Network device optimization method and apparatus, electronic device, and computer program product

Abstract

The present disclosure relates to the field of communications, and in particular to a network device optimization method and apparatus, an electronic device, and a computer program product. The method comprises: performing region division on a plurality of network devices to generate a plurality of first regions; performing interference path analysis on the network devices in each first region so as to generate a plurality of first interference path analysis results; on the basis of the plurality of first interference path analysis results, determining a plurality of second regions; on the basis of the second regions and a coding strategy, determining a network device code corresponding to each of the plurality of network devices; on the basis of the network device codes, performing interference path analysis on the plurality of network devices so as to generate a second interference path analysis result; and on the basis of a preset condition, determining an anomalous network device corresponding to an anomalous value in the second interference path analysis result, correcting the anomalous network device, and determining an updated network device code of the anomalous network device. The method achieves the uniqueness of a sequence code of an interfering base station, precise localization of the interfering base station, and real-time performance.

Description

Network equipment optimization methods, apparatuses, electronic devices and computer program products

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is based on and claims priority to Chinese Patent Application No. 202410513825.7, filed on April 26, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to the field of communications, and more particularly to a network device optimization method, apparatus, electronic device, and computer program product. Background Technology

[0004] Due to the massive scale of 5G base stations in my country and the complex atmospheric waveguide interference paths between them, the distance between interfering base stations may exceed 300-400 kilometers, often resulting in cross-provincial / cross-city interference issues. Current technologies lack sufficient reference signals to ensure the uniqueness of the sequence code of the interfering base station, leading to the detected base station detecting multiple identical sequences and making accurate identification of the interfering base station impossible. Alternatively, increasing the complexity of the hardware circuitry may be necessary for accurate identification, but this method suffers from compatibility issues and cannot be widely applied.

[0005] Meanwhile, atmospheric waveguide interference is a short-term, sudden interference problem, and existing technologies cannot meet its timeliness requirements. Summary of the Invention

[0006] This disclosure is made in view of the above-mentioned problems. This disclosure provides a network device optimization method, apparatus, electronic device, and computer program product.

[0007] According to one aspect of this disclosure, a network device optimization method is provided, the method comprising: dividing multiple network devices into regions to generate multiple first regions; performing interference path analysis on network devices in each first region to generate multiple first interference path analysis results; determining multiple second regions based on the multiple first interference path analysis results; determining the network device code corresponding to each of the multiple network devices based on the second regions and a coding strategy; performing interference path analysis on the multiple network devices based on the network device codes to generate second interference path analysis results; determining abnormal network devices corresponding to outliers in the second interference path analysis results based on preset conditions, correcting the abnormal network devices, and determining the updated network device codes of the abnormal network devices.

[0008] Furthermore, according to one aspect of the network device optimization method of this disclosure, interference path analysis is performed on network devices in each first region to generate multiple first interference path analysis results, including: configuring a corresponding first code for each first region, wherein the first code is unique; collecting interference data for network devices in each first region based on the far-end interference reference signal RIM-RS; and generating a first interference path analysis result corresponding to each first region based on the interference data and the first code.

[0009] Furthermore, according to one aspect of the network device optimization method of this disclosure, determining multiple second regions based on the analysis results of multiple first interference paths includes: re-dividing multiple network devices into regions based on the analysis results of multiple first interference paths to determine the second regions, wherein there are no interference paths between network devices in each second region.

[0010] Furthermore, according to one aspect of the network device optimization method of this disclosure, determining the network device code corresponding to each of the plurality of network devices based on a second region and a coding strategy includes: mapping a first code corresponding to a first region to a second code corresponding to a second region based on the coding strategy, wherein the number of bits in the second code is less than the number of bits in the first code; and determining the network device code corresponding to each of the plurality of network devices based on the second code.

[0011] Furthermore, according to one aspect of the network device optimization method disclosed herein, the process of correcting abnormal network devices and determining the updated network device code of the abnormal network devices includes: performing interference path analysis on the abnormal network devices and generating interference path analysis results for the abnormal network devices; and determining the updated network device code for the abnormal network devices when the interference path analysis results for the abnormal network devices meet preset conditions.

