25 reliability and quality of service in the communication system.
[0087] The SRS resources allocated to the UEs are divided into two sets. In
an embodiment, the first set of SRS resources includes New Radio (NR) SRS resources, and the second set of SRS resources includes Long-Term Evolution (LTE) SRS resources. This allocation scheme allows for the differentiation of SRS
28

resources based on the technology generation being used by the UEs. By allocating NR SRS resources to one set of UEs and LTE SRS resources to another set, the system can tailor the resource allocation to the specific technology capabilities and requirements of the UEs. This approach ensures efficient utilization of resources 5 while accommodating the coexistence of multiple wireless technologies within the communication system.
[0088] The dynamic resource management module may adjust the
allocation of NR and LTE SRS resources based on the delta values obtained from the estimation engine. This adaptive allocation strategy helps optimize the 10 performance of both NR and LTE networks, leading to improved overall system efficiency and user experience.
[0089] FIG. 3 illustrates a flow chart of a method (300) for determining
channel quality in the spectrum sharing network, in accordance with embodiments of the present disclosure.
15 [0090] The method, as depicted in FIG. 3, includes receiving (step 302), by
a processor such as the processor (202) of FIG.2, the set of signals indicative of request for services from each of one or more UE via the base station, such as the UE (104) and the base station (112) of FIG. 1. The base stations are configured to allow for spectrum sharing between networks belonging to a plurality of RATs. The
20 first set of signals includes an SRS.
[0091] At step 304, the method includes generating the list of the one or
more UEs based on a set of parameters associated with each service requesting signal. In an aspect, the method includes ranking, by the processor (202), the one or more UE based on the set of parameters.
25 [0092] At step 306, the method includes allocating, by the processor (202),
a first set of SRS resources of a first RAT generation to a first set of UEs having a predetermined number of UEs selected based on the corresponding rank and allocating a second set of SRS resources of a second RAT generation to a second
29

set of UEs. In an example, the first RAT is a 5G network and the second RAT is a 4G network, or vice versa.
[0093] At step 308, the method includes estimating, by the processor (202),
an actual channel condition value for each of the UEs based on the SRS resource 5 allocated thereto.
[0094] At step 310, the method includes estimating, by the estimation
engine, a channel condition value for each UE corresponding to the second set of SRS resources.
[0095] At step 312, the method includes determining, by the processor
10 (202), a delta value and offsetting the estimated channel condition value by the delta value, thereby periodically correcting the offset between the estimated channel condition value and the actual channel condition value.
[0096] In an embodiment, the method includes adjusting, by a dynamic
resource management module (220), the allocation of the SRS resources to the one 15 or more user equipments (UEs) based on the determined delta value.
[0097] In an embodiment, the method includes prioritizing the one or more
UEs based on a combination of factors including data rate requirements and network congestion levels.
[0098] In an embodiment, the method includes determining channel
20 correlation and orthogonality by driving a relationship between the one or more UEs of the generated list and selecting a plurality of UE pairs for employing MIMO based on the determined channel correlation and orthogonality.
[0099] In an embodiment, the method includes periodically swapping of the
SRS resources among the one or more UEs to refine an estimation of channel 25 conditions.
30

[00100] FIG. 4 illustrates a flow chart of a method (400) for estimating
channel quality, in accordance with embodiments of the present disclosure.
[00101] In step (402), the system is configured to create a list of UEs ranked
based on certain parameters. These parameters may include factors like signal 5 strength, data usage, connection stability, or any other relevant metrics. The system is configured to prioritize or categorize UEs based on their performance or characteristics, enabling various purposes such as network optimization, resource allocation, or troubleshooting.
[00102] In step (404), the system is configured to allocate NR SRS resources
10 to UEs in the ranked list starting from the top. This means that the UEs at the top of the list, having the highest priority based on the parameters, will be allocated NR SRS resources first. This allocation strategy ensures that the top prioritized UEs receive the necessary resources first, potentially improving overall network performance or efficiency.
15 [00103] In step (406), the system is configured to allocate LTE SRS
resources to the UEs that were not assigned NR SRS resources in the previous step. These leftover UEs are typically those lower in the ranked list or were not prioritized for NR SRS allocation. By allocating LTE SRS resources to these UEs, the system ensures that all UEs have access to the necessary resources for
20 communication, even if they are not as high priority as those allocated NR SRS resources initially. This helps in maintaining a balanced resource allocation and optimizing overall network performance.
[00104] In step (408), the system is configured to estimate the NR channel
based on the LTE SRS received from UEs. This process involves using the SRS 25 signals transmitted by UEs operating in LTE mode to infer information about the NR channel characteristics. By analyzing these LTE SRS signals, the system can make educated estimations about the corresponding NR channel conditions, such as channel quality, propagation characteristics, interference levels, and other relevant parameters.
31

