WO2020021504A1

WO2020021504A1 - System and method for load balancing in a cellular network

Info

Publication number: WO2020021504A1
Application number: PCT/IB2019/056396
Authority: WO
Inventors: Brijesh Shah; Manish Kumar Patel; Mayank Taran; Amarjith Karippath
Original assignee: Reliance Jio Infocomm Limited
Priority date: 2018-07-27
Filing date: 2019-07-26
Publication date: 2020-01-30

Abstract

A system and method for automatic load balancing of a serving cell in a cellular network comprising a plurality of serving cells, is disclosed. The present invention optimally addresses the problems existing in prior arts, by automatically identifying and optimizing unbalanced cells to improve network quality and coverage in congested areas, thereby mitigating the problem of congestion and facilitating high overall user experience. In the present invention, network parameters along with user device parameters and load balancing parameters are considered to perform load balancing between an unbalanced source cell to one or more balanced target cells.

Description

SYSTEM AND METHOD FOR LOAD BALANCING IN A CELLULAR NETWORK

TECHNICAL FIELD

The present disclosure generally relates to wireless networks, and more particularly relates to the identification and optimization of unbalanced cells to improve network quality and coverage in congested areas. Thereby, the proposed solution optimizes the unbalanced cells by load balancing between high loaded cells and less loaded cells, resulting in reduced congestion and hence, improving the quality of service.

BACKGROUND

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.

Today with the advent of wireless technology like GMS (Global System for Mobile communications), EDGE (Enhanced Data rates for GSM Evolution), HSPA (High Speed Packet Access), LTE (Long-Term Evolution), etc. all communications in a wireless network provides various communication services such as voice, video, data, advertisement, content, messaging, broadcasts, etc. have usually multiple access networks, support communications for multiple users by sharing the available network resources. With the advent of technology, demand for higher capacity and higher data transfer speeds have increased, however such demands are impacted because of problems associated with the cells and optimization of the cells in a cellular network.

Currently, Mobility Load Balancing (MLB) or Idle mode Mobility Load Balancing (IMLB) features are used for load balancing between the cells. Mobility Load Balancing (MLB) enables an eNodeB (E- UTRAN Node B) to release an overload of a cell or to maintain a cell load difference between colocated inter-frequency cells only. For intra-LTE MLB, the eNodeB periodically monitors the cell load status of its own cells along with neighbor cells. If the load of the serving cell reaches a threshold value, and a load of the neighbor cell is relatively low, the eNodeB relocates some selected user equipment (UE) from a higher-loaded cell to lower-loaded neighbor cells based on Physical Resource Block (PRB) Utilization and number of Radio Resource Control (RRC) connected users.

IMLB (Idle mode Mobility Load Balancing) is used to distribute the UE, i.e., a load, in idle mode, between highly loaded cells and lightly loaded cells. The load is shared between the neighbor cells periodically. The cell load for triggering the IMLB is calculated over a configured duration, by exponential moving average.

If the serving cell load, at the end of configured duration, is greater than a predefined threshold, the UEs are configured to go idle with dedicated cell reselection priorities in the "RRC connection release" message. After being configured with the cell reselection priorities, the UEs have a high probability to reselect the lightly loaded carrier cells. Thus, the UEs will be distributed in idle mode such that, the load will be distributed evenly in all the cells when they come to a connected state.

Other similarly known conventional solutions for load balancing have been known in the prior arts, some of which are provided below:

1. Load Balancing in Downlink LTE Self-Optimizing Networks - In this solution, it is proposed that, in the existing networks, parameters are manually adjusted to obtain a high level of network operational performance. In LTE, the concept of self-optimizing networks (SON) is introduced, where the parameter tuning is done automatically based on measurements. The load balancing aims at finding the optimum handover offset (HO) value between the overloaded cell and a possible target cell. This optimized offset value ensures that the users that are handed over to the target cell, will not be returned to the source cell, thus the load in the current cell is diminished.

2. A High-efficient Method of Mobile Load Balancing in LTE System- In this solution, the proposed method adjusts the cell-specific offset between neighboring cells (OCN) adaptively depending on the load difference between neighboring cells. If the load difference exceeds the presetting threshold, then the method will be triggered and adjust the OCN by adding or subtracting an adaptive step-size. Further, a power function is proposed to characterize an adaptive step-size, and the step-size will be larger as the load difference between neighboring cells increases. This feature of the power function makes the MLB algorithm more efficient to fit the largely uneven load between neighboring cells. Furthermore, a simulation platform with seven cells is set to evaluate the method with different power of the function.

The current solutions provided above describes features that pushes UEs randomly to neighboring cells based only on DL PRB Utilization and number of RRC connected users of the target cell in case the source cell is congested. All the proposed or conventional solutions and processes don't take Radio Frequency (RF) conditions and physical parameters of the target cells into consideration while load balancing, which is a massive flaw in the current and existing solutions.

Therefore, there is a need of improvement in the conventional solutions for identification and optimization of unbalanced cells to improve network quality and coverage in congested areas to mitigate or eliminate the congestion and hence achieve higher overall user experience. Also, there exists a need for an improvement in the existing systems and methods to deliver better optimization and decongestion results.

