Description:FORM 2
The Patent Act 1970
(39 of 1970)
&
The Patent Rules, 2003

COMPLETE SPECIFICATION
(SEE SECTION 10 AND RULE 13)

TITLE OF THE INVENTION

“CONVERSION OF SOUNDING REFERENCE SIGNALS AND DEMODULATION REFERENCE SIGNALS IN OPEN-RADIO ACCESS NETWORKS”

APPLICANT:

Name : Sterlite Technologies Limited

Nationality : Indian

Address : 3rd Floor, Plot No. 3, IFFCO Tower,
Sector – 29, Gurugram, Haryana, 122002

The following specification particularly describes the invention and the manner in which it is to be performed:
TECHNICAL FIELD
[0001] The present disclosure relates to wireless communication and networks, and more specifically relates to conversion (compression and decompression) of sounding reference signals (SRS) and demodulation reference signals (DMRS) in open-radio access networks (O-RAN).

BACKGROUND
[0002] In order to provide reliable communication over the air, a receiver needs to estimate the quality of a wireless link. This is done by the transmission of certain signals named pilots. In cellular communications, such as fifth generation (5G), the pilots are sent in both directions, which is from a radio unit (O-RU or RU) to a user equipment (UE) and vice versa. To support 5G systems, numerous antennas are used at a transmitter, the receiver, or both. Such 5G systems are called as massive multiple input multiple output (Massive MIMO) systems. The pilots need to be transmitted for each of these antennas and this will lead to a significant amount of data. The large number of antennas in a massive MIMO system will lead to the enormous amount of channel state information being stored in a memory, which demands the use of compression techniques for efficient utilization of the memory in the O-RU. The channel state information can be compressed by lossy compression methods which involve loss of some information but higher compression or by lossless compression methods that have no loss of information but lower compression.
[0003] Typically, lots of signals (i.e., control signals) are required for massive MIMO data transmission that uses beamforming technique and requires a lot of estimations coming from the UE in order to perform data transmission in uplink and downlink. The beamforming technique works on the control signals such as sounding reference signals (SRS) and demodulation reference signals (DMRS) on which the estimations are carried and fed to the O-RU. If the SRS and the DMRS are not compressed, the same will consume the memory of the O-RU and kill the bandwidth of interface connecting the O-RU to a DU (Distributed Unit), thereby bringing down the performance of the wireless link.
[0004] Some of the prior art references are given below regarding compression and decompression of the SRS and the DMRS, where:
[0005] WO2022015598A1 discloses a technique for signal compression. A method implemented in a Distributed unit in which reference signals are compressed using a first compression type and data is compressed using a second compression type. The reference signals are compressed using a more robust and less lossy compression types such that estimation of the channel, which is essential for data decoding, is not affected. The use of effective compression types reduces front-haul bandwidth.
[0006] US20200267715A1 discloses the transmission of reference signals such as DMRS and SRS from one user equipment (UE1) to another user equipment (UE2). The reference signals are used to calculate channel state information (CSI) estimation/calculation.
[0007] US20210234730A1 discloses a method implemented in a network device for channel estimation using SRS and DMRS.
[0008] A non-patent literature entitled ‘A Prefiltering C-RAN Architecture with Compressed Link Data Rate in Massive MIMO’ discloses a pre-filtering architecture in RRUs to compress the interconnection link data rate between RRU and BBU. To make the pre-filtering architecture feasible in realistic CRAN systems, two practical channel estimation schemes using demodulation reference signal (DMRS) and sounding reference signal (SRS) to calculate the prefiltering matrix, respectively are used.
[0009] While the prior arts discuss various techniques for compression and decompression of the SRS and the DMRS, however, the existing techniques are inefficient in saving enough space in the memory of gNB (gNode B) and the O-RU and saving bandwidth of fronthaul. Further, the prior arts/techniques fail to provide a channel gain estimation that is accurate and efficiently established. In light of the above-stated discussion, there is a need to overcome the above stated disadvantages.

