FORM 2
THE PATENTS ACT, 1970
(39 OF 1970)
AND
THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
“METHOD AND SYSTEM OF SMART NETWORK CONGESTION SOLUTION”
We, Reliance Jio Infocomm Limited, an Indian National of, 101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad-380006, Gujarat, India.
The following specification particularly describes the invention and the manner in which it is to be performed.

FIELD OF INVENTION
The embodiments of the present invention generally relate to wireless communication networks, and more particularly relates to congestion avoidance in a network comprising one or more NB-IoT device.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may 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.
Narrow Band-Internet of Things (NB-IoT) has recently emerged as a promising radio access connectivity solution for the low-powered end user IoT devices. The NB-IoT technology has been implemented in licensed bands, for instance, the licensed bands of LTE are used for implementing this technology. The NB-IoT technology utilizes a minimum system bandwidth of 180 KHz, i.e., one PRB (Physical Resource Block). The NB-IoT can be deployed in three modes, namely, “in-band”, “guard band” and “standalone”. In the “in-band” operation, resource blocks present within LTE carrier are used. The inner resource blocks are not used as they are allotted for synchronization of LTE signals. In “guard band” operation, resource blocks between LTE carriers that are not utilized by any operator are used. In “standalone” operation, GSM frequencies are used, or possibly unused LTE bands are used. Release 13 of the 3GPP contains important refinements like discontinuous reception (eDRX) and power save mode. The PSM (Power Save Mode) ensures battery longevity in release 12 and is completed by eDRX for devices that need to receive data more frequently.
The NB-IoT technology addresses some of the key IoT requirements, for instance, the battery lifetime of the devices increases, improved network coverage, cost of

the devices is reduced, multiplexing of devices met for capacity requirements, and supporting a massive number of devices. The NB-IoT technology support low power consumption, use of low-cost devices and provides excellent coverage. For example, in an NB-IoT deployment, the NB-IoT cells have a 20 dB gain over other categories like CAT 4/3/1 cells. As such, the NB-IoT Carrier can support much larger areas when compared to a CAT 4/3/1 base station or channel. Typically, in NB-IOT scenario, the same base station provides the NB-IoT channels for a device. The same or a different base station can provide a channel for a CAT-1 or a CAT 3/4 operation due to the difference in the NB-IoT and other category cell coverage areas.
Another key benefit of NB-IoT devices include energy optimization feature for operating the NB-IoT device on low-power consumption during a sleep mode as well as when the NB-IoT device is transmitting over the network. While other cellular technologies like LTE-M focus on saving power by sleeping and limiting their transmit time and frequency, the NB-IoT focus on its ability to sleep (with support for Extended Discontinuous Reception (eDRX) and minimize power consumption during data transmission, primarily due to the simplified data transmission method and lower data rate, which reduces the need to do power-hungry signal processing and improves the overall efficiency of the system. Secondly, NB-IoT possesses less complex radio design with a single antenna and are, accordingly, less expensive than other cellular technologies, reducing the barrier to integrate low-power cellular technology into their solutions. And thirdly, NB-IoT also provides improved range and obstacle penetration. Along with its reduced data rates and simplified radio design, NB-IoT has stronger link budgets than other cellular technologies, leading to greater coverage and strong building penetration, great for applications with devices deployed in difficult to reach places.
Smart NB-IoT devices (such as electric meters, etc.) are deployed by many utilities around the world, and with the technology available to smart meter manufacturers and utilities improving rapidly over the past few years, there is

scope for adding new and efficient technology to a rollout. There is a need for NB-IoT based smart-meter solution with capabilities to collect real-time voltage, current, power consumption and other information from the meter. NB-IOT based smart-meter solution optimizes and automates the meter reading process and enables accurate billing for electricity consumption. The smart IoT device meters are typically installed in locations where the network connectivity is hard to reach, such as in basements or inside cupboards and cabinets. Therefore, the network coverage is critical to ensure that every smart IoT device meter can be connected to the network and its management platform. The NB-IoT offers enhanced network coverage, allowing more smart meters to be connected. Although there is enhancement in coverage, the NB-IOT technology has limitations pertaining to network congestion where multiple smart-meters are expected to send the data at same time causing severe congestion at the Radio side.
Existing solutions provide deploying protocol agnostic wrapping and data analytics engine in SCEF which to take care of interoperability between different IOT devices using different application protocol to communicate with their application server, which is able to extract information and metrics from different entities and provide standard API which can be used by application servers. Another existing solution provides corrective actions taken by application to avoid heavy traffic by knowing SIB update data regarding barring in network from radio. The application becomes radio aware and also communicates the same to the application proxy client and server which can modify application behavior as per barring applied in network. Yet another existing solution describe a method to implement (calculate and report) CQI reporting in NBIOT, based on ENB request at radio level.
However, the existing solutions fail in case of multiple smart IoT devices installed in closed proximity probably in large numbers and in deep indoor coverage areas, with a possible crunch of Radio Resources due to congestion. Therefore, in the current system, there exists a major challenge to provide enhancement in