SUMMARY

This section is provided to introduce certain objects and aspects of the present disclosure 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 disclosure is to provide a novel method for identification and optimization of unbalanced cells to improve network quality and coverage in congested areas to mitigate or eliminate the congestion and hence achieve higher overall user experience. Another object of the present disclosure is to provide an improved system and method that take RF conditions and physical parameters of the target cells into consideration when load balancing between the cells, to deliver better optimization and decongestion results. Yet another object of the present disclosure is to provide a novel method that effectively utilizes the available spectrum by load balancing between highly utilized cell and its corresponding lightly utilized neighbor cell. Yet another object of the present disclosure is to provide a novel method that effectively and uniformly distributes traffic among all the cells of a cellular network which is achieved by effectively considering the neighbor's performance and physical parameters. Yet another object of the present disclosure is to provide a novel method that provides better capacity management and enhanced user experience in terms of better upload/download speed, less call muting etc. Yet another object of the present disclosure is to provide a novel mechanism that obviates the need of a manual intervention in steps like, identifying the cells to be optimized, changing the one or more cell parameters for one or more cells and checking the performance metrics, before and after optimization of the configuration parameters of the candidate cells. Yet another object of the present disclosure is to provide an efficient and effective novel mechanism of automatic self- evaluation of the network performance to keep the network performance optimum and uncompromised. Yet another object of the present disclosure is to provide features and ability to handle high volume calls, concurrently in a wireless ecosystem.

In order to achieve the aforementioned and other objectives, a first aspect of the present disclosure may relate to a method for automatic load balancing of a serving cell in a cellular network comprising a plurality of serving cells. The method begins at receiving, from each of the plurality of serving cells, at least one of a network parameter, at least one user device parameter, at least one unbalanced parameter and at least one load balancing parameter, wherein the at least one user device parameter is associated with at least one user device served by the plurality of serving cells. Further, a source unbalanced candidate cell experiencing the unbalanced load is identified from the plurality of serving cells, the identification being based on the at least one unbalanced parameter. Next, at least one source balanced candidate cell experiencing a balanced load is identified, from the plurality of serving cells, the identification being based on the at least one load balancing parameter. Subsequently, the at least one network parameter and the at least one user device parameter are analysed for the at least one candidate cell to determine at least one balancing category. Each of the at least one balancing category is associated with at least one identification criterion and at least one balancing action. The at least one identification criterion is based on at least one successful handover attempt rate, an IP throughput, a PRB utilization and minimum inter-site distance (ISD). Further, the determined at least one balancing category are compared for the best available source balanced candidate cell. Subsequently, the identified source unbalanced candidate cell is balanced by performing said at least one balancing action for each of the determined at least one balancing category. Next, a target balanced cell is selected, from the identified at least one source balanced candidate cell, based on the determined at least one balancing category. Lastly, the identified at least one source unbalanced candidate cell is offloaded on to the target balanced cell.

Yet another aspect of the present disclosure may relate to a system for automatic load balancing of a serving cell in a cellular network comprising a plurality of serving cell. The system comprises of a transceiver unit and a processor connected to the transceiver unit. Said transceiver unit is configured to receive, from each of the plurality of serving cells, at least one of a network parameters, at least one user device parameter, at least one unbalanced parameter and at least one load balancing parameter, wherein the at least one user device parameter is associated with at least one user device served by plurality of serving cells. The processor is configured to identify a source unbalanced candidate cell experiencing unbalanced load, from the plurality of serving cells, the identification being based on the at least one unbalanced parameter. The processor is also configured to identify a source balanced candidate cell experiencing balanced load, from the plurality of serving cells, the identification being based on the at least one load balancing parameter. Further, the processor is configured to analyze the at least one network parameter and the at least one user device parameter for the at least one candidate cell. Furthermore, the processor is configured to determine at least one balancing category based on said analysis of the at least one network parameter and the at least one user device parameter. Each of the at least one balancing category is associated with at least one identification criterion and at least one balancing action. The at least one balancing criterion is based on at least one successful handover attempt rate, an IP throughput, a PRB utilization and minimum inter-site distance (ISD). The processor is also configured to compare among the determined at least one balancing category for the best available source balanced candidate cell. The processor is also configured to balance the identified source unbalanced cell by performing said at least one balancing action for each of the determined at least one balancing category. The processor is also configured to select, from the identified at least one source balanced candidate cell, a target balanced cells based on the determined at least one balancing category. And lastly, the processor is also configured to offload the identified at least one source unbalanced candidate cell to the target balanced cell.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary instances of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components or circuitry commonly used to implement such components.

The present disclosure may be understood when read in conjunction with the following drawings:

Fig. 1 illustrates an exemplary block diagram of a network in which systems and/or methods described herein may be implemented, in accordance with exemplary embodiments of the present disclosure.

Fig. 2 illustrates an exemplary block diagram of the network entity depicted in Fig. 1, in accordance with exemplary embodiments of the present disclosure.

Fig. 3 illustrates an exemplary flow diagram of a method for load balancing in a cellular network, in accordance with exemplary embodiments of the present disclosure. Fig. 4 illustrates an exemplary Neighbor Relation Table (NRT) maintained by a network entity, in accordance with exemplary embodiments of the present disclosure.

Fig. 5 illustrates an aspect of the NRT table in accordance with exemplary embodiments of the present disclosure.

Fig. 6 illustrates yet another aspect of the NRT table maintained by the network entity, in accordance with exemplary embodiments of the present disclosure.

Fig. 7 - Fig. 12 illustrates an exemplary scenario of load balancing within three bands (along with four carriers), in accordance with exemplary embodiments of the present disclosure.

Fig. 13 illustrates the results of a case study involving the method of load balancing in a cellular network, in accordance with exemplary embodiments of the present disclosure.

Fig. 14 illustrates pre-post analysis of key point indicators (KPIs) of the cell after load balancing, in accordance with exemplary embodiments of the present disclosure.

