FI129036B - Automatic neighbor list optimization in communication networks - Google Patents

Abstract

A computer implemented method for neighbor list optimization in a communication network. The method comprises identifying (201) a first cell where neighbor list optimization is needed; confirming (202) that there exists free space in a neighbor list of the first cell; choosing (207) one or more new neighbors that are not listed in a black list of the first cell; and adding (208) the new neighbors to the neighbor list of the first cell.

Description

AUTOMATIC NEIGHBOR LIST OPTIMIZATION IN COMMUNICATION NETWORKS TECHNICAL FIELD

[0001] The present application generally relates to neighbor lists and optimization thereof in communication networks.

BACKGROUND

[0002] This section illustrates useful background information without admission of any technique described herein representative of the state of the art.

[0003] The network parameters that need to be set for cells of communication networks include neighbor lists. A neighbor list of a cell defines one or more other cells that can be used for handovers to enable continuous service for users as they move from service area of one cell to service area of another cell.

[0004] It is important that the neighbor list comprises the best handover candidates, but on the other hand there is an upper limit for the size of the neighbor list. That is, all other cells of the network cannot be in neighbor list of one cell. Maximum size of the neighbor list may be for example 30 cells.

[0005] Communication networks constantly evolve, and cells may be added, modified or removed for example due to changes in capacity reguirements, operating environment and available technology. At the same time also neighbor lists defined for cells of the network need to be changed accordingly. That is, the neighbor lists are not static.

[0006] Neighbor list optimization is an important and often time-consuming = task in optimization and operation of mobile communication networks. Typically, N there are tens or hundreds of thousands of cells in the network and therefore S automation of the neighbor list optimization is beneficial for network operators from S operating cost and quality of service perspectives.

E [0007] Basic principle in neighbor list optimization is to remove less o important neighbors and add more important neighbors. The challenge is to identify 3 the less important and more important neighbors. For example key performance S indicators, KPI, obtained from the network have been used for this purpose, but KPI:s from different network vendors are not always reliable or comparable. Additionally, it is difficult to obtain reliable KPI for neighbors that do not exist in the 1 neighbor list and therefore automatically finding new, more important neighbors may be difficult. In many cases, finding new neighbors may require manual work.

SUMMARY

[0008] Various aspects of examples of the invention are set out in the claims.

[0009] According to a first example aspect of the present invention, there is provided a computer implemented method for neighbor list optimization in a communication network as defined in independent claim 1. In an example, the method comprises identifying a first cell where neighbor list optimization is needed; confirming that there exists free space in a neighbor list of the first cell; choosing one or more new neighbors that are not listed in a black list of the first cell; and adding the new neighbors to the neighbor list of the first cell.

[0010] In an embodiment, the method further comprises removing one or more neighbors from the neighbor list of the first cell to confirm that there exists free space in the neighbor list of the first cell; and placing the removed neighbors in the black list of the first cell.

[0011] In an embodiment, one or more neighbors with lowest number of handovers are removed from the neighbor list to confirm that there exists free space in the neighbor list of the first cell.

[0012] In an embodiment, the method further comprises keeping the removed neighbors in the black list for a first predefined period of time.

= [0013] In an embodiment, the first predefined period of time is chosen from N set of: one week, two weeks, one month, 3 months, 5 months.

S [0014] In an embodiment, the method further comprises preventing removal S of the new added neighbors from the neighbor list of the first cell for a second E predefined period of time.

o [0015] In an embodiment, the second predefined period of time is chosen 3 from set of: 1 day, 3 days, 7 days, 14 days, one month.

S [0016] In an embodiment, the one or more new neighbors are chosen on the basis of network geometry.

[0017] In an embodiment, the one or more new neighbors are chosen on the 2 basis of distance between the first cell and other cells of the communication network.

[0018] In an embodiment, the one or more new neighbors are chosen on the basis of antenna directions of the first cell and other cells of the communication network.

[0019] In an embodiment, the one or more new neighbors are chosen on the basis of weight factors calculated between the first cell and other cells of the communication network.

[0020] According to a second example aspect of the present invention, there is provided an apparatus comprising a processor and a memory including computer program code; the memory and the computer program code configured to, with the processor, cause the apparatus to perform the method of the first aspect or any related embodiment.

[0021] According to a third example aspect of the present invention, there is provided a computer program comprising computer executable program code which when executed by a processor causes an apparatus to perform the method of the first aspect or any related embodiment.

[0022] The computer program of the third aspect may be a computer program product stored on a non-transitory memory medium.