coverage as the NB-IOT technology has limitations pertaining to network congestion where in multiple NB-IoT devices are expected to send the data at the same time causing severe congestion. Therefore, there is a need for a system and a method to avoid such congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell.
SUMMARY
This section is provided to introduce certain objects and aspects of the present invention in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
In order to overcome at least a few problems associated with the known solutions as provided in the previous section, an object of the present invention is to provide a method and a system to avoid congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell. Another object of the present invention is to provide a method and a system to provide enhancement in performance as the NB-IOT technology has limitations pertaining to network congestion wherein multiple NB-IoT device are trying to send the data at same time causing severe congestion.
In order to achieve the aforementioned objectives, the present invention provides a method and system to avoid congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell. A first aspect of the present invention relates to a method to avoid congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell. A head end system receives, from the one or more NB-IoT device, a first set of parameters comprising at least one of a unique identifier of the at least one NB-IoT cell, a reference signal received power (RSRP) and a signal-to-noise ratio (SNR). The head end system determines a count of connected devices for each of the at least one NB-IoT cell and identifies a category for RSRP and SNR of each of the one or more NB-IoT device. It further

determines a phase for each of the one or more NB-IoT device and provides access to the one or more NB-IoT device based on the phase to avoid congestion in the network.
Another aspect of the present invention relates to a system to avoid congestion in a network. The system comprises one or more NB-IoT device connected to the network via at least one NB-IoT cell, said one or more NB-IoT device configured to transmit a first set of parameters from the one or more NB-IoT device, wherein the first set of parameters comprises at least one of a unique identifier of the at least one NB-IoT cell, a reference signal received power (RSRP) and a signal-to-noise ratio (SNR). The system also comprises a head end system connected to the one or more NB-IoT device via the at least one NB-IoT cell, said head end system configured to receive the first set of parameters from the one or more NB-IoT device. The head end system is also configured to determine a count of connected devices for each of the at least one NB-IoT cell based on the first set of parameters and to identify a category for RSRP and SNR of each of the one or more NB-IoT device. The head end system is also configured to determine a phase for each of the one or more NB-IoT device based on the categorization and the count and provide access to the one or more NB-IoT device based on the phase of the one or more NB-IoT device to avoid congestion in the network.
BRIEF DESCRIPTION OF DRAWINGS
The accompanying drawings, which are incorporated herein, and constitute a part of this invention, 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 invention. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that invention of

such drawings includes the invention of electrical components, electronic components or circuitry commonly used to implement such components.
FIG.1 illustrates an exemplary block diagram representation of a system [100] to avoid congestion in a network, in accordance with exemplary embodiments of the present invention.
FIG.2 illustrates an exemplary method flow diagram depicting a method [200] to avoid congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell, in accordance with exemplary embodiments of the present invention.
FIG.3 illustrates an exemplary signal exchange diagram between an NB-IoT device and a head End System (HES), in accordance with exemplary embodiments of the present invention.
FIG.4 illustrates an exemplary signal flow diagram depicting a method to avoid congestion in a network, in accordance with exemplary embodiments of the present invention.
FIG.5 illustrates another exemplary signal flow diagram depicting a method to avoid congestion in a network, in accordance with exemplary embodiments of the present invention.
The foregoing shall be more apparent from the following more detailed description of the invention.
DETAILED DESCRIPTION OF INVENTION
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 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 all 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.
The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. 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 invention as set forth.
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 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.
Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a 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 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.

Furthermore, embodiments may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks (e.g., a computer-program product) may be stored in a machine-readable medium. A processor(s) may perform the necessary tasks.
The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, 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 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—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout 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.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly 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 features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.
As used herein, the term “infers” or “inference” refers generally to the process of reasoning about or inferring states of the system, environment, user, and/or intent from a set of observations as captured via events and/or data. Captured data and events can include user data, device data, environment data, data from sensors, sensor data, application data, implicit data, explicit data, etc. Inference can be employed to identify a specific context or action or can generate a probability distribution over states of interest based on a consideration of data and events, for example. Inference can also refer to techniques employed for composing higher-level events from a set of events and/or data. Such inference results in the construction of new events or actions from a set of observed events and/or stored event data, whether the events are correlated in close temporal proximity, and whether the events and data come from one or several event and data sources. Various classification schemes and/or systems (e.g., support vector machines, neural networks, expert systems, Bayesian belief networks, fuzzy logic, and data fusion engines) can be employed in connection with performing automatic and/or inferred action in connection with the disclosed subject matter.
In addition, the disclosed subject matter may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter. The term “article of manufacture” as used herein is intended to encompass a computer program accessible from any computer-readable device, computer-readable carrier, or computer-readable media. For example,