The foregoing shall be more apparent from the more detailed description of the invention below.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of instances of the present invention. It will be apparent, however, that instances of the present invention 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 any of the problems discussed above or might address only one of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein. Example instances of the present invention are described below, as illustrated in various drawings in which like reference numerals refer to the same parts throughout the different drawings. The present disclosure relates to a system and a method for automatic load balancing of a serving cell in a cellular network comprising a plurality of serving cells. Thereby, the present invention provides a system and method to optimally address the problems existing in prior arts, by automatically identifying and optimizing unbalanced cells to improve network quality and coverage in congested areas, thereby mitigating problem of cell congestion and facilitating high-quality user experience. Per present invention, network parameters, user device parameters, and load balancing parameters, for example, but not limited to, Radio-Frequency (RF) conditions and physical parameters of target cells are considered for performing load balancing between an unbalanced (loaded) source cell and to one or more balanced (target) source cells, to deliver better optimization and decongestion results. The present invention helps network operators to provide improved network facilities, which result in better network perception among users.

Fig. 1 illustrates an exemplary block diagram of a cellular network [100] in which systems and/or methods described herein may be implemented. As shown, the network [100] may include a plurality of serving cells [104, 106, 108, 110, 112, 114, 128], network nodes [102, 116, 118, 120, 122, 124, 130] serving each of the plurality of serving cells [104, 106, 108, 110, 112, 114, 128], and a network entity [126] A limited number of cells, network nodes, and a single network entity [126] have been illustrated in Fig. 1 for simplicity. In practice, there may be any number of cells and base stations, and/or more than one network entity [126] Also, in some instances, a component in network [100] may perform one or more functions described as being performed by another component or group of components in network [100] In the network [100], there may be one or more user equipment (UE) served by any of the network nodes [102, 116,118, 120, 122, 124, 130] Typically, the one or more UEs may include one or more devices capable of sending/receiving voice and/or data to/from base stations. UE may include, for example, a radio-telephone, a personal communications system (PCS) terminal (e.g., that may combine a cellular radio-telephone with data processing and data communications capabilities), a personal digital assistant (PDA) (e.g., that can include a radio-telephone, a pager, Internet/intranet access, etc.), a laptop computer, etc. In one instance, each of the network nodes [102, 116,118, 120, 122, 124, 130] may refer to, but not limited to, a base station, eNodeB, Mobile Switching Centre (MSC), and/or other core network element in the network [100] Each of the network nodes [102, 116,118, 120, 122, 124, 130] may include one or more devices that receive voice and/or data from a device (e.g., network entity [126]) and transmit that voice and/or data to UEs via an air interface. Each of the network nodes [102, 116,118, 120, 122, 124, 130] may also receive voice and/or data from UEs over an air interface and transmit that voice and/or data to other devices of the network (e.g., network entity [126]) or to other UEs. The network entity [126] may include one or more devices that control and manage network nodes [102, 116,118, 120, 122, 124, 130] In one instance, the network entity [126] may also perform data processing to manage the utilization of radio network services. The network entity [126] may support processes such as maintaining network inventory, provisioning services, configuring network components, and/or managing faults. In one instance, the network entity [126] may provide services for network [100], such as order processing, accounting, billing and cost management, network inventory, service provision, network design, network discovery and reconciliation, trouble and fault management, capacity management, network management, field service management, etc. In one instance, the network entity [126] may interconnect with the network nodes [102, 116,118, 120, 122, 124, 130] via wired or wireless connections. Although Fig. 1 shows exemplary components of network [100], in other instances, network [100] may contain fewer, different, differently arranged, or additional components than depicted in Fig. 1.

Fig. 2 illustrates an exemplary block diagram of a network entity [126] that may correspond to the network nodes [102, 116,118, 120, 122, 124, 130] depicted in Fig. 1. As shown in Fig. 2, the network node 200 may comprise of one or more antenna [210], one or more transceiver (TX/RX) [220], a processing system [230], and an interface (l/F) [240] In one instance, the one or more antenna [210] may include one or more directional and/or omni-directional antennas. The one or more transceiver [220] may be associated with the one or more antenna [210] and may include transceiver circuitry for transmitting and/or receiving symbol sequences in a network, such as network [100], via the one or more antenna [210] Said transceiver [220] may be configured to receive, from each of the plurality of serving cells of the network [100], at least one of a network parameters, at least one user device parameter, at least one unbalanced parameter and at least one load balancing parameter, wherein the at least one user device parameter is associated with at least one user device served by the plurality of serving cells.

The processing system [230] may control an operation of the network node [200] The processing system [230] may also process information received via the one or more transceiver [220] and/or the interface [240] As shown in Fig. 2, the processing system [230] may include a processor [232] and a memory [234] The processor [232] may be configured to identify a source unbalanced candidate cell experiencing unbalanced load, from the plurality of serving cells, the identification being based on the at least one unbalanced parameter. The processor [232] may also be configured to identify a source balanced candidate cell experiencing balanced load, from the plurality of serving cells, the identification being based on the at least one load balancing parameter. Further, the processor [232] may be configured to analyze the at least one network parameter and the at least one user device parameter for the at least one candidate cell. Furthermore, the processor [232] may be configured to determine at least one balancing category based on said analysis of the at least one network parameter and the at least one user device parameter. Each of the at least one balancing category is associated with at least one identification criterion and at least one balancing action. The at least one balancing criterion is based on at least one successful handover attempt rate, an IP throughput, a PRB utilization and minimum inter-site distance (ISD).