[0023] Different non-binding example aspects and embodiments of the present invention have been illustrated in the foregoing. The embodiments in the foregoing are used merely to explain selected aspects or steps that may be utilized in implementations of the present invention. Some embodiments may be presented only with reference to certain example aspects of the invention. It should be appreciated that corresponding embodiments may apply to other example aspects — as well.

S 3 BRIEF DESCRIPTION OF THE DRAWINGS S [0024] For a more complete understanding of example embodiments of the E present invention, reference is now made to the following descriptions taken in o connection with the accompanying drawings in which: 3 [0025] Fig. 1 shows an example scenario according to an embodiment; S [0026] Fig. 2 shows a flow diagram illustrating example methods according to certain embodiments; and

[0027] Fig. 3 shows an apparatus according to an embodiment.

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DETAILED DESCRIPTON OF THE DRAWINGS

[0028] Example embodiments of the present invention and its potential advantages are understood by referring to Figs. 1 through 3 of the drawings. In this document, like reference signs denote like parts or steps.

[0029] In an embodiment of the invention there is provided a neighbor list optimization method that is based on automatically circulating neighbors in the neighbor lists. In an example embodiment, less important neighbors are automatically removed and replaced by new neighbors. Any removed neighbors are put to a black list and only such new neighbors are chosen that are not listed in the black list. New neighbors may be selected on the basis of network geometry in addition to the black list. Use of KPI data is not required for selecting new neighbor candidates.

[0030] Fig. 1 shows an example scenario according to an embodiment. The scenario shows a communication network 101, an automation system 111 and a network operations system 112, such as an operations support system, OSS. The communication network 101, the automation system 111 and the network operations system 112 are communicatively connected to each other.

[0031] The automation system 111 is operable to receive performance indicator values from the communication network 101 via the network operations system 112. The performance indicators may be received separately from different base stations or different cells of the communication network, for example.

[0032] The automation system 111 is operable to interact with the network operations system 112 and to read and modify relevant network configurations in the = network operations system 112. Any changes in the network operations system 112 N are conveyed to the physical base stations and other network elements of the S communication network 101 and the network operates accordingly.

S [0033] The automation system 111 and the network operations system 112 E may be different physical elements or logical elements executed in the same o computer hardware.

3 [0034] In an example embodiment the scenario of Fig. 1 operates as follows: S Performance indicator values are received from the communication network 101 in phases 11 and 12. On the basis of the received performance indicator values the automation system 111 identifies a first cell for neighbor optimization in phase 13.

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The first cell may be identified for example based on a sub-optimal performance. The identification may be based on number of dropped calls or connections in the first cell, for example. If the number of dropped calls or connections exceeds a predefined threshold, it is determined that neighbor optimization is needed.

[0035] Neighbor list of the first cell is obtained from the network operations system 112 in phase 14. The automation system 111 performs optimization for the neighbor list in phase 15 and the optimized list is deployed in the network operations system 112 in phase 16. The optimized neighbor list is conveyed from the network operations system 112 to physical network elements of the first cell in phase 17.

[0036] The process may be continuously repeated. The process may be repeated for each sub-optimally performing cell, for example. Additionally or alternatively, the process may be performed for the whole communication network 101, for a subsection of the communication network 101, or individually for cells or base stations of the communication network 101.

[0037] Fig. 2 shows a flow diagram illustrating example methods according to certain embodiments. The methods may be implemented in the automation system 111 of Fig. 1. The methods are implemented in a computer and do not require human interaction. It is to be noted that the methods may however provide output that may be further processed by humans. For example, automatically performed actions may be logged and the logs may be processed by humans. The shown flow diagram incorporates plurality of embodiments and may be split into parts. The order of phases conducted in the flow chart may be changed except where otherwise explicitly defined. Furthermore, it is to be noted that performing all phases of the flow chart is not mandatory.

= [0038] The flow chart of Fig. 2 comprises following phases: N [0039] Phase 201: A first cell where neighbor list optimization is needed is S identified. For example, number of dropped calls or connections may indicate that S neighbor list optimization is needed.

E [0040] In an example embodiment, it is determined that neighbor list o optimization is needed if rate of dropped calls or connections is more that 03% or 3 number of dropped calls or connections is more than 10 per day. In an example > embodiment, it is determined that neighbor list optimization is needed if rate of dropped calls or connections is more that 0,3% and number of dropped calls or connections is more than 10 per day. Clearly these are only example parameters and values and also other threshold parameters and threshold values may be used.