[00105] In step (410), the system is configured to periodically enable NR
SRS transmission for UEs that only have LTE SRS enabled. This action is taken to obtain actual channel estimations for the NR channel. When UEs initially transmit only LTE SRS, the system may rely on estimations of the NR channel based on the 5 LTE SRS signals, as mentioned in the previous step. However, to improve the accuracy of these estimations and adapt to changing channel conditions, it's essential to periodically enable NR SRS transmission for these UEs. By enabling NR SRS periodically, the system can gather real-time channel measurements specific to the NR network. This allows for more precise channel estimations, 10 which in turn enables better optimization of NR network parameters and resource allocation, leading to improved overall network performance and efficiency.
[00106] In step (412), the system is configured to calculate the delta value
between the actual NR channel characteristics and the calculated NR channel characteristics derived from the LTE SRS. The system is configured to compare the
15 channel characteristics obtained directly from NR SRS measurements (actual NR channel) with the estimations derived from analyzing LTE SRS signals (calculated NR channel). The delta value represents the difference or discrepancy between these two sets of channel characteristics. By analyzing the delta value, the system assesses the accuracy of the channel estimations derived from LTE SRS signals and
20 refine its algorithms for predicting NR channel conditions based on LTE measurements. By minimizing this delta value, the system can improve the accuracy of its channel estimation techniques, leading to better network performance and resource optimization in both LTE and NR networks.
[00107] In step (414), the system is configured to update the estimated NR
25 channel characteristics derived from LTE SRS based on the delta value calculated in the previous step. The system is configured to refine the algorithms used to estimate the NR channel from LTE SRS measurements to better align with the actual NR channel characteristics obtained from direct NR SRS measurements. By incorporating the delta value, which represents the difference between the actual
32

NR channel and the estimated NR channel from LTE SRS, the system adjusts its estimation techniques to reduce discrepancies and improve accuracy.
[00108] By updating the estimated NR channel based on the delta value
ensures that the system's channel estimation algorithms remain adaptive and 5 responsive to changing network conditions. This iterative process helps optimize resource allocation, network configuration, and overall performance in both LTE and NR networks.
[00109] In step (416), the system is configured to estimate the NR channel
characteristics based on the LTE SRS received from the UEs. This step involves
10 analyzing the LTE SRS signals transmitted by UEs to infer information about the NR channel. By estimating the NR channel based on LTE SRS signals, the system can gain insights into the current state of the NR network without directly relying on NR-specific measurements. This information is valuable for optimizing resource allocation, network configuration, and overall performance in mixed LTE-NR
15 environments.
[00110] FIG. 5 illustrates a flow chart of a method (500) for creating the
plurality of UEs pairs from a SRS pool, in accordance with embodiments of the present disclosure.
[00111] In step (502), the system is configured to create the plurality of pairs
20 of UEs based on the correlation or beam orthogonality from the SRS pool. The orthogonality of beams refers to the degree to which different beams used for communication are independent of each other. In beamforming, it is essential to ensure that the beams used by different UEs are orthogonal to each other to minimize interference and maximize efficiency. By analyzing the SRS pool and 25 considering the correlation or orthogonality of beams from different UEs, the system can pair UEs in a way that minimizes interference and optimizes the utilization of available resources. This pairing process is essential for enabling efficient communication between UEs and improving overall network performance.
33

[00112] In step (504), the system is configured to rank the created pairs of
UEs based on a correlation index derived from the SR) pool. This correlation index serves as a metric to evaluate the quality of the pairs in terms of how well they complement each other in the context of beamforming or other communication 5 techniques. The correlation index is calculated based on factors such as the similarity or difference in the channel characteristics between the UEs in each pair. Pairs with higher correlation indices indicate that the UEs have similar channel characteristics, which might lead to better performance in terms of beamforming or other communication strategies.
10 [00113] By ranking the UE pairs based on the correlation index, the system
can prioritize the pairs that are expected to perform the best in terms of communication quality. This ranking enables efficient resource allocation and optimization of communication links within the network.
[00114] In an exemplary aspects, the present disclosure further discloses a
15 user equipment communicatively coupled with a system (108). The coupling comprises steps of receiving a connection request from the system (108). The coupling comprises steps of sending an acknowledgment of the connection request to the system (108). The coupling comprises steps of transmitting a plurality of signals in response to the connection request, wherein the system (108) is
20 configured for determining channel quality in a spectrum sharing network. The system includes a processor (202), an allocation engine (214), and an estimation engine (216). The processor (202) is configured to receive a set of service requesting signals from one or more user equipments (UEs) (104-1, 104-2) via a base station (112). The allocation engine (214), operable by the processor (202), is
25 configured to generate a list of the one or more UEs based on a set of parameters associated with each service requesting signal and allocate a first set of Sounding Reference Signal (SRS) resources to a first set of UEs and a second set of SRS resources to a second set of UEs based on a ranking order of the generated list. The estimation engine (216), operable by the processor (202), is configured to determine
30 an actual channel condition value for each UE corresponding to the first set of SRS
34