The processor [232] may be configured to compare among the determined at least one balancing category for the best available source balanced candidate cell. The processor [232] may be configured to balance the identified source unbalanced cell by performing said at least one balancing action for each of the determined at least one balancing category. The processor [232] may further be configured to select, from the identified at least one source balanced candidate cell, a target balanced cells based on the determined at least one balancing category. And lastly, processor [232] may also be configured to offload the identified at least one source unbalanced candidate cell to the target balanced cell. In one instance, the processor [232] may include one or more processors, microprocessors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and the like. The processor [232] may process information received via the one or more transceiver [220] and/or interface [240] In addition, the processor [232] may transmit control messages and/or data messages and may cause those control messages and/or data messages to be transmitted via transceivers [220] and/or interface [240] The processor [232] may also process control messages and/or data messages received from the one or more transceiver [220] and/or interface [240] In one instance, the memory [234] may include a random-access memory (RAM), a read-only memory (ROM), and/or another type of memory to store data and instructions that may be used by the processor [232]

In one instance, the interface [240] may include one or more circuitries, such as line cards that allow the network node to transmit data to and receive data from another network nodes or a network entity [126] In one example, the interface [240] may include an X2 interface that enables the network node to exchange information related to performing a load balancing operation.

In one instance, the network entity [126] may perform certain operations in response to the processor [232] executing software instructions of an application contained in a computer- readable medium, such as memory [234] A computer-readable medium may be defined as a physical or logical memory device. A logical memory device may include memory space within a single physical memory device or spread across multiple physical memory devices. The software instructions may be read into memory [234] from another computer-readable medium or from another device via antennas [210] and transceivers [220] The software instructions contained in memory [234] may cause processing unit [232] to perform processes described herein. Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to implement processes described herein. Thus, instances described herein are not limited to any specific combination of hardware circuitry and software.

Although Fig. 2 shows exemplary components of the network node, in other instances, the network node may contain fewer, different, differently arranged, or additional components than depicted in Fig. 2. Alternatively, or additionally, one or more components of the network node may perform one or more other tasks described as being performed by one or more other components of the network node.

Referring to Fig. 3, it illustrates an exemplary flow diagram of a method for load balancing in a cellular network [100] The method begins at step 301, with receiving, from each of the plurality of serving cells, at least one of a network parameter, at least one user device parameter, at least one unbalanced parameter and at least one load balancing parameter, wherein the at least one user device parameter is associated with at least one user device served by the plurality of serving cells.

The at least one network parameter may include, but not limited to, at least one of a cell ID of the at least one source unbalanced candidate cell, a cell ID of the at least one source balanced candidate cell, a cell band of the at least one source unbalanced candidate cell, a cell band of the at least one source balanced candidate cell, a successful handover count from the at least one source unbalanced candidate cell to the at least one source balanced candidate cell, a total successful handover count of the at least one source unbalanced candidate cell, a successful handover attempt rate of the at least one source unbalanced candidate cell, a ranking of the at least one source balanced candidate cell, a KPI value of the at least one source unbalanced candidate cell and a KPI value of the at least one source balanced candidate cell.

The at least one user device parameter may include, but not limited to, one of an International Mobile Subscriber Identity (IMSI), an outage count, a user density, a user IP throughput, a packet loss at a user device and a percentage of ROHC-decompression failures. The at least one load balancing parameter may include, but not limited to, a physical resource block utilization value (PRB) and a number of RRC connected users. The at least one unbalanced parameter may include, but not limited to, a physical resource block utilization value (PRB) and a number of RRC connected users. In an instance of the present invention, the unbalanced parameter may be same as the load balancing parameter. Further, at step 302, a source unbalanced candidate cell experiencing the unbalanced load is identified from the plurality of serving cells, the identification being based on the at least one unbalanced parameter. For example, the source unbalance candidate cell is the serving cell with a high load, a high downlink physical resource block utilisation and a high number of RRC connected users. The at least one source unbalanced candidate cell may be identified based at least on, for instance, a comparison of the physical resource block utilization (PRB) with a pre-defined threshold.

In an instance of the invention, the network entity [126] may monitor PRB of each of the serving cell in the network [100], and then the network entity [126] compares the PRBs of the serving cells with a preset PRB threshold. The cells with PRB greater than the said threshold are selected as highly utilized cells. Among the highly utilized cells, the cell with the highest PRB is selected as a source cell for performing load balancing. For example, the PRB threshold may be 70% of the downlink PRB Utilization, and the cell [128] has PRB utilisation of 85%, highest among other cells, then cell [128] may be selected as the source cell for load balancing.

Next, at step 303, at least one source balanced candidate cell experiencing balanced load is identified, from the plurality of serving cells, the identification being based on the at least one load balancing parameter. For instance, the at least one source balanced candidate cell may be identified based on at least one of: (a) a comparison of the physical resource block utilization (PRB) with a pre-defined threshold PRB utilization, (b) a comparison of the IP throughput with a predefined threshold IP throughput, and (c) a comparison of inter-site distance between the at least one source unbalanced candidate cell and the at least one source balanced candidate cell. In an instance of the invention, the identified at least one source balanced candidate cell may be a neighbour cell of the identified source unbalanced candidate cell. The step 403 may further comprise assigning a rank to the at least one source balanced candidate cell.