computer-readable media can include, but are not limited to, magnetic storage devices, e.g., hard disk; floppy disk; magnetic strip(s); optical disk (e.g., compact disk (CD), digital video disc (DVD), Blu-ray Disc™ (BD); smart card(s), flash memory device(s) (e.g., card, stick, key drive).
As used herein, “user device” or "user equipment“, “mobile station,” “mobile subscriber station,” “access terminal,” “terminal,” “handset,” and similar terminology refers to any electrical, electronic, electromechanical and computing wireless device utilized by a subscriber or user of a wireless communication service to receive and/or convey data associated with voice, video, sound, and/or substantially any data-stream or signaling-stream. Further, the foregoing terms are utilized interchangeably in the subject specification and related drawings. The user device is capable of receiving and/or transmitting one or parameters, performing function/s, communicating with other user devices and transmitting data to the other user devices. The user device may have a processor, a display, a memory unit, a battery and an input-means such as a hard keypad and/or a soft keypad. The input interface also comprises touch/acoustic/video components for touch/sound/video input and output. The output interface may comprise a microphone, a speaker, camera and additionally audio/video I/O ports in an accessories interface, wherein the speaker normally serves to provide acoustic output in the form of human speech, ring signals, music, etc. The user device may be capable of operating on any radio access technology including but not limited to IP-enabled communication, Zig Bee, Bluetooth, Bluetooth Low Energy, Near Field Communication, Z-Wave, NB-IoT etc. For instance, the user devices may include, but not limited to, a mobile phone, smartphone, virtual reality (VR) devices, augmented reality (AR) devices, pager, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other device as may be obvious to a per-son skilled in the art.
The terms “node”, “local wireless communications cite,” “access point” (AP), “base station”, “Node B”, “evolved Node B (eNodeB)”, “home Node B” (HNB),

“home access point” (HAP), and the like are utilized interchangeably in the subject specification and drawings and refer to devices that can receive and transmit signal(s) from and to wireless devices through one or more antennas, or act as a wireless network component or apparatus that sends and/or receives data associated with voice, video, sound, and/or substantially any data-stream or signaling-stream between a set of subscriber stations—unless context warrants particular distinction(s) among the terms. Further, the data and signaling streams can be packetized or frame-based flows. As used herein, “at least one NB-IoT cell” may refer to one or more base stations or cells which provide a network coverage to a geographic coverage area, thus the geographic area served by the one or more cells is termed as coverage area of the one or more cells.
Furthermore, the terms “user,” “subscriber,” “customer,” “consumer,” “agent,”, “owner,” and the like are employed interchangeably throughout the subject specification and related drawings, unless context warrants particular distinction(s) among the terms. It should be appreciated that such terms can refer to human entities, or automated components supported through artificial intelligence, e.g., a capacity to make inference based on complex mathematical formulations, that can provide simulated vision, sound recognition, decision making, etc. In addition, the terms “wireless network” and “network” are used interchangeable in the subject application, unless context warrants particular distinction(s) among the terms.
As used herein, a “processor” or “processing unit” includes one or more processors, wherein processor refers to any logic circuitry for processing instructions. A processor may be a general-purpose processor, a special-purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, a low-end 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 functionality that enables

the working of the system according to the present disclosure. More specifically, the processor or processing unit is a hardware processor.
As used herein, a “communication unit” or a “transceiver unit” may include at least one of a “transmitter unit” configured to transmit at least one data and/or signals to one or more destination and a “receiver unit” configured to receive at least one data and/or signals from one or more source. The “communication unit” or the “transceiver unit” may also be configured to process the at least one data and/or signal received or transmitted at the “communication unit” or the “transceiver unit”. Also, the “communication unit” or the “transceiver unit” may further include, any other similar units obvious to a person skilled in the art, required to implement the features of the present invention.
As used herein, “memory unit”, “storage unit” and/or “memory” refers to a machine or computer-readable medium including any mechanism for storing information in a form readable by a computer or similar machine. For example, a computer-readable medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices or other types of machine-accessible storage media.
As used herein, a “controller” or “control unit” includes at least one controller, wherein the controller refers to any logic circuitry for processing instructions. A controller may be a general-purpose controller, a special-purpose controller, a conventional controller, a digital signal controller, a plurality of microcontrollers, at least one microcontroller in association with a DSP core, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The controller may perform signal coding, data processing, input/output processing, and/or any other functionality that enables the working of the system according to the present disclosure. More specifically, the controller or control unit is a hardware processor that comprises a memory and a processor. The memory is configured to store the