[0041] Phase 202: It is confirmed that there exists free space in a neighbor list of the first cell. One or more neighbors may be removed from the neighbor list of the first cell to confirm that there exists free space. For example, cells that have not been used for handovers, may be removed. Alternatively, cells that have lowest number of handovers, may be removed. If the neighbor list has at least one free slot, removal of neighbors is not mandatory. In an embodiment it is required that there are at least two free slots in the list. One of these free slots may be reserved for optimization and the other one may be reserved for use in case new cells or base stations are added into the network.

[0042] If there are completely unused neighbor cells in the neighbor list of the first cell, such unused cells may be removed even if the list were not full.

[0043] Phase 205: Any removed neighbors are placed in a black list of the first cell.

[0044] Phase 206: The removed neighbors are kept in the black list for a first predefined period of time. The first predefined period of time may be for example one week, two weeks, one month, 3 months, or 5 months. In this way, it is guaranteed that a removed cell is not immediately added back to the neighbor list. In this way it can be guaranteed that different cells are actually being circulated in the list.

[0045] If there are many potential neighbor cells (for example in city areas), the first predefined period of time may be longer. If there are only few potential neighbor cells (for example in rural areas), shorter time period may be applied so that the system does not run out of possible new neighbors to consider.

[0046] Phase 207: One or more new neighbors that are not listed in the = black list of the first cell are chosen. N [0047] The new neighbors may be chosen on the basis network geometry. S For example, distance between the first cell and other cells of the communication S network and/or antenna directions of the first cell and other cells of the E communication network may be used For example other cells within smallest o distance may be chosen for new neighbors or other cells with antenna directions 3 pointing towards the first cell may be chosen for new neighbors. In yet another S alternative, the new neighbors are chosen on the basis of weight factors calculated between the first cell and other cells of the communication network. The weight factor may be based on distance between cells and antenna directions of cells and 6 other cells providing largest weight factors may be chosen for new neighbors.

[0048] Phase 208: The chosen new neighbors are added to the neighbor list of the first cell to obtain optimized neighbor list and the optimized neighbor list is taken into use in the first cell. The number of neighbors that are being added may depend on the number of neighbors in the list. If the list is relatively empty, more new neighbors may be added. If the list is nearly full, one new neighbor is generally added. Added neighbors may be either unidirectional (enabling handover from a first cell to a second cell) or bidirectional (enabling handover from a first cell to a second cell and vice versa).

[0049] If an added new neighbor is a relevant neighbor cell the new neighbor starts to gather handovers and such new neighbor will not be removed from the list in following optimization rounds.

[0050] Phase 209: Removal of the new added neighbors from the neighbor list of the first cell is prevented for a second predefined period of time. The second predefined period of time may be for example 1 day, 3 days, 7 days, 14 days, one month. In this way the new neighbor cell is not immediately removed from the neighbor list. Instead the new neighbor cell is provided a change to gather handovers in different operating conditions for example if user distribution and amount of connections varies between different time periods. Demand may be different during weekdays and weekends or during summer season and winter season etc.

[0051] Fig. 3 shows an apparatus 30 according to an embodiment. The apparatus 30 is for example a general-purpose computer or server or some other electronic data processing apparatus. The apparatus 30 can be used for = implementing embodiments of the invention. That is, with suitable configuration the N apparatus 30 is suited for operating for example as the automation system 111 of the S foregoing disclosure. S [0052] The general structure of the apparatus 30 comprises a processor 31, E and a memory 32 coupled to the processor 31. The apparatus 30 further comprises o software 33 and database 34 stored in the memory 32 and operable to be loaded 3 into and executed in the processor 31. The software 33 may comprise one or more S software modules and can be in the form of a computer program product. The database 34 may be usable for storing e.g. rules and patterns for use in data analysis. Further, the apparatus 30 comprises a communication interface 35 coupled 7 to the processor 31.

[0053] The processor 31 may comprise, e.g., a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a graphics processing unit, or the like. Fig. 3 shows one processor 31, but the apparatus 30 may comprise a plurality of processors.

[0054] The memory 32 may be for example a non-volatile or a volatile memory, such as a read-only memory (ROM), a programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), a random-access memory (RAM), a flash memory, a data disk, an optical storage, a magnetic storage, a smart card, or the like. The apparatus 30 may comprise a plurality of memories. The memory 32 may be constructed as a part of the apparatus 30 or it may be inserted into a slot, port, or the like of the apparatus 30 by a user.

[0065] The communication interface 35 may comprise communication modules that implement data transmission to and from the apparatus 30. The communication modules may comprise, e.g., a wireless or a wired interface module. The wireless interface may comprise such as a WLAN, Bluetooth, infrared (IR), radio frequency identification (RF ID), GSM/GPRS, CDMA, WCDMA, or LTE (Long Term Evolution) radio module. The wired interface may comprise such as Ethernet or universal serial bus (USB), for example. Further the apparatus 30 may comprise a user interface (not shown) for providing interaction with a user of the apparatus. The user interface may comprise a display and a keyboard, for example. The user interaction may be implemented through the communication interface 35, too.