[0012] According to another aspect of this disclosure, a network device optimization apparatus is provided, comprising: a first partitioning module for partitioning multiple network devices into regions to generate multiple first regions; a first analysis module for performing interference path analysis on network devices in each first region to generate multiple first interference path analysis results; a second partitioning module for determining multiple second regions based on the multiple first interference path analysis results; an encoding mapping module for determining the network device code corresponding to each of the multiple network devices based on the second regions and an encoding strategy; a second analysis module for performing interference path analysis on multiple network devices based on the network device codes to generate second interference path analysis results; and an anomaly correction module for determining the abnormal network devices corresponding to the abnormal values ​​in the second interference path analysis results based on preset conditions, correcting the abnormal network devices, and determining the updated network device codes of the abnormal network devices.

[0013] Furthermore, according to one aspect of the network device optimization apparatus of this disclosure, the first analysis module includes: a first coding unit, configured to configure a corresponding first code for each first region, wherein the first code is unique; a data acquisition unit, configured to acquire interference data of network devices in each first region based on the far-end interference reference signal RIM-RS; and a first analysis unit, configured to generate a first interference path analysis result corresponding to each first region based on the interference data and the first code.

[0014] Furthermore, according to one aspect of the network device optimization apparatus of this disclosure, the second partitioning module includes: a second partitioning unit, configured to re-partition multiple network devices into regions based on the analysis results of multiple first interference paths, and determine a second region, wherein there are no interference paths between network devices in each second region.

[0015] Furthermore, according to one aspect of the network device optimization apparatus of this disclosure, the encoding mapping module includes: an encoding mapping unit, configured to map a first code corresponding to a first region to a second code corresponding to a second region based on an encoding strategy, wherein the number of bits in the second code is less than the number of bits in the first code; and a second encoding unit, configured to determine a network device code corresponding to each of a plurality of network devices based on the second code.

[0016] Furthermore, according to one aspect of the network device optimization apparatus of this disclosure, the anomaly correction module includes: an anomaly analysis unit, used to perform interference path analysis on the abnormal network device and generate interference path analysis results of the abnormal network device; and a coding update unit, used to determine the updated network device coding of the abnormal network device when the interference path analysis results of the abnormal network device meet preset conditions.

[0017] According to another aspect of this disclosure, an electronic device is provided, comprising: a memory for storing computer-readable instructions; and a processor for executing the computer-readable instructions, causing the electronic device to perform the network device optimization method as described above.

[0018] According to another aspect of this disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, it implements the network device optimization method as described above.

[0019] According to another aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the network device optimization method as described above.

[0020] As will be described in detail below, the network device optimization method according to embodiments of this disclosure achieves the uniqueness of the sequence code of the harassing base station, accurate location of the harassing base station, and timeliness requirements without increasing circuit and encoding / decoding complexity.

[0021] It should be understood that both the foregoing general description and the following detailed description are exemplary and intended to provide further illustration of the claimed technology. Attached Figure Description

[0022] The above and other objects, features, and advantages of this disclosure will become more apparent from the more detailed description of the embodiments thereof in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this disclosure and form part of the specification. They are used together with the embodiments of this disclosure to explain the disclosure and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0023] Figure 1 is a schematic diagram illustrating a scenario of co-channel interference caused by atmospheric waveguides according to existing technology.

[0024] Figure 2 is a flowchart illustrating a network device optimization method according to an embodiment of the present disclosure.

[0025] Figure 3 is a flowchart illustrating the interference path analysis method according to an embodiment of the present disclosure.

[0026] Figure 4 is a schematic diagram illustrating the principle of interference identification based on RIM-RS according to an embodiment of the present disclosure.

[0027] Figure 5 is a schematic diagram of a network device optimization apparatus according to an embodiment of the present disclosure.

[0028] Figure 6 is a hardware block diagram illustrating an electronic device according to an embodiment of the present disclosure.

[0029] Figure 7 is a schematic diagram illustrating a computer program product according to an embodiment of the present disclosure. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this disclosure more apparent, exemplary embodiments according to this disclosure will now be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this disclosure, and not all embodiments of this disclosure. It should be understood that this disclosure is not limited to the exemplary embodiments described herein.

[0031] First, let’s take a look at the application scenarios according to the embodiments of this disclosure with reference to FIG1.