modules and the processor is specifically configured to execute said modules to perform one or more processes which are described further below.
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present disclosure.
Embodiments of the present disclosure relate to a method and a system to avoid congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell. The solution describes that a head end system receives the NB Cell information and the RF condition of the NB-cell to which the NB-IoT device is camped on. The NB-IoT device information comprises at least one of a unique identifier of the at least one NB-IoT cell, a reference signal received power (RSRP) and a signal-to-noise ratio (SNR). The head end system determines a count of connected devices for each of the at least one NB-IoT cell and identifies a category for RSRP and SNR of each of the one or more NB-IoT device. It further determines a phase for each of the one or more NB-IoT device and provides access to the one or more NB-IoT device based on the phase to avoid congestion in the network.
As used herein, “one or more NB-IoT device” refers to one or more such user device operating on NB-IoT radio access technology. In an instance of the invention, the one or more NB-IoT device [102] is a chipset-based device, capable of supporting at least one power saving mode. For example, the one or more NB-IoT device [102] is capable of supporting the Power Saving Mode (PSM) and the extended idle-mode discontinuous reception (eDRX), like, smart measuring devices, utility metering devices, etc.
The invention encompasses that the one or more NB-IoT device [102] is operated by a subscriber within a coverage area typically communicates with the network via an eNodeB [104]. The eNodeB [104] is configured to perform radio interface transmission and reception, and including, but not limited to, radio channel modulation/ demodulation, channel coding/ decoding and multiplexing/

demultiplexing. The eNodeB [104] is also configured to manage the System information Broadcast (SIB) in each NB-IoT cell on the downlink radio interface to provide basic information to one or more NB-IoT device [102] as a prerequisite to access the network. The eNodeB [104] is also configured to transfer dedicated non-access stratum (NAS) information, and to transfer radio access capability information of the one or more NB-IoT device [102] to the core network. In operation, the one or more NB-IoT device [102] registers with the eNodeB and accordingly, the subscriber’s communication, e.g., voice traffic, data traffic, can be routed to the subscriber through the eNodeB [104] utilizing the licensed radio spectrum. The eNodeB can employ a backhaul network, e.g., broadband wired or wireless network backbone, to route packet communication, e.g., voice traffic, data traffic, data, to the core network.
Referring to FIG.1 illustrates an exemplary block diagram representation of a system to avoid congestion in a network, in accordance with exemplary embodiments of the present invention. The system comprises of one or more NB-IoT device [102A, 102B, … 102F, hereinafter collectively referred to as 102] with each having Network Interface Card (NIC) [114A, 114B, ... 114F, hereinafter collectively referred to as 114] connected to a control system [100] via at least one NB-IoT cell [104] and a modem client module [116] (not shown in the figure). The control system [100] further comprises of a Head End System (HES) [106], meter data management system (MDMS) [108], a utility supply [110], a system database [112]. The control system [100] is an electronic device configured to record consumption of utilities, for example electric energy, and communicates the information of measured consumption to the energy supplier for monitoring and billing. The control system [100] may typically record energy hourly or more frequently, and report at least daily. The control system [100] of the present invention provides a solution to reduce load over a single cell and increase the efficiency of the network.
The HES [106], also known as meter control system, is located within the Solution Providers Network or the Solution Providers Cloud Infrastructure. The main

objective of HES [106] is to acquire metering data automatically from the one or more NB-IoT devices [102] avoiding any human intervention and monitor parameters acquired from the one or more NB-IoT devices [102] (for example, meters). In this regard, the HES [106] is configured to receive a first set of parameters from the one or more NB-IoT device [102]. The first set of parameters comprises at least one of a unique identifier of the at least one NB-IoT cell [104], a reference signal received power (RSRP) and a signal-to-noise ratio (SNR). The HES [106] is configured to determine a count of connected devices for each of the at least one NB-IoT cell [104] based on the first set of parameters, and to identify a category for RSRP and SNR of each of the one or more NB-IoT device. The category is one of a best, an ideal, a poor and a worst. Further, based on the categorization and the count, the HES [106] determines a phase for each of the one or more NB-IoT device [102]. The HES [106] provides access (hereinafter also referred to as “polling”) to the one or more NB-IoT device [102] based on the phase of the one or more NB-IoT device [102] to avoid congestion in the network.
The present invention also encompasses that the HES [106] compares the count of connected devices for the at least one NB-IoT cell [104] with a threshold count, and classifies the at least one NB-IoT cell [104] into one of an even cell and an odd cell based on the unique cell identifier of the at least one NB-IoT cell [104] in event the count of connected devices for the at least one NB-IoT cell [104] exceeds a threshold count. Accordingly, the HES [106] determines a phase for each of the one or more NB-IoT device [102] based on the classification of the at least one NB-IoT cell [104] and provides access to the one or more NB-IoT device [102] based on the phase of the one or more NB-IoT device.
The present invention also encompasses that the HES [106] compares the count of connected devices for each of the at least one NB-IoT cell [104] with a minimum count and assigns a high priority to the one or more devices connected to the at least one NB-IoT cell [104] based on the comparison in an event the count of connected devices for the at least one NB-IoT cell [104] exceeds a