In an instance of the present invention, one or more neighboring cells [104, 106, 108, 110, 112, 114] located in the vicinity of the source unbalanced cell [128] are identified by the network entity [126] The vicinity of the source cell [128] may correspond to location or position adjacent to the source cell [128], or the vicinity of the source cell [128] may also correspond to a location or position which may be within a predetermined distance from the source cell [128] Thereafter, the network entity [126] determines the total number of handovers of one or more user equipment (UE) successfully completed by the source unbalanced cell [128], and the number of handovers of the UEs to each of the neighboring cells [104, 106, 108, 110, 112, 114] completed successfully by the source unbalanced cell [128] Based on the determined total number of handovers and number of handovers of the UEs to each of the neighboring cells, the network entity [126] may determine a successful handover attempt rate (SHAR) for the source unbalanced cell [128] as follows:

Successful Handover Attempt Rate (%) = (Source to target successful handover count/ Source total successful handover count)

In an exemplary instance of the present invention, depending on the determined SHAR, a Neighbor Relation Table (NRT), as depicted in Fig. 4, may be maintained by the network entity [126] The SHAR may be sorted with neighboring cell IDs (N1 ... N256) in descending order along with radio access network Key Point Indicators (KPI)s. Based on the determined SHAR, a rank may be assigned to each of the neighboring cells [104, 106, 108, 110, 112, 114], wherein preferably the neighboring cells are ranked from top to bottom, as also shown in Fig. 4.

Subsequently, at step 304, the at least one network parameter and the at least one user device parameter are analysed for the at least one candidate cell. Next, at step 305, at least one balancing category is determined based on said analysis of the at least one network parameter and the at least one user device parameter. Each of the at least one balancing category is associated with at least one identification criterion and at least one balancing action. The at least one identification criterion is based on at least one successful handover attempt rate, an IP throughput, a PRB utilization and minimum inter-site distance (ISD).

Further, at step 306, the determined at least one balancing category are compared for the best available source balanced candidate cell. Subsequently, at step 307, the identified source unbalanced candidate cell is balanced by performing said at least one balancing action for each of the determined at least one balancing category. Next, at step 308, a target balanced cell is selected, from the identified at least one source balanced candidate cell, based on the determined at least one balancing category. Lastly, at step 309, the identified at least one source unbalanced candidate cell is offloaded on to the target balanced cell.

For instance, the network entity [126] selects a source unbalanced candidate cell and/or the source balanced candidate cell from the one or more neighboring cells [104, 106, 108, 110, 112, 114] based on a cell-identification criteria. The cell-identification criteria may include, for example, Downlink PRB or throughput. As also shown in the table of Fig. 4, the neighboring cells having a rank within a preset range are selected, and further Fig. 5 shows the selected neighboring cells. Say, neighboring cells having rank ranging 1-5 are selected for processing according to the cell identification criteria. In the selected neighboring cells shown in Fig. 5, one or more neighboring cells having the DL-PRB utilization and throughput less than a DL-PRB utilization threshold and a throughput threshold are selected. In one preferred instance, the throughput threshold is 2 Mbps. For example, if the source cell [128] and the one or more neighboring cells [104, 106, 108, 110, 112, 114] are intra band, the DL PRB utilization less than 50% is used as the cell-identification criteria.

In one other instance, the cell-identification criteria includes, but not limited to, Inter-Site Distance (ISD), wherein a neighboring cell amongst the one or more neighboring cells [104, 106, 108, 110, 112, 114] having a minimum ISD from the source unbalanced candidate cell [128] is selected as the at least one source balanced candidate cell. The at least one neighboring cell amongst the one or more other neighboring cells [104, 106, 108, 110, 112, 114], are also selected as source balanced candidate cell. As shown in Fig. 6, a neighboring cell with cell ID N2 is selected as the target balanced cell from the neighboring cells.

Subsequently, the network entity [126] determines whether physical parameters of the first target cell exceeds a preset threshold due to load balancing which includes the transfer of one or more UEs from the source cell [128] to the first target cell. For example, the network entity [126] may determine whether the of the cell with the cell ID N2 exceeds the preset threshold due to the load balancing. In an event, the parameters do not exceed the preset threshold, the first target cell, which is the cell with cell ID N2, is used for the load balancing. In an event, the parameters exceed the preset threshold, then another/ second target cell N1 is used for the load balancing which includes the transfer of the one or more UEs from the source cell [128] to the second target cell Nl.

The method may further comprise of an additional step of re-selecting the target balanced cell in an event of degradation of the at least one network parameter, wherein the degradation of the network parameter comprises a comparison of the network parameter with a pre-defined threshold network parameter. The method, as depicted in Fig. 3 may be performed at a network level or a user device level.

Exemplary Scenario of load balancing in network with 3 bands, i.e., 4 carriers

The method and system of the present invention is described herein with respect to an exemplary scenario of 3 bands (4 carriers) as mentioned in below Table 1.

Table 1

The network entity [126] may try to offload a congested cell to lightly loaded cells in a same sector (Intra cells) by soft parameter changes. If all the cells in a given sector are loaded, the network entity [126] will search for the nearest lightly loaded cell where the congested cell can offload its data. The Load optimization may be prioritized based on the soft parameter changes (multi-carrier parameter changes) followed by the physical parameter changes. The details of each scenario are described below and the steps of load balancing are illustrated in Fig. 7 - Fig. 12, for the exemplary scenario of load balancing within 3 bands (4 carriers).

SCENARIO 1: (LOAD BALANCING FOR CARRIERS OF 2300 MHZ BAND)

In Scenario 1, referring to Fig. 7, at step 701 it is identified by the invention whether the DL PRB Utilization of the source cell is > 70%. If yes, the method proceeds to step 702, else the method proceeds to step 714. At 702, it is detected if the source cell is a 2300 MHz Carrier 1. If the source cell is 2300 MHz Carrier 1, the method proceeds to step A, else the method proceeds to step 703. At step 703, it determined if the source cell band is 2300 MHz Carrier 2. If yes, the invention determines at step 706 if the DL PRB Utilization of the 2300 MHz Carrier 2 is < 70% and the loading difference is >20% with respect to the 2300 MHz Carrier 2 in Co-located cell. In such a scenario, the following steps may be performed by the network entity [126]:

a) If 2300 MHz C2 carrier is not integrated, a work order is created to respective stakeholders to prioritize an integration of 2300 MHz C2.

b) If 2300 MHz C2 carrier is already integrated, then the cell reselection priority is changed from 7 to 6 for 2300 MHz Cl at step 710, to ensure that 2300 MHz C2 is selected as the target cell.