OBJECT OF THE DISCLOSURE
[0010] A principal object of the present disclosure is to solve the aforesaid drawbacks and provide conversion (compression and decompression) of sounding reference signals (SRS) and demodulation reference signals (DMRS) in open-radio access networks, where a radio unit performs compression of SRS-based channel estimates and DMRS based channel estimates using a lossless compression technique and the compressed SRS and DMRS based channel estimates are sent to a distributed unit for beamforming weight calculation to facilitate massive antenna beamforming.
[0011] Another object of the present disclosure is to save spaces in a memory at gNB (gNode B) and memory at a radio unit so that more channel feedback can be accumulated from UEs (User Equipments), to save bandwidth of a fronthaul and to provide a channel gain estimation that is accurate and efficiently established in the open-radio access networks without compromising on a capacity in terms of a number of SRS and DMRS.

SUMMARY
[0012] Accordingly, the present disclosure provides a method for space saving in a shared memory of a base station in an Open-Radio Access Network (O-RAN). The method implements conversion techniques i.e., compression and decompression. The method includes compressing one or more reference signals at an Open-Radio Unit (O-RU) to form one or more compressed reference signals, wherein the one or more reference signals are one or more demodulation reference signals (DMRS) and one or more sounding reference signals (SRS). The one or more DMRS estimates a radio channel and the one or more SRS gives information about the combined effect of multipath fading, scattering, doppler, and power loss of a signal transmitted by a user equipment (UE). The method further includes transmitting the one or more compressed reference signals from the O-RU to an Open-Distributed Unit (O-DU) and decompressing the one or more compressed reference signals at the O-DU. The compression and the decompression occur within a prominent time, wherein the prominent time is the total time used in extraction, compression, transmission and decompression of the one or more reference signals, wherein the prominent time depends upon the number of reference signals.
[0013] In other words, the method includes extracting the one or more reference signals, transmitted by the UE, at the O-RU and estimating the one or more reference signals for channel quality over a wider bandwidth by the O-RU. Thereafter, the method includes compressing the one or more estimated reference signals by the O-RU, transmitting the one or more compressed reference signals from the O-RU to the O-DU and decompressing the one or more compressed reference signals at the O-DU. While transmitting the one or more compressed reference signals from the O-RU to the O-DU, compression settings are also exchanged between the O-RU and the O-DU by a coding mechanism for the compression to decode the one or more compressed reference signals successfully.
[0014] The one or more estimated reference signals are transmitted by the UE, by extracting a channel estimation of a sounding reference signal (SRS) and a demodulation reference signal (DMRS) at the O-RU from at least one of a Physical Uplink Control Channel (PUCCH) and a Physical Uplink Shared Channel (PUSCH), wherein the PUSCH carries signaling messages, uplink control information, and application data.
[0015] The compression is performed by using a lossless compression technique, wherein data is recreated and recovered from compressed data which is identical to original data without loss of information. The compression is done by generating prefix codes of variable length which are uniquely decodable and shared to the O-DU.
[0016] These and other aspects herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the invention herein without departing from the spirit thereof.

BRIEF DESCRIPTION OF FIGURES
[0017] The invention is illustrated in the accompanying drawings, throughout which like reference letters indicate corresponding parts in the drawings. The invention herein will be better understood from the following description with reference to the drawings, in which:
[0018] FIG. 1 illustrates the conversion (compression and decompression) of a sounding reference signal (SRS) and demodulation reference signal (DMRS) based on channel estimates in an open-radio access network (O-RAN).
[0019] FIG. 2 illustrates various hardware elements of an open radio unit (O-RU).
[0020] FIG. 3 illustrates various hardware elements of an open distributed unit (O-DU).
[0021] FIG. 4 and FIG. 5 illustrate examples of SRS transmission with different comb spacings and offsets.
[0022] FIG. 6 illustrates a lossless compression technique.
[0023] FIG. 7 to FIG. 10 illustrate results for compression of the SRS and the DMRS.
[0024] FIG. 11 is a flow chart illustrating a method for space saving in a shared memory of a 5G New Radio (NR) base station (or any base station).
[0025] FIG. 12 is a flow chart illustrating a method for space saving in the shared memory of the 5G New Radio (NR) base station (or any base station).