[0056] The database 34 may be certain memory area in the memory 32 or alternatively the database 34 may be a separate component or the database 34 may = be located in a physically separate database server that is accessed for example N through the communication unit 35. The database unit 34 may be a relational (SOL) S or a non-relational (NoSOL) database. S [0057] Askilled person appreciates that in addition to the elements shown in E Fig. 3, the apparatus 30 may comprise other elements, such as microphones, o displays, as well as additional circuitry such as memory chips, application-specific 3 integrated circuits (ASIC), other processing circuitry for specific purposes and the S like. Further, it is noted that only one apparatus is shown in Fig. 3, but the embodiments of the invention may equally be implemented in a cluster of shown apparatuses. 8

[0058] Without in any way limiting the scope, interpretation, or application of the claims appearing below, a technical effect of one or more of the example embodiments disclosed herein is ability automatically optimize neighbor lists whereby human resources can be saved. By circulating the cells in the neighbor list, the neighbor list may gradually converge towards optimal list.

[0059] Another technical effect of one or more of the example embodiments disclosed herein is that a technology and vendor independent solution is provided. The same implementation can be applied in 3G, 4G and 5G networks for example.

[0060] Another technical effect of one or more of the example embodiments disclosed herein is that there is no need to obtain key performance indicator, KPI, data for determining new neighbors.

[0061] Another technical effect of one or more of the example embodiments disclosed herein is that complex systems with increasing traffic amount can be optimized.

[0062] Another technical effect of one or more of the example embodiments disclosed herein is that the optimization method of various embodiments inherently reacts and adopts to changes in the network. The changes may be short term or long term changes.

[0063] If desired, the different functions discussed herein may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the before-described functions may be optional or may be combined.

[0064] Although various aspects of the invention are set out in the independent claims, other aspects of the invention comprise other combinations of features from the described embodiments and/or the dependent claims with the = features of the independent claims, and not solely the combinations explicitly set out N in the claims. S [0065] It is also noted herein that while the foregoing describes example S embodiments of the invention, these descriptions should not be viewed in a limiting E sense. Rather, there are several variations and modifications, which may be made o without departing from the scope of the present invention as defined in the appended 3 claims.

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Claims (13)

1. A computer implemented method for neighbor list optimization in a communication network (101), the method comprising identifying (201) a first cell where neighbor list optimization is needed; confirming (202) that there exists free space in a neighbor list of the first cell; characterized in that the method comprises choosing (207) one or more new neighbors that are not listed in a black list of the first cell, wherein the black list is a list of cells that are not to be added to the neighbor list; and adding (208) the new neighbors to the neighbor list of the first cell.

2. The method of claim 1, further comprising removing one or more neighbors from the neighbor list of the first cell to confirm that there exists free space in the neighbor list of the first cell; and placing (205) the removed neighbors in the black list of the first cell.

3. The method of claim 2, wherein one or more neighbors with lowest number of handovers are removed.

4. The method of claim 2 or 3, further comprising keeping (206) said removed neighbors in the black list for a first predefined period of time.

5. Themethodof claim 4, wherein said first predefined period of time is chosen from set of: one week, two weeks, one month, 3 months, 5 months.

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6. The method of any preceding claim, further comprising preventing (209) S removal of the new added neighbors from the neighbor list of the first cell for a I second predefined period of time. 2

7. The method of claim 6, wherein said second predefined period of time is 3 chosen from set of: 1 day, 3 days, 7 days, 14 days, one month.

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8. The method of any preceding claim, wherein the one or more new neighbors are chosen on the basis of network geometry.

9. The method of any preceding claim, wherein the one or more new neighbors are chosen on the basis of distance between the first cell and other cells of the communication network.

10. The method of any preceding claim, wherein the one or more new neighbors are chosen on the basis of antenna directions of the first cell and other cells of the communication network.

11. The method of any preceding claim, wherein the one or more new neighbors are chosen on the basis of weight factors calculated between the first cell and other cells of the communication network.

12. An apparatus (30, 111) comprising a processor (31), and a memory (32) including computer program code; the memory and the computer program code configured to, with the processor, cause the apparatus to perform the method of any one of claims 1-11.

13. A computer program comprising computer executable program code (33) which when executed by a processor causes an apparatus to perform the method of any one of claims 1-11.

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