Further, referring to Fig. 8, at step 703, if the invention determines that the source cell band is 2300 MHz carrier 1, it proceeds to step A. At step 801, it determined if the source cell band is colocated on 2300 MHz carrier 1 on air. If yes, the resolution is provided at step 806 to change Reselection Priority for 2300 MHz -C2 from 7 to 6. If no, at step 802, it determines if the source cell band is 2300 MHz Carrier, and if the DL PRB Utilization of the 2300 MHz Carrier 1 is < 50% and the IP throughput is >2 Mbps. If yes, resolution is provided at step 807 to Change Reselection Priority for 2300 MHz -C2 from 7 to 6. However, if no, it determines that the collocated 1800 MHz and 850 MHz is available. If not available, then resolution of step 808 is followed, wherein a work order is created for 1800 MHz/850 MHz integration. If available, the network entity [126] may check at step 804 whether the DL PRB Utilization < 50% and IP throughput > 2 Mbps of 1800 MHz/850 MHz. If no, the method executes step D. If yes, then resolution 2 is followed at step 805 wherein Tilt harmonization is executed by the network entity [126], which is executed when all band antenna height is with ±2 meter. For tilt harmonization, the network entity [126] may check the following conditions at step 810 and configure accordingly.

Condition 1: if 1800 MHz lightly loaded: E-tilt 2300= X and 1800 =Y>X+2°, Change E-tilt from Y to Y= X+2°

Condition 2: if 850 MHz lightly loaded: E-tilt 2300= X and 850 =Z>X+4°, Change E-tilt from Z to Z= X+4°

If tilts are not harmonized, Resolution 3 is followed in step 809, wherein the network entity [126] may change/audit multi-carrier settings, wherein the network entity [126] is configured to:

1. Increase A2 threshold by 5dB (2300 MHz traffic being pushed to 1800 MHz/850MHz), or

2. Increase A1 Threshold by 5dB (2300 MHz traffic being pushed to 1800 MHz/850MHz), or

3. Decrease A3 Threshold by 5dB (2300 MHz traffic being pushed to 850 MHz).

SCENARIO 2: (LOAD BALANCING SOLUTIONS WITHIN CO-LOCATED CELLS)

Scenario 2 is further subdivided into 3 categories (a, b and c) for resolutions as mentioned below.

a) 2300 MHz Cells Congested:

If it is determined at step 703 that source cell band is not 2300 MHz Carrier 2, the network entity may check availability of 1800 MHz and the availability of 850 MHz band at step 707 within co-located cells.

If at step 707 it is determined that the collocated 1800 MHz and 850 MHz is available. If not available, then Resolution 1 is followed, wherein a work order is created for 1800 MHz/850 MHz integration at step 711. If available, the network entity [126] may check at step 708 whether the DL PRB Utilization < 50% and IP throughput > 2 Mbps of 1800 MHz/850 MHz.

If yes, then Resolution 2 is followed at step 709 wherein Tilt harmonization is executed by the network entity [126], which is executed when all band antenna height is with ±2 meter. For tilt harmonization, the network entity [126] may check the following conditions at step 713 and configure accordingly.

If tilts are not harmonized, Resolution 3 is followed in step 712, wherein the network entity [126] may change/audit multi-carrier settings, wherein the network entity [126] is configured to:

3. Decrease A3 Threshold by 5dB (2300 MHz traffic being pushed to 850 MHz). b) 1800 MHz Cells Congested:

Referring now to Fig. 9, when it is determined at step 704 that the source cell band isl800 MHz, the network entity [126] may check availability of 2300 MHz C2 within co-located cells at step 901. If not available, the network entity [126] may perform Resolution 1 at step 904, wherein a work order is created for 2300 & 850 MHz integration.

If available, the network entity [126] may check at step 902 whether DL PRB Utilization < 50% and IP throughput > 2 for 2300 MHz/850 MHz, and may perform Resolution 2, at step 903 wherein Tilt harmonization is checked. Tilt harmonization is performed only when all band antenna height is with ±2 meter. In tilt harmonization, the following conditions are checked at step 906 and performed, Condition 1: If 2300 MHz is less utilized: E-tilt 1800= X and 2300 =Y>X-2°, Change E-tilt from Y to Y= X-2° if X>3 or Y= X-l° if X=3 or Y=X if X<3

Condition 2 : If 850 MHz is less utilized: E-tilt 1800= X and 850 =Z>X+2°, Change E-tilt from Z to Z= X+2°

If tilts are harmonized at step 903, the Resolution 3 is performed at step 905, wherein the network entity may change or audit multi-carrier settings, in which:

1. the network entity [126] may decrease A5 threshold 2 by 3dB (1800 MHz traffic being

pushed to 2300 MHz Cl and C2) - If 2300 MHz is less utilized, and

2. the network entity [126] may increase A5 threshold 1 5dB (1800 MHz traffic being pushed to 850MHz)- If 850 MHz is less utilized. c) 850 MHz Cells Congested:

Referring to Fig. 10, the network entity [126] may check, at step 1001, the availability of 2300 MHz & 1800 MHz within co-located cells. If not available, then Resolution 1 is performed at step 1004, wherein the network entity [126] may create work order for 2300 & 1800 MHz integration, and wherein, if available, the network entity [126] may check at step 1002 whether the PRB Utilization < 50% and the IP throughput > 2 Mbps for 2300 MHz / 1800 MHz.