[0032] Figure 1 is a schematic diagram illustrating a scenario of co-channel interference caused by atmospheric waveguides according to existing technology. As shown in Figure 1(A), atmospheric waveguides refer to an abnormal atmospheric structure, mainly caused by atmospheric temperature inversion (temperature increases with altitude) and humidity inversion (water vapor density decreases rapidly with altitude). When atmospheric waveguides occur, electromagnetic waves propagating in the near-surface layer are affected by atmospheric refraction, causing their propagation trajectory to bend towards the ground. When the curvature exceeds the curvature of the Earth's surface, the electromagnetic waves will bend towards the ground and continue propagating after being reflected by the ground. This process is repeated multiple times, causing them to propagate forward in a circuitous manner between the ground and a certain atmospheric layer. Because this situation is similar to the propagation of microwaves in a waveguide, it is called atmospheric waveguide propagation.

[0033] The presence of atmospheric waveguides can interfere with the propagation path and range of electromagnetic waves, thereby affecting communication systems and causing issues such as signals propagating over extremely long distances and unstable mobile phone signals.

[0034] Network equipment can be understood as a base station. A base station is an important component of a wireless communication system. It can be a base station (BTS) in a Global System for Mobile Communications (GSM) or Code Division Multiple Access (CDMA) communication system, a base station (nodeB, NB) in a Wideband Code Division Multiple Access (WCDMA) communication system, an evolved Node B (eNB or eNodeB) in a Long Term Evolution (LTE) communication system, a next-generation base station (ng-eNB) in a New Radio (NR) communication system, a next-generation Node B (gNB) in a NR communication system, or a base station in a future communication system, or other equipment in the core network (CN). This disclosure does not impose specific limitations. Similarly, for ease of description, this disclosure uses a 5G base station as an example, which is merely illustrative and does not constitute a limitation.

[0035] As shown in Figure 1(B), in my country's Time Division Duplex (TDD) system, a co-channel uplink / downlink transmission scheme is adopted. Interference between uplink and downlink signals between base stations is avoided through uplink / downlink guard period (GP) configuration. Because signal loss is very low within the atmospheric waveguide layer, even after the GP guard distance, the downlink signal from the far-end base station still possesses strong power. Simultaneously, the increased transmission distance leads to increased propagation delay, causing the strong downlink signal from the far-end base station to fall into the uplink subframe of the near-end base station. This raises the noise floor of the near-end base station, causing the useful signal to be submerged and resulting in severe co-channel interference at the near-end base station.

[0036] In my country, atmospheric ducting interference (TDD) mainly occurs in coastal and rural plain areas, primarily between March and November. The Bohai Bay, Beibu Gulf, North China Plain, and East China Plain are particularly affected, experiencing frequent inter-provincial / inter-city interference. In severe cases, this can raise cell noise floor by nearly 20 dB, shrinking uplink coverage radius by 40%, and drastically deteriorating network connectivity, uptime, and handover performance, leading to frequent large-scale user complaints. Taking a coastal province as an example, depending on the intensity of the atmospheric ducting effect, thousands of base stations are affected, significantly impacting user experience. Due to the vast scale of base stations in my country and the complex atmospheric ducting interference paths between them, the distance between interfering base stations can exceed 300-400 kilometers, exceeding the detection range of Remote Interference Management (RIM). Furthermore, in many cases, this interference crosses provincial and / or municipal boundaries, lacking sufficient orthogonal reference signals to ensure the uniqueness of the interfering base station's sequence code. This results in multiple identical sequences being detected by affected base stations, making it impossible to accurately identify the interfering base station.

[0037] Figure 2 is a flowchart illustrating a network device optimization method according to an embodiment of the present disclosure. As shown in Figure 2, the network device optimization method may include at least the following steps.

[0038] In step S201, multiple network devices are divided into regions to generate multiple first regions. As mentioned above, network devices can be base stations, and the base stations affected by atmospheric waveguide interference may involve tens of thousands of base stations. This step aims to perform the first regional division of base stations. The division can be based on administrative provinces, past experience, artificial intelligence (AI) models, geographical environment, or other division criteria. This disclosure does not impose any specific limitations. Based on the above first regional division, N first regions will be obtained (for example, denoted as Region 1, Region 2, ..., Region N, where N is a positive integer).

[0039] In one embodiment of this disclosure, the division can be based on administrative provinces, with one province / municipality / autonomous region corresponding to one first region, and each first region is unique.