DETAILED DESCRIPTION
[0026] In the following detailed description of the invention, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be obvious to a person skilled in the art that the invention may be practiced with or without these specific details. In other instances, well known methods, procedures and components have not been described in details so as not to unnecessarily obscure aspects of the invention.
[0027] Furthermore, it will be clear that the invention is not limited to these alternatives only. Numerous modifications, changes, variations, substitutions and equivalents will be apparent to those skilled in the art, without parting from the scope of the invention.
[0028] The accompanying drawings are used to help easily understand various technical features and it should be understood that the alternatives presented herein are not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawings. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.
[0029] Unlike the conventional techniques, the present disclosure provides utilization of a sounding reference signal (SRS) and a demodulation reference signal (DMRS) to estimate channel quality, where compression of SRS based channel estimate and DMRS based channel estimate is done using a lossless compression technique at an O-RU (Open Radio Unit) and decompression of the SRS and DMRS based channel estimates is done at an Open Distributed Unit (O-DU). Advantageously, compressing the SRS based channel estimates and the DMRS based channel estimates helps in attaining space savings in memory of a gNB (gNode B or any other base station) and a memory of an O-RU (Open Radio Unit), as well as helps in saving bandwidth of a fronthaul link.
[0030] FIG. 1 illustrates conversion (compression and decompression) of a sounding reference signal (SRS) and demodulation reference signal (DMRS) based on channel estimates in an Open-Radio Access Network (O-RAN) (100).
[0031] The O-RAN (100) is a part of a telecommunications system which connects individual devices to other parts of a network through radio connections. The O-RAN (100) provides a connection of user equipment (UE) such as mobile phones or computer with a core network of the telecommunication systems. The O-RAN (100) is an essential part of an access layer in the telecommunication systems which utilize base stations (such as eNodeB, gNodeB) for establishing radio connections. The O-RAN (100) is an evolved version of prior radio access networks, making the prior radio access networks more open and smarter than previous generations. The O-RAN (100) provides real-time analytics that drives embedded machine learning systems and artificial intelligence (AI) back-end modules to empower network intelligence. Further, the O-RAN (100) includes virtualized network elements with open and standardized interfaces. The open interfaces are essential to enable smaller vendors and operators to quickly introduce their own services or enable operators to customize the network to suit their own unique needs. Open interfaces also enable multivendor deployments, enabling a more competitive and vibrant supplier ecosystem. Similarly, open-source software and hardware reference designs enable faster, more democratic, and permission-less innovation. Further, the O-RAN (100) introduces a self-driving network by utilizing new learning-based technologies to automate operational network functions. These learning-based technologies make the O-RAN intelligent. Embedded intelligence, applied at both component and network levels, enables dynamic local radio resource allocation and optimizes network wide efficiency. In combination with O-RAN’s open interfaces, Artificial intelligence (AI)-optimized closed-loop automation is a new era for network operations.
[0032] The O-RAN (100) comprises an Open Radio Unit (O-RU) (102) and an Open Distributed Unit (O-DU) (104). The O-RU (102) is a logical node hosting a Low-PHY layer and RF (Radio Frequency) processing based on a lower layer functional split. This is similar to 3rd Generation Partnership Projects (3GPP’s) “TRP (Transmission and Reception Point)” or “RRH (Remote Radio Head)” but more specific in including the Low-PHY layer (FFT/iFFT, PRACH (Physical Random Access Channel) extraction). The O-DU (104) is a logical node hosting RLC/MAC (Medium access control)/High-PHY layers based on a lower layer functional split.