minimum count. Accordingly, the HES [106] provides access to the one or more NB-IoT device [102] connected to the at least one NB-IoT cell [104] based on the assignment at a higher priority. The present invention further encompasses that the HES [106] is based on at least one of an Advanced Metering Infrastructure (AMI) or Automatic Meter Reading (AMR) systems.
The meter data management system (MDMS) [108] is configured to collect data from the HES [106] and performs validation and cleansing of the data before making it available for billing and analysis. The MDMS performs long term data storage and management for the vast quantities of data delivered by smart metering systems. This data consists primarily of usage data and events imported from the HES [106]. The utility supply [110] refers to a receiving unit for supply provided by a distribution company (DISCOM). For instance, DISCOM takes electricity from transmission companies and undertake and manage the distribution of the electricity to the consumers, and the utility supply unit [110] receives electricity from the DISCOM. The system database [112] is configured to store the data obtained by the HES [106]. In an instance, the system database [112] is a Solution Providers Data Base that performs real-time monitoring of the data obtained from the HES [106] for further analysis.
The NIC [114] is a hardware component that connects the NB-IoT device [102] to the at least one NB-IOT cell [104] and enables communication with the HES [106] in the network. Referring to FIG.3 illustrates an exemplary signal exchange diagram between an NB-IoT device and a head End System (HES), in accordance with exemplary embodiments of the present invention. In one of the preferred embodiments and to aid in understanding about various aspects of the disclosure, the block diagram depicts the key functionalities of various modules in the embedded NB-IOT ecosystem. Distribution Line Message Specification (DLMS) is an application layer specification which is used by the Embedded Application. NIC [114] of the NB-IoT device [102] and the HES [106] supports standard DLMS protocol on top of TCP. It is independent of the lower layers and thus of the communication channel, designed to support messaging to and from

(energy) distribution devices in a computer-integrated environment. The NIC [114] further comprises of a DLMS Embedded Client which is a DLMS Application that fetches the data from the control system [100] over the Serial Port of the NB-Iot device [102] (e.g., a meter).
Further, the NIC [114] comprises an Object Identification System (OBIS) for identification of data objects in DLMS communication. The OBIS codes are used as Logical names of data objects. The DLMS User Association defines and allocates OBIS codes and maintains list of valid OBIS codes. DLMS provides a rich set of standard objects to support a wide functionality of metering equipment. However, in order to support innovation, manufacturer specific objects can be defined and used. These will be identified by manufacturer specific OBIS codes. An OBIS code is manufacturer specific, if any of the value groups B to D has a value between 128 and 254. As the RF Parameters are not a part of the Metering Data, an OBIS Code can be defined to identify the RF Parameters and then will be forwarded to the Application which will report the Data to HES using DLMS. The modem client module [116] is configured to reads specific data set (e.g.: RSRP, SINR) from the modem on reception of the event notification (Attach or Reselection). Upon obtaining the dataset from the modem, it forms a record in a pre-defined format and forwards the Data set to the embedded client.
Referring to FIG.2 illustrates an exemplary method flow diagram depicting a method [200] to avoid congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell, in accordance with exemplary embodiments of the present invention. The method is performed at the head end system [106]. The method begins at step [202]. The method at step [204] comprises receiving a first set of parameters from the one or more NB-IoT device [102]. The first set of parameters comprises at least one of a unique identifier of the at least one NB-IoT cell [104], a reference signal received power (RSRP) and a signal-to-noise ratio (SNR). The invention encompasses the one or more NB-IoT device [102] transmitting the first set of parameters to the head end system [106]. In operation, when a new one or more NB-IoT device [102] is

configured with the NIC [114] and turned on, the modem selects a suitable NB-IoT cell [104] and attaches the one or more NB-IoT device [102] to the NB-IoT network. The modem client module [116] collects the network parameters from the NB-IoT device (or modem) like the Cell ID, RSRP and SNR on occurrence of specific events like Attach Accept or Reselection and passes the information to the embedded client. The embedded client concurrently establishes a connection with the HES [106] and reports the parameters to the HES [106].
At step [206], the method comprises the head end system [106] determining a count of connected devices for each of the at least one NB-IoT cell [104] based on the first set of parameters. At step [208], the head end system [106] identifies a category for RSRP and SNR of each of the one or more NB-IoT device [102]. In operation, the HES [106] stores the information for each of the one or more NB-IoT device [102] within the system database [110] and categorizes the one or more NB-IoT device [102] based on the network parameters, for e.g. the three exemplary databases created by the HES [106] are a cell ID database, a RSRP database and a SNR database. The category is one of a best, an ideal, a poor and a worst. For example, the HES [106] creates following exemplary categories for RSRP measurements (illustrated in Table 1):

Best -40 to -80 dBm
Ideal -80 to -100 dBm
Poor -100 to -105 dBm
Worst >-105 dBm
Table 1
In another example, the HES [106] creates following exemplary categories for SNR measurement (illustrated in Table 2):

Best >3 dB
Ideal 0 to 3 dB
Worst <0 dB
Table 2
At step [210], the head end system [106] determining a phase for each of the one or more NB-IoT device [102] based on the categorization and the count. For instance, in operation, the HES [106] creates a polling criteria for each of the one or more NB-IoT device [102]. The criteria filter out those meters which are not more than 10 in number served by the at least one NB-IoT cell [104], i.e., a single cell. The HES [106] poll the one or more NB-IoT device [102] in phases as below (illustrated in Table 3):