[0040] In another embodiment of this disclosure, segmentation can be performed based on an AI model. Specifically:

[0041] Currently, in the LTE TDD standard, China Mobile's spectrum resources are 1880-1900MHz, 2320-2370MHz, and 2575-2635MHz; China Unicom's spectrum resources are 2300-2320MHz and 2555-2575MHz; and China Telecom's spectrum resources are 2370-2390MHz and 2635-2655MHz.

[0042] In the 5G TDD standard, China Mobile's frequency resources are 2515MHz-2675MHz and 4800MHz-4900MHz; China Telecom's frequency resources are 3400MHz-3500MHz; and China Unicom's frequency resources are 3500MHz-3600MHz.

[0043] Atmospheric waveguides mainly create a free-space propagation-like structure, which reduces path loss and causes TDD downlink signals to propagate beyond the protection distance, resulting in co-channel interference with remote base stations. Free-space loss is calculated using a free-space propagation loss model.

[0044] Free space refers to the region where electromagnetic waves can propagate freely in the absence of obvious physical obstacles or media.

[0045] or L bf (dB)=32.45+20lg[f(MHz)]+20lg[r(km)]

[0046] Among them, P t P r These represent the transmit power and receive power, respectively; r is the radio wave propagation distance; λ is the wavelength; f is the frequency; L bf (dB) represents link loss. Propagation loss is proportional to frequency and distance. 1880MHz is currently the lowest conventional frequency for TDD, and it has the longest propagation distance under the same conditions. Calculations show that the propagation loss per meter at 1800MHz is approximately 37.5dB.

[0047] Signal reception strength refers to the strength of the wireless signal received by the receiving station equipment. It is calculated as follows: RSS = P t +G r +G t -L c -L bf

[0048] Among them, G r For the receiving antenna gain, G t For the transmit antenna gain, L c For, L bf This refers to link loss.

[0049] Based on the aforementioned free space loss and the basic conditions of the existing network base station equipment, the maximum transmission range of the base station under atmospheric waveguide conditions can be determined, with the atmospheric waveguide physical path not exceeding 500km. Based on this range and mountain barriers, a first regional division can be made, as shown in Table 1.

[0050] Table 1

[0051] It should be noted that the above embodiments are merely illustrative and do not constitute a limitation; they are applicable to similar issues both domestically and internationally.

[0052] In step S202, interference path analysis is performed on the network devices in each first region, generating multiple first interference path analysis results. As mentioned above, N first regions have been obtained in step S201. The specific method of interference path analysis will be described in detail below with reference to FIG3.

[0053] Figure 3 is a flowchart illustrating an interference path analysis method according to an embodiment of the present disclosure. As shown in Figure 3, the interference path analysis method may include at least the following steps.

[0054] In step S301, a corresponding first code is configured for each first region, wherein the first code is unique. As described above, N first regions have been obtained. Within each first region, a unique code is configured for all base stations, denoted as gNB ID.

[0055] In one embodiment of this disclosure, the binary representation of gNB ID can be X1X2X3X4X5X6, where X1X2X3X4X5X6 is 24 bits in total, and X1X2 occupies 8 bits. This can be understood as the first encoding mentioned above. All base stations in each first area have the same X1X2, while X3X4X5X6 are different. The X1X2 of different first areas are different from each other.

[0056] In step S302, interference data is collected for each network device in the first area based on the far-end interference reference signal (RIM-RS). RIM-RS refers to the interference signal caused by the presence of a far-end interference source in a wireless communication system. This interference signal typically originates from other wireless devices or electromagnetic sources outside the system, and may have a similar or identical signal frequency to the target communication system, leading to mutual interference. The far-end interference reference signal and the target communication system are usually some distance apart, hence the term far-end interference.

[0057] Remote interference reference signals can negatively impact the performance and quality of a target communication system, such as reducing communication quality, increasing the bit error rate, and decreasing data transmission rate. To mitigate the effects of remote interference, various techniques are typically employed to suppress or reduce its impact, including frequency-selective reception, automatic gain control, and signal processing algorithms.

[0058] Specifically, the method for identifying interference based on RIM-RS will be described in detail with reference to Figure 4.

[0059] Figure 4 is a schematic diagram illustrating the principle of interference identification based on RIM-RS according to an embodiment of the present disclosure. As shown in Figure 4, the presence of interference can be identified between the interfering base station and the interfered base station through RIM-RS. The specific method is as follows:

[0060] In the event of atmospheric waveguide interference, there is an interference path between the interfering base station and the affected base station.