[0033] Open fronthaul interfaces i.e., OFH CUS-Plane (Open Fronthaul Control, User, Synchronization Plane) and OFH M-Plane (Open Fronthaul Management Plane) connect the O-DU (104) and the O-RU (102). The OFH CUS-Plane is multi-functional, where the control and user feature transfer control signals and user data respectively and the synchronization feature synchronizes activities between multiple RAN devices. The OFH M-Plane optionally connects the O-RU (102) to a Service Management and Orchestration (SMO) (not shown). The O-DU (104) uses the OFH M-Plane to manage the O-RU (102), while the SMO can provide FCAPS (fault, configuration, accounting, performance, security) services to the O-RU (102).
[0034] Further, the O-RU (102) and the O-DU (104) are divided using an Enhanced Common Public Radio Interface (eCPRI) that splits up baseband functions to reduce traffic strain on an optical fiber. The eCPRI provides flexible radio data transmission through a packet based fronthaul network (e.g., IP or Ethernet).
[0035] Referring to FIG. 1, the O-RU (102) receives and converts radio signals sent to and from an antenna (106) to a digital signal that is transmitted over a fronthaul to the O-DU (104). Particularly, the O-RU (102) compresses one or more reference signals received from the antenna (106) to form one or more compressed reference signals. The one or more reference signals are one or more demodulation reference signals (DMRS) and one or more sounding reference signals (SRS) that carry channel estimation of a single user equipment (UE) (not shown) or multiple UEs. The additional details of the DMRS and the SRS are provided below in conjunction with FIG. 4 and FIG. 5.
[0036] As shown in FIG. 1, initially, when the one or more reference signals are received from the antenna (106) at the O-RU (102), the same is processed using FFT (Fast Fourier Transform). In general, FFT based signal processing is a tool for spectrum enhancement of orthogonal frequency-division multiplexing (OFDM)-based waveforms, which is a central element in fifth generation new radio (5G-NR) developments.
[0037] The one or more FFT processed reference signals are sent for three simultaneous actions i.e., beam forming and port reduction, DMRS processing and SRS processing. Beamforming is a key wireless technique which works in unison with Massive MIMO to increase network throughput and capacity. The beamforming uses advanced antenna technologies to focus the wireless signal in a specific direction, rather than broadcasting to a wide area. This technique reduces interference between beams directed in different directions, enabling the deployment of larger antenna arrays.
[0038] During the SRS processing and the DMRS processing, the one or more reference signals transmitted by the UE(s) are extracted at the O-RU (102) (i.e., SRS extraction and DMRS extraction) and the one or more transmitted reference signals is estimated for the channel quality/gain over a wider bandwidth (i.e., SRS Channel Estimation and DMRS Channel Estimation).
[0039] For estimating channel gain over frequencies of bandwidth in the O-RAN (100), a radio network node (e.g., O-RU) measures a first channel gain based on a received power of a received SRS over the first set of frequencies from a user equipment, in which the first set of frequencies is comprised of the frequencies of the bandwidth. The radio network node measures a second channel gain based on a received power of a received DMRS of a physical uplink shared channel over a second set of frequencies from the user equipment, in which the second set of frequencies is comprised of the frequencies of the bandwidth.
[0040] The channel is always estimated using the DMRS and the SRS as the UE(s) have a static allocation of resource elements (REs). Assuming that the pilot symbols lie on a unit circle, such as when using quadrature phase-shift keying (QPSK) pilots, the channel estimate is calculated with least squares (LS) as follows:

where * denotes the Hermitian transpose, P denotes the indices of REs carrying pilots, and xij and yij are the transmitted and received pilot symbols. The channel estimate is expanded to the whole slot using linear interpolation.
[0041] Typically, the DMRS estimates the radio channel and the SRS gives information about the combined effect of multipath fading, scattering, doppler, and power loss of transmitted signal.
[0042] The one or more estimated reference signals are transmitted by the UE, by extracting a channel estimation of the SRS and the DMRS at the O-RU (102) from a PUCCH (Physical Uplink Control Channel) and/or a PUSCH (Physical Uplink Shared Channel), wherein the PUSCH carries signaling messages, uplink control information, and application data.
[0043] The one or more estimated reference signals are further compressed (i.e., SRS and DMRS compression). The level of compression can be specified by the compression ratio and space savings. That is, the compression ratio, the performance of compression by the amount of compression, the speed at which data is compressed and decompressed, the complexity of the technique, the memory requirement of the algorithm, etc. are measured. The compression ratio is defined as:
?????????????????????? ?????????? = (???????? ???? ???????????????? ???????? / ???????? ???? ???????????????????? ????????)
[0044] Similarly, the space savings term is defined as:
?????????? ?????????????? = (1 - ???????? ???? ???????????????????? ????????/???????? ???? ???????????????? ????????) × 100%
[0045] The compression is done using lossless compression, wherein the data can be recreated/recovered from the compressed data which is identical to the original data and there is no loss of information. The compression is done by generating prefix codes of variable length which are uniquely decodable and shared with the O-DU (104). That is, the compression is done by using Huffman coding, which uses memory and provides entropy-based encoding (“a lossless compression technique”) of information/data that compresses data by replacing fixed-length input symbols with variable-length prefix-free output codeword. Huffman coding is a lossless data compression technique. The idea is to assign variable-length codes to input characters, lengths of the assigned codes are based on the frequencies of corresponding characters. For example, the most frequent character (estimation/s) gets the smallest code, and the least frequent character gets the largest code. In other words, the variable-length codes assigned to input characters are Prefix Codes, which means the codes (bit sequences) are assigned in such a way that the code assigned to one character is not the prefix of code assigned to any other character. This is how Huffman coding makes sure that there is no ambiguity when decoding the generated bitstream.
[0046] In a nutshell, the compression occurs into two phases, i.e., a modelling phase and a coding phase. In the modelling phase, the information about parameters like redundancy or probability present in data/reference signal is extracted and represented as a model and in the coding phase, entropy-based coding takes place.
[0047] The one or more compressed reference signals are then transmitted from the O-RU (102) to the O-DU (104) for decompression, where the O-DU (104) performs decompression. Along with the one or more compressed reference signals, (optionally) compression settings are also exchanged between the O-RU (102) and the O-DU (104) by the coding technique/mechanism (e.g., Huffman coding as shown in FIG. 6) for the compression in order to decode the compressed data successfully with no error. The compression setting corresponds to a type of compression technique and parameters used to compress the SRS and DMRS based channel estimates.
[0048] The one or more compressed reference signals is transmitted at the O-DU (104) for beamforming weight calculation, equalization, layer mapping, and decoding, wherein the one or more compressed reference signals undergoes equalization using an equalizer within the O-DU (104) that compensates for an average range of expected channel amplitude and delay characteristics. After equalization, each codeword is mapped to one or multiple layers under layer mapping/demapping, which is further demodulated or decoded.
[0049] Once the one or more compressed reference signals are decompressed, the same undergoes beamforming weight (BFW) calculation to facilitate massive antenna beamforming, which is further fed for beam forming and port reduction at the O-RU (102).
[0050] It may be noted that, the compression and the decompression occur within a prominent time, wherein the prominent time is the total time used in the extraction, compression, transmission and decompression of the one or more reference signals. The prominent time depends upon the number of reference signals. Another important performance measure is the time required to compress and decompress the data, namely compression and decompression times. The time taken during compression and decompression of the data (SRS and DMRS based estimates) is called compression and decompression time. Typically, when a lossless compression and decompression technique is used, the compression and decompression time is less as compared to the other lossy compression and decompression technique.
[0051] The above compression and decompression technique advantageously facilitate space saving in a shared memory of a 5G New Radio (NR) base station (O-RU).
[0052] FIG. 2 illustrates various hardware elements of the O-RU (102). The O-RU (102) comprises a processor (202), a memory (204), a compression unit (206) and a communicator (208). The processor (202) is configured to execute instructions stored in the memory (204) and to perform various processes related to the present disclosure. The communicator (208) is configured for communicating internally between internal hardware components and with external devices via one or more networks. The memory (204) is configured to store instructions to be executed by the processor (202).
[0053] The compression unit (206) performs all the functions regarding the compression of the one or more reference signals as disclosed above in FIG. 1 and the same has not been provided herein again to avoid redundancy.