Ideal Mid Poor Worst
Polling Matrix -50 to -80 -80 to -100 -100 to -105 >-105
Best >3 Phase 1 Phase 4 Phase 7 Phase 10
Ideal 0 to 3 Phase 2 Phase 5 Phase 8 Phase 11
Worst <0 Phase 3 Phase 6 Phase 9 Phase 12
Table 3
The invention also encompasses that the HES [106] compares the count of connected devices for the at least one NB-IoT cell [104] with a threshold count, and classifies the at least one NB-IoT cell [104] into one of an even cell and an

odd cell based on the unique cell identifier of the at least one NB-IoT cell [104] in event the count of connected devices for the at least one NB-IoT cell [104] exceeds a threshold count. Accordingly, the HES [106] determines a phase for each of the one or more NB-IoT device [102] based on the classification of the at least one NB-IoT cell [104] and provides access to the one or more NB-IoT device [102] based on the phase of the one or more NB-IoT device.
In operation, if the number of NB-IoT device [102] in any phase belonging to the at least one NB-IoT cell [104] exceeds ‘n’ (a configurable number), the number of NB-IoT device [102] within that phase can be further divided into Sub Categories based on the Cell ID’s, for e.g., Category 1: Meters Belonging to Odd Cell IDs, and Category 2: Meters Belonging to Even Cell IDs. Accordingly, in event ‘n’ devices are to be polled, ‘n’ number of NB-IoT devices from each odd numbered cell in phases are polled till all the meter from this category are polled. Subsequently, ‘n’ number of NB-IoT devices from each even numbered cell in phases are polled till all the meter from this category are polled. The sequence adopted in the present invention is merely illustrative, and any other sequence can be adopted by a person skilled in the art to achieve the object of the present invention.
In an illustration, referring to Table 4 below, if the number of NB-IoT devices in Phase 5 are 110 and out of it, 30 meters belong to a particular single Cell (Cell ID 8).

Phases Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
Total meters Phase wise/ Cell IDs 100 160 80 90 110
Cell ID 1 5 15 0 30 5
Cell ID 2 20 20 5 20 5

Cell ID 3 10 25 5 10 20
Cell ID 4 25 30 0 5 0
Cell ID 5 5 20 10 5 5
Cell ID 6 0 10 10 10 5
Cell ID 7 10 10 5 10 10
Cell ID 8 10 10 5 0 30
Cell ID 9 10 10 10 0 20
Cell ID 10 5 10 20 0 10

Meters more than 10 in a
cell

Meters less than 10 in a
cell
Table 4
Out of 110 NB-IoT devices from Phase 5, 40 NB-IoT devices do not meet the criteria (Number of meters in any Phase, belonging to a single particular cell exceeds 10 (n=10)) hence, those NB-IoT devices will be polled according to the defined Phases (illustrated below in Table 5). The NB-IoT devices polled are illustrated in Tables 6 and 7.

Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
Number of meters less than 10
in a cell and will be polled
immediately in Phases 55 50 50 40 40
Remaining meters 45 110 30 50 70
Odd Cell ID 0 60 0 30 40
Even Cell ID 45 50 20 20 30
Table 5

Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
Poll 10 NB-IoT device from each odd numbered Cell ID Phase wise till all the NB-IoT device are polled 0 10 0 10 10

0 10 0 10 10

0 10 0 10 10

0 10 0 0 10

0 10 0 0 0

0 10 0 0 0
Table 6

Phase 1 Phase 2 Phase 3 Phase 4 Phase 5
Poll 10 NB-IoT device from each odd numbered Cell ID Phase wise till all the NB-IoT device are polled 10 10 10 10 10

10 10 10 10 10

10 10 0 0 10

10 10 0 0 0

5 10 0 0 0
Table 7
The remaining 70 meters will go through another round of categorization where odd numbered NB-IoT devices and even numbered NB-IoT devices are sorted out and polled according to the above description at step [212]. The method completes at step [214].
The present invention also encompasses that the HES [106] compares the count of connected devices for each of the at least one NB-IoT cell [104] with a minimum count and assigns a high priority to the one or more devices connected to the at least one NB-IoT cell [104] based on the comparison in an event the count of connected devices for the at least one NB-IoT cell [104] exceeds a minimum count. Accordingly, the HES [106] provides access to the one or more NB-IoT device [102] connected to the at least one NB-IoT cell [104] based on the assignment at a higher priority. For instance, in the above illustration, the HES [106] will rank the meters according to criteria and the cell conditions reported. The criteria will filter out those meters that are not more than 10 in numbers served by a single cell. The HES [106] considers these meters as high priority meters and the same will be communicated to the meters which in turn will report the events to the HES [106] immediately at occurrence. The rest of the

meters will have to go through the same categorization through which the HES [106] will rank them based on the categorization. The reporting time lag based on rank will be communicated to all the meters immediately after these meters report the parameters to the HES [106] or whenever the rank and reporting time lag will change. The meters once subjected to the events like Power Failure/Resume and Tampering will store the events and then report to the HES [106] in timely manner based on their Ranks (as illustrated in Table 8 below).