[0061] (1) After detecting that its received signal has characteristics such as increased noise floor and ramp, the disturbed base station starts monitoring the RS signal and sends the RS-1 signal to the disturbing base station. Then the disturbing base station starts monitoring the RS signal according to the information from the central control station.

[0062] (2) When the harassing base station detects the RS-1 signal, it activates the adaptive interference mitigation adjustment measures and sends the RS-2 signal to the harassed base station.

[0063] (3) If the disturbed base station can receive the RS-2 signal, it means that the disturbed base station is still being interfered with by the disturbing base station. At this time, the disturbed base station will continue to send the RS-1 signal to the disturbing base station. If the disturbed base station does not receive the RS-2 signal again within the limited period and the noise floor recovers, it means that the atmospheric waveguide path has disappeared. At this time, the disturbed base station will stop sending the RS-1 signal.

[0064] (4) If the interfering base station continues to receive RS-1 signals, continue mitigation measures; if no RS-1 signals are received, start restoring the original configuration.

[0065] This concludes the explanation of the principle of interference identification based on RIM-RS.

[0066] As stated above, one of the purposes of this disclosure is to achieve accurate location of the harassing base station. To achieve this, RIM-RS needs to be used in conjunction with RIM feature sequences.

[0067] In the 3GPP RIM technology, base stations can identify themselves by sending specific sequence codes, helping surrounding base stations and / or terminal equipment to identify their location and signal characteristics. This specific sequence code refers to the RIM feature sequence.

[0068] In one embodiment of this disclosure, based on the above-described principle of interference identification based on RIM-RS, the parameters in the RIM feature sequence can be as shown in Table 2.

[0069] Table 2

[0070] Based on the atmospheric waveguide formation conditions, when collecting interference data (such as the RIM characteristic sequence mentioned above) of the disturbed base station, it is necessary to take into account the atmospheric waveguide interference under different weather conditions.

[0071] Specifically, atmospheric waveguides are primarily affected by humidity and temperature. When the temperature near the ground is low, and the temperature T increases with altitude, an inversion layer forms. If the water vapor density e w When a layer of atmospheric humidity sharply decreases with increasing altitude, the atmospheric refractive index exceeds the curvature of the Earth's surface, leading to atmospheric waveguide phenomena, the expression of which is as follows:

[0072] Where T is temperature, in K; and p is pressure, in hPa.

[0073] In step S303, based on the interference data and the first encoding, the first interference path analysis result corresponding to each first region is generated. As mentioned above, the interference data (as shown in Table 2, including RimRsSetID information) and the gNB ID including the first encoding have been obtained in steps S302 and S301, respectively. In this step, based on the RimRsSetID information received by the disturbed base station (which may point to the disturbing base station), data aggregation and statistics will be performed on the disturbing base station to determine the path relationship set between the disturbing base station and the disturbed base station in each first region.

[0074] Within each first region, RimRsSetID, as a unique value, can directly correspond to the base station code (gNB ID). By using the engineering parameter information corresponding to the base station code, the latitude and longitude information of the disturbed base station and the interfering base station can be found. Thus, the actual physical distance between the disturbed base station and the interfering base station can be calculated. Then, abnormal interference paths with an actual physical distance exceeding 500km are eliminated, resulting in a set of multiple interference path relationships with normal actual physical distances, denoted as the analysis results of multiple first interference paths.

[0075] The analysis results of these multiple primary interference paths can form a table of base station interference path relationships for the entire region.

[0076] In one embodiment of this disclosure, the base station interference path relationship table for the entire area can be as shown in Table 3:

[0077] Table 3

[0078] This concludes the introduction to the interference path analysis method. We will now return to Figure 2 to continue with the subsequent steps of the network device optimization method.

[0079] In step S203, multiple second regions are determined based on the analysis results of multiple first interference paths. As mentioned above, in the previous steps, based on experience or other division criteria, the base stations within the entire region were divided into regions for the first time, and the results of the first interference path analysis were obtained. This step will perform a more precise second region division of the base stations within the entire region based on the results of the first interference path analysis. The division criterion for this second division is: there are no interference paths between base stations in each newly divided region. For ease of description, the newly divided regions are referred to as the second regions.