resources, estimate a channel condition value for each UE corresponding to the second set of SRS resources, and determine a delta value indicative of a difference between the actual channel condition value and the estimated channel condition value.
5 [00115] FIG. 6 illustrates an exemplary computer system (600) in which or
with which embodiments of the present disclosure may be implemented. As shown in FIG. 6, the computer system (600) may include an external storage device (610), a bus (620), a main memory (630), a read only memory (640), a mass storage device (650), a communication port (660), and a processor (670). A person skilled in the 10 art will appreciate that the computer system (600) may include more than one processor (670) and communication port (660). Processor (670) may include various modules associated with embodiments of the present disclosure.
[00116] In an embodiment, the communication port (660) may be any of an
RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, 15 a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. The communication port (660) may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (600) connects.
[00117] In an embodiment, the memory (630) may be Random Access
20 Memory (RAM), or any other dynamic storage device commonly known in the art. Read-only memory (640) may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or Basic Input/Output System (BIOS) instructions for the processor (670).
25 [00118] In an embodiment, the mass storage (650) may be any current or
future mass storage solution, which may be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or
35

external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g., an array of disks (e.g., SATA arrays).
[00119] In an embodiment, the bus (620) communicatively couples the
5 processor(s) (670) with the other memory, storage, and communication blocks. The bus (620) may be, e.g., a Peripheral Component Interconnect (PCI)/PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), Universal Serial Bus (USB) or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor (670) to the 10 computer system (600).
[00120] Optionally, operator and administrative interfaces, e.g., a display,
keyboard, joystick, and a cursor control device, may also be coupled to the bus (620) to support direct operator interaction with the computer system (600). Other operator and administrative interfaces may be provided through network 15 connections connected through the communication port (660). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system (600) limit the scope of the present disclosure.
[00121] The computer system (600) incorporates one or more functional
20 components of a system and method tailored for estimating channel quality in spectrum sharing networks. The embodiment directs to the dynamic allocation and management of network resources across various Radio Access Technologies (RATs), catering to a diverse range of user equipments (UEs).
[00122] The processor is capable of processing a vast array of data collected
25 from the network. The processor is linked to a memory unit that stores necessary instructions and data for the system's operations. Communication within the system is facilitated by a series of interfaces that connect various processing engines to a central database. The processing engines, including a receiving engine, an
36

allocation engine, an estimation engine, and other auxiliary engines, are tasked with specific functions essential to the system's overall performance.
[00123] The receiving engine initially gathers signals from UEs via base
stations. The signals, particularly the Sounding Reference Signals (SRS), are 5 indicative of the UEs' service requests and their current network conditions. Upon collecting this data, the allocation engine analyzes and ranks the UEs based on various parameters, such as data rate, buffer occupancy, and bearer type. Such ranking process is critical as it determines how the system allocates SRS resources across different RATs, ensuring that each UE receives the necessary resources 10 according to its network compatibility and requirements.
[00124] The estimation engine by assessing the allocated SRS resources and
their effectiveness, provides a clear picture of the network's performance and the specific needs of each UE. Such ongoing estimation is not static; the system is designed to dynamically adjust its resource allocation based on the continuous 15 monitoring of channel conditions. Such an adaptive approach enables the network to respond proactively to changing conditions and UE behaviors, optimizing network performance and resource utilization.
[00125] The present disclosure provides technical advancement related to
DSS where both LTE and NR systems share the same spectrum. In existing DSS 20 implementations, while LTE and NR share the spectrum, they do not reuse other RATs SRS for channel estimation of a current RAT. By incorporating the SRS from other RATs (such as LTE or NR) for channel estimation, the present system provides the following technical advantages:
. Utilizing SRS from multiple RATs expands the pool of available UEs for
25 SRS-based operations. By using SRS of other RATs, more UEs can be
accommodated in the network. . With more UEs contributing to SRS, the pool of candidates for SRS-based
Multiple Input Multiple Output (MIMO) operations grows, thereby
37

enhancing the effectiveness of MIMO techniques for improving spectral efficiency and data rates.
. By utilizing SRS from other RATs, more UEs can be accommodated,
expanding the pool of candidates for SRS-based MIMO operations, and
5 providing more accurate channel state information.
[00126] The method and system of the present disclosure may be
implemented in a number of ways. For example, the methods and systems of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for
10 the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according
15 to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
[00127] While the foregoing describes various embodiments of the present
disclosure, other and further embodiments of the present disclosure may be devised
20 without departing from the basic scope thereof. The scope of the present disclosure is determined by the claims that follow. The present disclosure is not limited to the described embodiments, versions, or examples, which are included to enable a person having ordinary skill in the art to make and use the present disclosure when combined with information and knowledge available to the person having ordinary
25 skill in the art.
ADVANTAGES OF THE PRESENT DISCLOSURE
[00128] The present disclosure provides a system and a method for channel
quality estimation in spectrum sharing networks.
38