[0054] FIG. 3 illustrates various hardware elements of the O-DU (104). The O-DU (104) comprises a processor (302), a memory (304), a decompression unit (306) and a communicator (308). The processor (302) is configured to execute instructions stored in the memory (304) and to perform various processes related to the present disclosure. The communicator (308) is configured for communicating internally between internal hardware components and with external devices via one or more networks. The memory (304) is configured to store instructions to be executed by the processor (302).
[0055] The decompression unit (306) performs all the functions regarding decompression of the one or more compressed reference signals as disclosed above in FIG. 1 and the same has not been provided herein again to avoid redundancy.
[0056] FIG. 4 and FIG. 5 illustrate examples of SRS transmission (400 and 500) with different comb spacings and offsets. In general, the SRS always uses Zadoff-Chu (ZC) sequences that are good candidates, since they exhibit constant power in time and frequency and are represented by a 32-bit complex number. As a UL (uplink)-only signal, the SRS is transmitted by the UE to help the gNB obtain channel state information (CSI) for each user. The CSI from all the UEs is stored in shared memory. The Channel State Information describes how the NR signal propagates from the UE to the gNB and represents the combined effect of scattering, fading, and power decay with distance. Apart from providing the CSI, the SRS obtains detailed information about the amplitude and phase estimates and scattering.
[0057] The SRS is used for resource scheduling, link adaptation, Massive MIMO, and beam management. The SRS is configured specifically to the UE. In the time domain, it spans 1/2/4 consecutive symbols which are mapped within the last six symbols of the slot. Periodic SRS transmissions occur regularly in the time domain as frequently as once every 2 ms or infrequently as once every 160 ms. The SRS is sent in the last symbol of a subframe. The SRS is sent by the UE(s) to aid channel estimation. The SRS is sent over 1, 2, or 4 antenna ports and over 1, 2, or 4 OFDM symbols. The SRS bandwidth is defined by higher layer parameters between 1 and 272 RBs and has a comb structure with 2, 4 or 8 combs. A transmission comb size of 2 means that an individual UE transmits on every second subcarrier. This allows two groups of UE to be frequency multiplexed with a single subcarrier offset between the two groups. Similarly, a transmission comb size of 4 means that an individual UE transmits on every fourth subcarrier. This increases the frequency domain multiplexing capability but reduces the quality of the SRS measurements.
[0058] An SRS resource can be configured as Periodic by higher layers parameters having periodicity in slots, where slot offset <= period – 1. The SRS resource can also be aperiodic and semi-persistent.
[0059] Multiple SRS symbols allow coverage extension and increased sounding capacity. The design of the SRS and its frequency hopping mechanism is the same as that used in LTE (Long Term Evolution).
[0060] Like the SRS, the DMRS can use Zadoff-Chu (ZC) or Gold sequences. The DMRS is used by a receiver for radio channel estimation for demodulation of associated physical channels. DMRS design and mapping are specific to each Downlink and Uplink NR channel viz NR-PBCH (New Radio - Physical Broadcast Channel), NR-PDCCH (NR- Physical Downlink Control Channel), NR-PDSCH (NR- Physical Downlink Shared Channel), and NR-PUSCH (NR- Physical Uplink Shared Channel). The DMRS is specific for specific UE, and transmitted on demand and can beamform the DMRS, kept within a scheduled resource, and transmit it only when necessary in either DL or UL. Multiple orthogonal DMRSs can be allocated to support MIMO transmission.
[0061] FIG. 6 illustrates a lossless compression technique (600) in conjunction with FIG. 1. The lossless compression technique (600) is Huffman coding which uses memory and is the entropy-based encoding of information as disclosed above. The objective of this technique is to compress data by generating prefix codes, which refer to uniquely decodable codes.
[0062] FIG. 7 to FIG. 10 illustrate results for compression of the SRS and the DMRS, where FIG. 7 is a graph (700) plotted between Resource Block (RB) and time (ms). The graph (700) depicts the compression time and the decompression time.
[0063] FIG. 8 is a graph (800) plotted between the Resource Block (RB) and size (KB). The graph (800) depicts the memory before compression and memory after compression. That is, the graph (800) depicts space saving in the shared memory of the 5G New Radio (NR) base station after implementing the techniques disclosed in the present disclosure. Table 1 depicts the outcome of the technique described in the present disclosure:
RB SCS Memory before Compression (KB) Memory after Compression (KB) Compression Time (ms) De-compression Time (ms) Compression Ratio Space Saving (%)
52 15 0.482 0.347 14.93 17.01 1.389 28.008
136 15 6.15 1.01 32.937 48.056 6.089 83.577
273 30 11.7 1.74 64.136 103.53 6.724 85.128
Table 1
[0064] FIG. 9 is a graph (900) plotted between sample index and sample magnitude depicting compressed signals.
[0065] FIG. 10 is a graph (1000) plotted between sample index and sample magnitude depicting decompressed signals.
[0066] FIG. 11 is a flow chart (1100) illustrating a method for space saving in the shared memory of the 5G New Radio (NR) base station (or any base station). The steps 1102 to 1104 are handled by the O-RU (102) in the O-RAN (100). For the sake of brevity, the operations and functions of the O-RU (102) are not repeated while describing FIG. 11.
[0067] At Step 1102, the method includes compressing the one or more reference signals at the O-RU (102) to form the one or more compressed reference signals, wherein the one or more reference signals are one or more of the demodulation reference signals (DMRS) and the sounding reference signals (SRS).
[0068] At Step 1104, the method includes transmitting the one or more compressed reference signals from the O-RU (102) to the O-DU (104).
[0069] FIG. 12 is a flow chart (1200) illustrating a method for space saving in the shared memory of the 5G New Radio (NR) base station (or any base station). The steps 1202 to 1206 are handled by the O-RU (102) and the O-DU (104) respectively in the O-RAN (100). For the sake of brevity, the operations and functions of the O-RU (102) and the O-DU (104) are not repeated while describing FIG. 12.