[0080] In step S204, based on the second region and coding strategy, the corresponding network device code for each of the multiple network devices is determined. As mentioned above, atmospheric duct interference is a short-term, sudden interference problem. Therefore, interference mitigation requires recovering the network quality loss caused by interference as quickly as possible, which necessitates minimizing detection latency. This step aims to shorten the coding time and increase transmission efficiency.

[0081] This step can be further refined:

[0082] 1. Based on the encoding strategy, the first encoding corresponding to the first region is mapped to the second encoding corresponding to the second region, wherein the number of bits in the second encoding is less than the number of bits in the first encoding.

[0083] Specifically, the coding strategy can be to shorten the base station's gNB ID from 24 bits to 20 bits. The existing 24-bit gNB ID has too low response efficiency to atmospheric duct interference. Pilot tests have shown that if it is shortened to 22 bits (using Nf = 4 frequency division * Ns = 4 code division), the single RS transmission period is 43 minutes, which still results in an excessively long detection period and low response efficiency. Therefore, this disclosure innovatively shortens it to 20 bits, with a single RS transmission period of 22 minutes, which meets the response efficiency requirements.

[0084] As mentioned above, the binary representation of the gNB ID can be X1X2X3X4X5X6, where X1X2X3X4X5X6 is a total of 24 bits, and the first encoding X1X2 occupies 8 bits. The encoding strategy can map X1X2 and the high 2 bits of the cell ID to a 4-bit binary A (i.e., the second encoding).

[0085] In one embodiment of this disclosure, the mapping relationship from X1 to X2 to A can be as shown in Table 4.

[0086] Table 4

[0087] 2. Based on the second encoding, determine the corresponding network device encoding for each of the plurality of network devices. As described above, the 8-bit X1X2 is mapped to the 4-bit A, and then the subsequent X3X4X5X6 (a total of 16 bits) remain unchanged, so that the base station encoding after mapping is 20 bits, which can be denoted as AX3X4X5X6. AX3X4X5X6 ensures both encoding shortening and uniqueness.

[0088] In step S205, based on the network device coding, interference path analysis is performed on multiple network devices to generate a second interference path analysis result. As mentioned above, the shortened coding AX3X4X5X6 was obtained in step S204. Based on this coding, the above interference path analysis is performed on the collected interference data, and the physical distance between the interfering base station and the interfered base station is recalculated in conjunction with the engineering parameter information, which is recorded as the second interference path analysis result.

[0089] In step S206, based on preset conditions, the abnormal network device corresponding to the abnormal value in the second interference path analysis result is determined, the abnormal network device is corrected, and the updated network device code of the abnormal network device is determined.

[0090] In one embodiment of this disclosure, the preset condition may be that the physical distance does not exceed 500km.

[0091] Based on preset conditions, abnormal base stations corresponding to outliers in the second interference path analysis results obtained in step S205 are identified, and these abnormal base stations are corrected. The correction method may involve retransmitting the reference signal, acquiring and analyzing data, recalculating the physical distance, determining the correct interference path, and determining the updated correct base station code through mapping to ensure its uniqueness.

[0092] The above methods can be applied to atmospheric waveguide generation areas for a long time. When a major tectonic plate movement occurs, a new mapping scheme can be relearned and configured for the areas involved in the movement.

[0093] Figure 5 is a schematic diagram illustrating a network device optimization apparatus according to an embodiment of the present disclosure. As shown in Figure 5, the network device optimization apparatus 500 may include at least the following modules.

[0094] The first partitioning module 501 is used to partition multiple network devices into regions and generate multiple first regions.

[0095] The first analysis module 502 is used to perform interference path analysis on network devices in each first area and generate multiple first interference path analysis results.

[0096] The second partitioning module 503 is used to determine multiple second regions based on the analysis results of multiple first interference pathways.

[0097] The encoding mapping module 504 is used to determine the corresponding network device encoding for each of the multiple network devices based on the second region and the encoding strategy.

[0098] The second analysis module 505 is used to perform interference path analysis on multiple network devices based on network device coding, and generate a second interference path analysis result.

[0099] The anomaly correction module 506 is used to determine the abnormal network device corresponding to the abnormal value in the second interference path analysis result based on preset conditions, correct the abnormal network device, and determine the updated network device code of the abnormal network device.