If the above conditions are satisfied, Resolution 2 is performed at step 1003, wherein the network entity [126] may check if tilts are harmonized. Tilt harmonization only in instances when all band antenna height is with ±2 meter. If the tilts are not harmonized, harmonization is performed at step 1006 wherien the network entity may check:

1. Condition 1 wherein if 2300 MHz not utilized: E-tilt 850= X and 2300 =Y>X-4°, Change E-tilt from Y to Y= X-4° if X>5 or Y= 2 if X<=5

2. Condition 2 if 1800 MHz not utilized: E-tilt 850= X and 1800 =Z>X-2°, Change E-tilt from Z to Z= X-2° if X>3 or Z=2 if X=<3

If tilts are harmonized, Resolution 3 is performed at step 1005, wherein the network entity [126] may change or audit multi-carrier settings, wherein the network entity [126] is configured to:

1. Decrease A5 threshold 2 3dB (850 MHz traffic being pushed to 2300 MHz Cl) - If 2300 MHz is less utilized. 2. Increase A5 Threshold 1 by 5dB (850 MHz traffic being pushed to 1800 MHz) -If 1800 MHz is less utilized.

SCENARIO 3: (LOAD BALANCI NG FOR INTER SECTOR NEIGHBOR CELLS OF THE SAME BAND)

Referring to Fig. 11, if the outcome of any of the above steps 708, 804, 902 or 1002 is step D, the invention then fetches NRT table for the respective source cell. It then determines whether respective bands' PRB Utilization < 50% and I P throughput >2 Mbps. If no, the method proceeds to step E. If yes, the method calculates the successful handover attempt rate for each Nbr as below successful Handover Attempt Rate (%)=Source to target successful handover (count) /source total successful handover (count)

At step 1104, the network entity [126] then sorts the "Successful Handover Attempt Rate " and finds the top 5 Nbr having highest successful handover attempt rate (%).

At step 1105, it determines whether more than one potential Nbr is identified. If yes, then it selects the one with minimal ISD for traffic offloading at step 1110. However, in the event of no, it proceeds to step 1106 to determine if Identified Nbr cell is same band as source cell. The network entity [126] may check for any cell with the same band of source cell in Top 5 best neighbor cell list with DL PRB Utilization < 50% and IP Throughput > 2 Mbps. In Resolution 1, at step 1107, the network entity [126] may change Cell Individual Offset by +2 for source cell and -2 for neighbor cell, if Ping Pong is less than 1000. The network entity [126] may monitor the next 48 hours, if traffic is not balanced, and may change further by 2db and so on till 6 dB.

SCENARIO 4: (LOAD BALANCI NG SOLUTIONS FOR INTER SECTOR NEIGH BOR CELLS OF ANOTH ER

Referring to Fig. 11, in Resolution 1, the network entity may identify a band of best neighbor cell and, at step 1111, down tilt source cell by 2 degrees and target neighbor cell by 2 degrees. The network entity [126] may monitor the next 48 hours, and if traffic is not balanced, roll back the changes. SCENARIO 5: INTEGRATION OF EXISTING PLANNED SITES

TO

SHARE TRAFFIC FOR CONGESTION RELIEF)

Referring to Figure 12, if all identified neighbors are congested, the network entity [126] may check for 4^th sector availability on the source cell and target cells at step 1201. If not available, the network entity at step 1201, may create work order (WO) for prioritizing the integration of 4^th Sector. If available, the network entity [126] at step 1202 may check for already planned (Macro or Micro) within the range of top 5 Neighbors. Further, the network entity [126] at step 1204 may create a work order to integrate existing planned sites (Macro + Micro). If there are no existing planned sites, the network entity [126] at step 1205 may propose ODSC/I DSC/I nfill sites based in that area.

Referring to Fig. 13, the results of a case study involving the method of load balancing in a cellular network in accordance with an instance of the present invention, is illustrated. The method and system of the present invention has been implemented in one cluster with field results as below. The following steps were carried out:

• BBH (Bouncing Busy Hour) data for the cluster circle were taken, and the congested cells were identified;

• few congested cells were identified using the method of the present invention by utilizing data from an in-house tool, and the identification of target cells was optimized for implementation using the method of the present invention; and

• after implementation, it was found that the highly utilized cells were offloaded/decongested to the neighbouring cells and traffic was shared among the neighbouring cells.

As shown in Fig. 14, after implementing the recommendations in accordance with the method of the present invention, uniform distribution of traffic was found in both cells. Further, downlink PRB utilization of highly utilized cells reduced from 92% to 73 % and the downlink PRB utilization of nearest lightly loaded cell increased from 46% to 60 %. Further, data traffic and other important KPIs have either improved or remained the same in the pre-post analysis of above-mentioned cells, as shown in Fig. 14.

The units, interfaces, modules, and/or components depicted in the figures and described herein may be present in the form of a hardware, a software and a combination thereof. Connection/s shown between these units/components/modules/interfaces in the exemplary system architecture [100A] may interact with each other through various wired links, wireless links, logical links and/or physical links. Further, the units/components/modules/interfaces may be connected in other possible ways.

While considerable emphasis has been placed herein on the disclosed instances, it will be appreciated that many instances can be made and that many changes can be made to the instances without departing from the principles of the present invention. These and other changes in the instances of the present invention will be apparent to those skilled in the art, whereby it is to be understood that the foregoing descriptive matter to be implemented is illustrative and non limiting.