[0070] At Step 1202, the method includes compressing the one or more reference signals at the O-RU (102) to form the one or more compressed reference signals, wherein the one or more reference signals are one or more of the demodulation references signals (DMRS) and the sounding reference signals (SRS).
[0071] At Step 1204, the method includes transmitting the one or more compressed reference signals from the O-RU (102) to the O-DU (104).
[0072] At Step 1206, the method includes decompressing the one or more compressed reference signals at the O-DU (104), wherein the compression and de-compression occur within the prominent time. The prominent time is the total time used in the extraction, compression, transmission and decompression of the one or more reference signals and depends upon the number of the reference signals.
[0073] Advantageously, compression of SRS and DMRS based channel estimates saves spaces in the gNB memory and the O-RU memory. The saved spaces are used to accumulate more channel feedback from the UEs. Both the SRS and DMRS based channel estimates are used by the O-DU for better beamforming weight calculation. The compressed SRS and DMRS based channel estimates help in saving fronthaul bandwidth, thereby improving the performance of the O-RAN (100).
[0074] The various actions, acts, blocks, steps, or the like in the flow charts (1100 and 1200) may be performed in the order presented, in a different order or simultaneously. Further, in some implementations, some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the invention.
[0075] The embodiments disclosed herein can be implemented using at least one software program running on at least one hardware device and performing network management functions to control the elements.
[0076] It will be apparent to those skilled in the art that other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention. While the foregoing written description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations, combinations, and equivalents of the specific embodiment, method, and examples herein. The invention should therefore not be limited by the above-described embodiment, method, and examples, but by all embodiments and methods within the scope of the invention. It is intended that the specification and examples be considered as exemplary, with the true scope of the invention being indicated by the claims.
[0077] The methods and processes described herein may have fewer or additional steps or states and the steps or states may be performed in a different order. Not all steps or states need to be reached. The methods and processes described herein may be embodied in, and fully or partially automated via, software code modules executed by one or more general purpose computers. The code modules may be stored in any type of computer-readable medium or other computer storage device. Some or all of the methods may alternatively be embodied in whole or in part in specialized computer hardware.
[0078] The results of the disclosed methods may be stored in any type of computer data repository, such as relational databases and flat file systems that use volatile and/or non-volatile memory (e.g., magnetic disk storage, optical storage, EEPROM and/or solid-state RAM).
[0079] The various illustrative logical blocks, modules, routines, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. The described functionality can be implemented in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosure.
[0080] Moreover, the various illustrative logical blocks and modules described in connection with the embodiments disclosed herein can be implemented or performed by a machine, such as a general purpose processor device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components or any combination thereof designed to perform the functions described herein. A general-purpose processor device can be a microprocessor, but in the alternative, the processor device can be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor device can include electrical circuitry configured to process computer-executable instructions. In another embodiment, a processor device includes an FPGA or other programmable device that performs logic operations without processing computer-executable instructions. A processor device can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Although described herein primarily with respect to digital technology, a processor device may also include primarily analog components. A computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.
[0081] The elements of a method, process, routine, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor device, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of a non-transitory computer-readable storage medium. An exemplary storage medium can be coupled to the processor device such that the processor device can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor device. The processor device and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor device and the storage medium can reside as discrete components in a user terminal.
[0082] Conditional language used herein, such as, among others, "can," "may," "might," "may," “e.g.,” and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain alternatives include, while other alternatives do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more alternatives or that one or more alternatives necessarily include logic for deciding, with or without other input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular alternative. The terms “comprising,” “including,” “having,” and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term “or” is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term “or” means one, some, or all of the elements in the list.
[0083] Disjunctive language such as the phrase “at least one of X, Y, Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain alternatives require at least one of X, at least one of Y, or at least one of Z to each be present.
[0084] While the detailed description has shown, described, and pointed out novel features as applied to various alternatives, it can be understood that various omissions, substitutions, and changes in the form and details of the devices or algorithms illustrated can be made without departing from the scope of the disclosure. As can be recognized, certain alternatives described herein can be embodied within a form that does not provide all of the features and benefits set forth herein, as some features can be used or practiced separately from others.
, Claims:CLAIMS