[00129] The present disclosure provides a system and a method for efficient
management of Sounding Reference Signals (SRS) resources.
[00130] The present disclosure provides a system and a method that
estimates channel quality with improved accuracy.
5 [00131] The present disclosure provides a system and a method for
periodically adjusting the offset between the estimated and actual channel quality value.
[00132] The present disclosure provides a system and a method that allows
for the utilization of massive Multiple-Input-Multiple-Output (MIMO) based on 10 channel quality estimation.
[00133] The present disclosure provides a system and a method that increases
the number of user equipment (UE) available in the SRS pool, thereby providing an increased number of candidates for SRS-based Multi-User MIMO.
39

We Claim:
1. A system (108) for determining channel quality in a spectrum sharing network,
comprising:
a processor (202) configured to receive a set of service requesting signals from one or more user equipments (UEs) (104) via a base station (112);
an allocation engine (214), operable by the processor (202), configured to generate a list of the one or more UEs based on a set of parameters associated with each service requesting signal and allocate a first set of Sounding Reference Signal (SRS) resources to a first set of UEs and a second set of SRS resources to a second set of UEs based on a ranking order of the generated list; and
an estimation engine (216), operable by the processor (202), configured to:
determine an actual channel condition value for each UE
corresponding to the first set of SRS resources;
estimate a channel condition value for each UE
corresponding to the second set of SRS resources; and
determine a delta value indicative of a difference between the
actual channel condition value and the estimated channel condition
value.
2. The system (108) of claim 1, further includes a dynamic resource management module (220) configured to adjust the allocation of SRS resources to the one or more user equipments (UEs) (104) based on the determined delta value.
3. The system (108) of claim 1, wherein the first set of SRS resources includes New Radio (NR) SRS resources, and the second set of SRS resources includes Long-Term Evolution (LTE) SRS resources.

4. The system (108) of claim 1, wherein the first set of SRS resources is associated with a first radio access technology (RAT) and the second set of SRS resources is associated with a second RAT.
5. The system (108) of claim 4, wherein the first RAT and the second RAT belong to different generations of a communication network.
6. The system (108) of claim 1, wherein the allocation engine (214) is configured to determine channel correlation and orthogonality by driving a relationship between the one or more UEs of the generated list and is further configured to select a plurality of UE pairs for employing multiple-input-multiple-output (MIMO) based on the determined channel correlation and orthogonality.
7. The system (108) of claim 1, wherein the estimation engine (216) is configured to periodically enable swapping of the SRS resources among the one or more UEs to refine an estimation of channel conditions.
8. The system (108) of claim 1, wherein the set of parameters includes bearer type, radio bearer type, UE data rate, and UE buffer occupancy.
9. A method (300) of determining channel quality in a spectrum sharing network, comprising:
receiving (302), by a processor (202), a set of service requesting signals from one or more user equipments (UEs) (104) via a base station (112);
generating (304), by the processor (202), a list of the one or more UEs based on a set of parameters associated with each service requesting signal;
allocating (306), by an allocation engine (214), a first set of Sounding Reference Signal (SRS) resources to a first set of UEs and a second set of SRS resources to a second set of UEs based on a ranking order of the generated list;

determining (308), by an estimation engine (216), an actual channel condition value for each UE corresponding to the first set of SRS resources;
estimating (310), by the estimation engine (216), a channel condition value for each UE corresponding to the second set of SRS resources; and
determining (312), by the estimation engine (216), a delta value indicative of the difference between the actual channel condition value and the estimated channel condition value.
10. The method (300) of claim 9, further comprising adjusting, by a dynamic resource management module (220), the allocation of the SRS resources to the one or more user equipments (UEs) (104) based on the determined delta value.
11. The method (300) of claim 9, further comprising prioritizing the one or more UEs based on a combination of factors including data rate requirements and network congestion levels.
12. The method (300) of claim 9, further comprising determining channel correlation and orthogonality by driving a relationship between the one or more UEs of the generated list and selecting a plurality of UE pairs for employing multiple-input-multiple-output (MIMO) based on the determined channel correlation and orthogonality.
13. The method (300) of claim 9, further comprising periodically swapping of the SRS resources among the one or more UEs to refine an estimation of channel conditions.
14. A user equipment (104) communicatively coupled with a system (108), the coupling comprises steps of:
receiving a connection request from the system (108); sending an acknowledgment of the connection request to the system (108); and

transmitting a plurality of signals in response to the connection request, wherein the system (108) is configured for determining channel quality in a spectrum sharing network as claimed in claim 1.