Claims

We Claim

1. A method for automatic load balancing of a serving cell in a cellular network comprising a plurality of serving cells, the method comprising: receiving, from each of the plurality of serving cells, at least one of a network parameter, at least one user device parameter, at least one unbalanced parameter and at least one load balancing parameter, wherein the at least one user device parameter is associated with at least one user device served by the plurality of serving cells; identifying a source unbalanced candidate cell experiencing unbalanced load, from the plurality of serving cells, the identification being based on the at least one unbalanced parameter; identifying at least one source balanced candidate cell experiencing balanced load, from the plurality of serving cells, the identification being based on the at least one load balancing parameter; analyzing the at least one network parameter and the at least one user device parameter for the at least one candidate cell; determining at least one balancing category based on said analysis of the at least one network parameter and the at least one user device parameter, wherein each of the at least one balancing category is associated with at least one identification criterion and at least one balancing action, and the at least one identification criterion is based on at least one successful handover attempt rate, an IP throughput, a PRB utilization and minimum inter-site distance (ISD); comparing among the determined at least one balancing category for the best available source balanced candidate cell; balancing the identified source unbalanced candidate cell by performing said at least one balancing action for each of the determined at least one balancing category; selecting, from the identified at least one source balanced candidate cell, a target balanced cell based on the determined at least one balancing category; and offloading the identified at least one source unbalanced candidate cell to the target balanced cell.

2. The method as claimed in claim 1, further comprising re-selecting the target balanced cell in an event of degradation of the at least one network parameter.

3. The method as claimed in claim 1, wherein the method is performed at a network level or a user device level.

4. The method as claimed in claim 1, wherein the source unbalance candidate cell represents a high loaded cell, a high downlink physical resource block utilisation and a high number of RRC connected users.

5. The method as claimed in claim 1, wherein the at least one load balancing parameter is a physical resource block utilization (PRB), and a number of RRC connected users.

6. The method as claimed in claim 1, wherein the at least one network parameter is at least one of a cell ID of the at least one source unbalanced candidate cell, a cell ID of the at least one source balanced candidate cell, a cell band of the at least one source unbalanced candidate cell, a cell band of the at least one source balanced candidate cell, a successful handover count from of the at least one source unbalanced candidate cell to the at least one source balanced candidate cell, a total successful handover count of the at least one source unbalanced candidate cell, a successful handover attempt rate of the at least one source unbalanced candidate cell, a ranking of the at least one source balanced candidate cell, a KPI value of the at least one source unbalanced candidate cell and a KPI value of the at least one source balanced candidate cell.

7. The method as claimed in claim 5, further comprising assigning a rank to the at least one source balanced candidate cell.

8. The method as claimed in claim 1, wherein the at least one user device parameter is at least one of an International mobile subscriber identity (IMSI), an outage count, a user density, a user IP throughput, a packet loss at a user device and a percentage of ROHC-decompression failures.

9. The method as claimed in claim 1, wherein the at least one source unbalanced candidate cell is identified based at least on a comparison of the physical resource block utilization (PRB) with a pre-defined threshold.

10. The method as claimed in claim 1, wherein the at least one source balanced candidate cell is identified based on at least on one of a comparison of the physical resource block utilization (PRB) with a pre-defined threshold PRB utilization, a comparison of the IP throughput with a pre-defined threshold IP throughput, and a comparison of inter-site distance between the at least one source unbalanced candidate cell and the at least one source balanced candidate cell.

11. The method as claimed in claim 1, wherein the cellular network comprises LTE/GSM/5G/WCDMA.

12. The method as claimed in claim 5, wherein the band comprises at least one of a 2300C1 MHz, a 2300C2 MHz, a 1800C1 MHz and a 850C1 MHz.

13. The method as claimed in claim 5, wherein the band may be an intra band or an inter band.

14. The method as claimed in claim 1, wherein the degradation of the network parameter comprises a comparison of the network parameter with a pre-defined threshold network parameter.

15. The method as claimed in claim 1, wherein the identified at least one source balanced candidate cell is a neighbour cell of the identified source unbalanced candidate cell.

16. A system for automatic load balancing of a serving cell in a cellular network comprising a plurality of serving cell, the system comprising: a transceiver unit [220] configured to receive, from each of the plurality of serving cells, at least one of a network parameters, at least one user device parameter, at least one unbalanced parameter and at least one load balancing parameter, wherein the at least one user device parameter is associated with at least one user device served by plurality of serving cells; and a processor [232] connected to the transceiver unit [220], said processor [232] configured to: identify a source unbalanced candidate cell experiencing unbalanced load, from the plurality of serving cells, the identification being based on the at least one unbalanced parameter; identify a source balanced candidate cell experiencing balanced load, from the plurality of serving cells, the identification being based on the at least one load balancing parameter; analyze the at least one network parameter and the at least one user device parameter for the at least one candidate cell; determine at least one balancing category based on said analysis of the at least one network parameter and the at least one user device parameter, wherein each of the at least one balancing category is associated with at least one identification criterion and at least one balancing action, and the at least one balancing criterion is based on at least one successful handover attempt rate, an IP throughput, a PRB utilization and minimum inter-site distance (ISD); compare among the determined at least one balancing category for the best available source balanced candidate cell; balance the identified source unbalanced cell by performing said at least one balancing action for each of the determined at least one balancing category; select, from the identified at least one source balanced candidate cell, a target balanced cells based on the determined at least one balancing category; and offload the identified at least one source unbalanced candidate cell to the target balanced cell.

17. The system as claimed in claim 14, wherein the system is implemented at a network level or at a user device level.