[0100] The first analysis module 502 may further include:

[0101] The first coding unit 5021 is used to configure a corresponding first code for each first region, wherein the first code is unique;

[0102] Data acquisition unit 5022 is used to acquire interference data of network devices in each first area based on the far-end interference reference signal RIM-RS;

[0103] The first analysis unit 5023 is used to generate the first interference path analysis result corresponding to each first region based on the interference data and the first code.

[0104] The second partitioning module 503 may further include:

[0105] The second partitioning unit 5031 is used to re-partition multiple network devices based on the first interference path analysis results to determine a second region, wherein there is no interference path between network devices in each second region.

[0106] The encoding mapping module 504 may further include:

[0107] The encoding mapping unit 5041 is used to map the first code corresponding to the first region to the second code corresponding to the second region based on the encoding strategy, wherein the number of bits of the second code is less than the number of bits of the first code;

[0108] The second coding unit 5042 is used to determine the network device code for each of the multiple network devices based on the second coding.

[0109] The anomaly correction module 506 may further include:

[0110] Anomaly analysis unit 5061 is used to perform interference path analysis on abnormal network devices and generate interference path analysis results for abnormal network devices.

[0111] The coding update unit 5062 is used to determine the updated network device code of the abnormal network device when the interference path analysis results of the abnormal network device meet the preset conditions.

[0112] Figure 6 is a hardware block diagram illustrating an electronic device according to an embodiment of the present disclosure. The electronic device according to an embodiment of the present disclosure includes at least a processor and a memory for storing computer-readable instructions. When the computer-readable instructions are loaded and executed by the processor, the processor performs the network device optimization method as described above.

[0113] The electronic device 600 shown in Figure 6 specifically includes a central processing unit (CPU) 601, a graphics processing unit (GPU) 602, and a memory 603. These units are interconnected via a bus 604. The CPU 601 and / or GPU 602 can function as the aforementioned processors, and the memory 603 can function as the aforementioned memory storing computer-readable instructions. Furthermore, the electronic device 600 may also include a communication unit 605, a storage unit 606, an output unit 607, an input unit 608, and an external device 609, all of which are also connected to the bus 604.

[0114] Figure 7 is a schematic diagram illustrating a computer program product according to an embodiment of the present disclosure. As shown in Figure 7, a computer program product 700 according to an embodiment of the present disclosure stores a computer program 701 thereon. When the computer program 701 is executed by a processor, it performs the network device optimization method described with reference to the above figures. The computer program product includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0115] The network device optimization method, apparatus, electronic device, and computer program product according to embodiments of the present disclosure have been described above with reference to the accompanying drawings. The network device optimization method according to embodiments of the present disclosure achieves the requirements of uniqueness of the sequence code of the scrambling base station, accurate location of the scrambling base station, and timeliness without increasing circuit and encoding / decoding complexity.

[0116] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0117] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this disclosure are merely illustrative and not restrictive, and should not be construed as necessarily possessed by each embodiment of the present disclosure. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, rather than as limitations. These details do not limit the present disclosure to necessarily being implemented using these specific details.

[0118] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0119] Additionally, as used herein, the “or” used in a list of items beginning with “at least one” indicates a separate list, such that a list of, for example, “at least one of A, B, or C” means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word “exemplary” does not imply that the described example is preferred or better than other examples.

[0120] It should also be noted that in the systems and methods of this disclosure, the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions to this disclosure.

[0121] Various changes, substitutions, and modifications may be made to the technology described herein without departing from the teachings defined by the appended claims. Moreover, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of things, means, methods, and actions described above. Currently existing or later developed processes, machines, manufactures, compositions of things, means, methods, or actions that perform substantially the same function or achieve substantially the same results as the corresponding aspects described herein may be utilized. Accordingly, the appended claims include within their scope such processes, machines, manufactures, compositions of things, means, methods, or actions.

[0122] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0123] The above description has been provided for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for optimizing network devices, characterized in that, The method includes: Divide multiple network devices into regions to generate multiple first regions; For each network device in the first region, perform interference path analysis to generate multiple first interference path analysis results; Based on the analysis results of the multiple first interference pathways, multiple second regions were identified; Based on the second region and the encoding strategy, determine the corresponding network device code for each of the plurality of network devices; Based on the network device coding, the interference path analysis is performed on the multiple network devices to generate a second interference path analysis result. Based on preset conditions, the abnormal network devices corresponding to the outliers in the second interference path analysis results are identified, the abnormal network devices are corrected, and the updated network device codes of the abnormal network devices are determined.