Ideal Mid Poor Worst
Polling Matrix -50 to -80 -80 to -100 -100 to -105 >-105
Best >3 Rank 1(5 sec) Rank Sec) 4(20 Rank 7(35 Sec) Rank 10(50 Sec)
Ideal 0 to 3 Rank 2(10 sec) Rank Sec) 5(25 Rank 8(40 Sec) Rank 11(55 Sec)
Worst <0 Rank 3(15 Sec) Rank Sec) 6(30 Rank 9(45 Sec) Rank 12(60 Sec)
Table 8
Different Time lags can be defined to these Sub-ranks and the meters can report according to these Sub Ranks. Those meters in any Rank, belonging to a single particular cell fall below the configurable number ‘n’ can report the events according to their Rank and time lags.
Referring to FIG.4 illustrates an exemplary signal flow diagram depicting a method to avoid congestion in a network, in accordance with exemplary embodiments of the present invention. In the exemplary implementation, the NB-IoT device [102] is a smart meter. At step [402], the method is initiated. At

step [404], when a new smart meter is configured with a NIC and turned on, the modem will select a suitable NB-IoT cell and attach to the NB-IoT network. The modem client module will collect the network parameters from the modem like the Cell ID, RSRP and SNR on occurrence of specific events like Attach Accept or Reselection and pass on the information to the Embedded client. The embedded client will immediately establish a connection to the HES [106] and report the parameters to the HES [106]. At step [406], the HES [106] stores the information for each such smart Meter within the designated area and categorizes these meters and create different data bases based on these network parameters e.g. Cell ID database, RSRP database and SNR database. Step [410] onwards, the HES [106] creates a polling criteria (Criteria A) for each NB-IoT cell. At step [410], the criteria filter out those meters which are not more than 10 in number served by a single cell. The HES [106] assigns the smart meters high priority at step [430] and poll these meters at first go high priority at step [432]. For other smart meters which doesn’t meet Criteria A, the HES [106] creates sub-categories of database at step [414]. At step [416], the method implements conditions of Tables 1 and 2 illustrated above. At step [418], the HES [106] creates a polling Matrix through which it will start polling the meters in phases illustrated in Table 3 above at step [428].
At step [420], if the number of meters is too high i.e. If the number of meters in any Phase, belonging to a single particular cell exceeds n (configurable number) the number of meters within that phase can be further divided into sub-categories based on the Cell ID’s. Further, at step [422], in event the number of meters in any Phase belonging to a single particular cell exceeds ‘n’ (configurable value), the smart meters are categorized into meters Belonging to Odd Cell IDs, and meters Belonging to Even Cell IDs. Accordingly, at step [426], the smart meters can be poll ‘n’ (configurable value) meters from each odd numbered Cell in Phases till all the meter from this category are polled. Subsequently, at step [426], the smart meters poll ‘n’ (configurable value) meters from each even

numbered Cell in Phases till all the meter from this category are polled. The method completes at step [434].
Referring to FIG.5 illustrates another exemplary signal flow diagram depicting a method to avoid congestion in a network, in accordance with exemplary embodiments of the present invention. In the exemplary implementation, the NB-IoT device [102] is a smart meter. At step [502], the method is initiated. At step [504], when a new smart meter is configured with a NIC and turned on, the modem will select a suitable NB-IoT cell and attach to the NB-IoT network. The modem client module will collect the network parameters from the modem like the Cell ID, RSRP and SNR on occurrence of specific events like Attach Accept or Reselection and pass on the information to the Embedded client. The embedded client will immediately establish a connection to the HES [106] and report the parameters to the HES [106]. At step [506], the HES [106] stores the information for each such smart Meter within the designated area and categorizes these meters and create different data bases based on these network parameters e.g. Cell ID database, RSRP database and SNR database.
At step [508], the HES [106] ranks the smart meters according to criteria (criteria A) and the NB-IoT cell conditions are reported. At step [510], the criteria will filter out those meters that are not more than 10 in numbers served by a single Cell. The HES [106] consider these meters as high priority meters and the same will be communicated to the meters at step [526] which in turn will report the events to the HES [106] immediately at occurrence as per step [528]. For other smart meters which doesn’t meet Criteria A, the HES [106] assigns these meters as low priority meters, categorizes the meters in different sub-categories by creating different data bases depending upon these sub-categories at step [512]. At step [514], the HES [106] categorizes the meters according to the reported RSRP and the reported SNR. At step [516], the method implements conditions of Tables 1 and 2 illustrated above. At step [518], the HES [106] ranks them based on the categorization. The reporting time lag based on rank is communicated to all the smart meters immediately after these smart meters report the