We Claim:
1. A method for space saving in a shared memory of a base station in an Open-Radio Access Network (O-RAN) (100), the method comprising:
compressing one or more reference signals at an Open-Radio Unit (O-RU) (102) to form one or more compressed reference signals, wherein the one or more reference signals are one or more demodulation reference signals (DMRS) and one or more sounding reference signals (SRS); and
transmitting the one or more compressed reference signals from the O-RU (102) to an Open-Distributed Unit (O-DU) (104).

2. The method as claimed in claim 1, wherein the method comprises:
decompressing the one or more compressed reference signals at the O-DU (104), wherein the compression and the decompression occur within a prominent time, wherein the prominent time is the total time used in extraction, compression, transmission and decompression of the one or more reference signals, wherein the prominent time depends upon the number of reference signals.

3. The method as claimed in claim 1, wherein the method comprises:
extracting the one or more reference signals, transmitted by user equipment (UE), at the O-RU (102);
estimating, by the O-RU (102), the one or more reference signals for channel quality over a wider bandwidth;
compressing, by the O-RU (102), the one or more estimated reference signals;
transmitting the one or more compressed reference signals from the O-RU (102) to the O-DU (104); and
decompressing the one or more compressed reference signals at the O-DU (104).

4. The method as claimed in claim 3, wherein the one or more estimated reference signals are transmitted by the UE, by extracting a channel estimation of a sounding reference signal (SRS) and a demodulation reference signal (DMRS) at the O-RU (102) from at least one of a Physical Uplink Control Channel (PUCCH) and a Physical Uplink Shared Channel (PUSCH), wherein the PUSCH carries signaling messages, uplink control information, and application data.

5. The method as claimed in claim 1, wherein the one or more DMRS estimates a radio channel and the one or more SRS gives information about the combined effect of multipath fading, scattering, doppler, and power loss of a signal transmitted by a UE.

6. The method as claimed in claim 1, wherein the method comprises:
exchanging, by the O-RU (102), compression settings between the O-RU (102) and the O-DU (104) by a coding mechanism for the compression to decode one or more compressed reference signals successfully.

7. The method as claimed in claim 1, wherein the compression is performed by using a lossless compression technique, wherein data is recreated and recovered from compressed data which is identical to original data without loss of information.

8. The method as claimed in claim 1, wherein the compression is done by generating prefix codes of variable length which is uniquely decodable and shared to the O-DU (104).

9. The method as claimed in claim 1, wherein the method comprises:
measuring a compression ratio and a space ratio for space saving in the shared memory of the base station, wherein the compression ratio is defined as:
?????????????????????? ?????????? = (???????? ???? ???????????????? ???????? / ???????? ???? ???????????????????? ????????)
wherein the space ratio is defined as:
?????????? ?????????????? = (1 - ???????? ???? ???????????????????? ????????/???????? ???? ???????????????? ????????) × 100%

10. An Open Radio Access Network (O-RAN) (100), comprising:
a compression unit (206) for compressing one or more reference signals at an Open-Radio Unit (O-RU) (102) to form one or more compressed reference signals, wherein the one or more reference signals are one or more demodulation reference signals (DMRS) and one or more sounding reference signals (SRS); and
a decompression unit (306) for decompressing the one or more compressed reference signals, received from the O-RU (102), at an Open-Distributed Unit (O-DU) (104), wherein the compression and the decompression occur within a prominent time, wherein the prominent time is the total time used in extraction, compression, transmission and decompression of the one or more reference signals, wherein the prominent time depends upon the number of reference signals, wherein the compression and the decompression facilitate space saving in a shared memory of a base station in the O-RAN (100).

Dated this 3rd day of October 2022
Signature:

Name: Arun Kishore Narasani
Patent Agent (IN/PA 1049)