2. The network device optimization method as described in claim 1, characterized in that, The interference path analysis is performed on each network device in the first region to generate multiple first interference path analysis results, including: Configure a corresponding first code for each of the first regions, wherein the first code is unique; Based on the far-end interference reference signal RIM-RS, interference data is collected for each network device in the first area. Based on the interference data and the first encoding, the first interference path analysis result corresponding to each of the first regions is generated.

3. The network device optimization method as described in claim 1 or 2, characterized in that, Based on the analysis results of the multiple first interference pathways, the determined multiple second regions include: Based on the analysis results of the multiple first interference paths, the multiple network devices are re-divided into regions to determine the second region, wherein there are no interference paths between network devices in each of the second regions.

4. The network device optimization method as described in claim 2, characterized in that, The step of determining the network device code corresponding to each of the plurality of network devices based on the second region and the encoding strategy includes: Based on the encoding strategy, the first encoding corresponding to the first region is mapped to the second encoding corresponding to the second region, wherein the number of bits in the second encoding is less than the number of bits in the first encoding; Based on the second encoding, a corresponding network device encoding is determined for each of the plurality of network devices.

5. The network device optimization method according to any one of claims 1-4, characterized in that, The step of correcting the abnormal network device and determining the updated network device code of the abnormal network device includes: The interference path analysis is performed on the abnormal network device to generate the interference path analysis results of the abnormal network device; If the interference path analysis results of the abnormal network device meet the preset conditions, the updated network device code of the abnormal network device is determined.

6. A network device optimization apparatus, characterized in that, The device includes: The first partitioning module is used to partition multiple network devices into regions and generate multiple first regions; The first analysis module is used to perform interference path analysis on each network device in the first region and generate multiple first interference path analysis results. The second partitioning module is used to determine multiple second regions based on the analysis results of the multiple first interference pathways; The encoding mapping module is used to determine the network device encoding corresponding to each of the plurality of network devices based on the second region and the encoding strategy; The second analysis module is used to perform interference path analysis on the multiple network devices based on the network device coding, and generate a second interference path analysis result. An anomaly correction module is used to determine, based on preset conditions, the abnormal network device corresponding to the abnormal value in the second interference path analysis result, correct the abnormal network device, and determine the updated network device code of the abnormal network device.

7. The network device optimization apparatus as described in claim 6, characterized in that, The first analysis module includes: The first encoding unit is configured to configure a corresponding first code for each of the first regions, wherein the first code is unique; The data acquisition unit is used to acquire interference data for each network device in the first area based on the far-end interference reference signal RIM-RS. The first analysis unit is used to generate the first interference path analysis result corresponding to each of the first regions based on the interference data and the first encoding.

8. The network device optimization apparatus as described in claim 6 or 7, characterized in that, The second partitioning module includes: The second partitioning unit is used to re-partition the multiple network devices based on the analysis results of the multiple first interference paths, and determine the second region, wherein there are no interference paths between network devices in each of the second regions.

9. The network device optimization apparatus as described in claim 7, characterized in that, The encoding mapping module includes: An encoding mapping unit is used to map a first code corresponding to the first region to a second code corresponding to the second region based on an encoding strategy, wherein the number of bits in the second code is less than the number of bits in the first code; The second encoding unit is used to determine the network device code corresponding to each of the plurality of network devices based on the second encoding.

10. The network device optimization apparatus according to any one of claims 6-9, characterized in that, The anomaly correction module includes: An anomaly analysis unit is used to perform interference path analysis on the abnormal network device and generate interference path analysis results for the abnormal network device. The encoding update unit is used to determine the updated network device encoding of the abnormal network device when the interference path analysis result of the abnormal network device meets the preset conditions.

11. An electronic device, characterized in that, include: Memory, used to store computer-readable instructions; as well as A processor for executing the computer-readable instructions, causing the electronic device to perform the network device optimization method as described in any one of claims 1 to 5.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the network device optimization method according to any one of claims 1 to 5.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the network device optimization method as described in any one of claims 1 to 5.

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