parameters to HES [106] or whenever the rank and reporting time lag will change. The smart meters once subjected to the events like Power Failure/Resume and Tampering will store the events and then report to the HES [106] in timely manner based on their Ranks at step [524]. The id method can be further extended to achieve more reliability if the number of meters is too high i.e. at step [520], the HES [106] determines if the number of meters in any Rank, belonging to a single particular cell exceeds n (configurable number), the number of meters within that phase can be further divided into sub-categories based on the Cell ID’s and Sub Ranks can be assigned to these meters based on the sub categorization at step [522]. For instance, different Time lags can be defined to these Sub-ranks and the meters can report according to these sub ranks. In another instance, those meters in any Rank, belonging to a single particular cell fall below the configurable number ‘n’ can report the events according to their Rank and time lags (illustrated in Table 8).
Thus, the present invention provides a novel solution for the technical problem of avoiding congestion in a network comprising one or more NB-IoT device connected to the network via at least one NB-IoT cell. The solution of the present invention provides enhancement in RF performance as the NB-IOT technology has limitations pertaining to network congestion wherein multiple NB-IoT device are trying to send the data at same time causing severe congestion.
While considerable emphasis has been placed herein on 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 invention. These and other changes in the preferred embodiments of the invention 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 to be implemented merely as illustrative of the invention and not as limitation.

We Claim
1. A method to avoid congestion in a network comprising one or more NB-
IoT device [102] connected to the network via at least one NB-IoT cell
[104], the method being performed by a head end system [106], the
method comprising:
- receiving a first set of parameters from the one or more NB-IoT device
[102] wherein
- the first set of parameters comprises at least one of a unique identifier of the at least one NB-IoT cell [104], a reference signal received power (RSRP) and a signal-to-noise ratio (SNR);
- determining a count of connected devices for each of the at least one NB-IoT cell [104] based on the first set of parameters;
- identifying a category for RSRP and SNR of each of the one or more NB-IoT device [102];
- determining a phase for each of the one or more NB-IoT device [102] based on the categorization and the count; and
- providing access to the one or more NB-IoT device [102] based on the phase of the one or more NB-IoT device [102] to avoid congestion in the network.

2. The method as claimed in claim 1, wherein the category is one of a best, an ideal, a poor and a worst.
3. The method as claimed in claim 1, further comprising:
- determining that a count of connected devices for the at least one NB-IoT
cell [104] exceeds a threshold count;

- classifying the at least one NB-IoT cell [104] into one of an even cell and an odd cell based on the unique cell identifier of the at least one NB-IoT cell [104];
- determining a phase for each of the one or more NB-IoT device [102] based on the classification of the at least one NB-IoT cell [104]; and
- providing access to the one or more NB-IoT device [102] based on the phase of the one or more NB-IoT device.
4. The method as claimed in claim 1, wherein determining a phase for each
of the one or more NB-IoT device [102] based on the categorization and
the count further comprises:
- comparing the count of connected devices for each of the at least one NB-IoT cell [104] with a minimum count;
- assigning a high priority to the one or more devices connected to the at least one NB-IoT cell [104] based on the comparison.

5. The method as claimed in claim 4, further comprising providing access to the one or more NB-IoT device [102] connected to the at least one NB-IoT cell [104] based on the assignment.
6. A system to avoid congestion in a network, the system comprising:
- one or more NB-IoT device [102] connected to the network via at least
one NB-IoT cell [104], said one or more NB-IoT device [102] configured to
transmit a first set of parameters from the one or more NB-IoT device
[102] wherein
- the first set of parameters comprises at least one of a unique identifier of the at least one NB-IoT cell [104], a reference signal received power (RSRP) and a signal-to-noise ratio (SNR); and

- a head end system [106] connected to the one or more NB-IoT device
[102] via the at least one NB-IoT cell [104], said head end system [106]
configured to:
- receive the first set of parameters from the one or more NB-IoT device,
- determine a count of connected devices for each of the at least one NB-IoT cell [104] based on the first set of parameters,
- identify a category for RSRP and SNR of each of the one or more NB-IoT device,
- determine a phase for each of the one or more NB-IoT device [102] based on the categorization and the count, and
- provide access to the one or more NB-IoT device [102] based on the phase of the one or more NB-IoT device [102] to avoid congestion in the network.

7. The system as claimed in claim 6, wherein the category is one of a best, an ideal, a poor and a worst.
8. The system as claimed in claim 6, wherein the head end system [106] is further configured to:

- determine that a count of connected devices for the at least one NB-IoT cell [104] exceeds a threshold count;
- classify the at least one NB-IoT cell [104] into one of an even cell and an odd cell based on the unique cell identifier of the at least one NB-IoT cell [104];
- determine a phase for each of the one or more NB-IoT device [102] based on the classification of the at least one NB-IoT cell [104]; and

- provide access to the one or more NB-IoT device [102] based on the
phase of the one or more NB-IoT device.
9. The system as claimed in claim 6, wherein the head end system [106] is further configured to:
- compare the count of connected devices for each of the at least one NB-IoT cell [104] with a minimum count;
- assign a high priority to the one or more devices connected to the at least one NB-IoT cell [104] based on the comparison; and
- provide access to the one or more NB-IoT device [102] connected to the at least one NB-IoT cell [104] based on the assignment.