Abnormal neighbor cell identification method, neighbor cell measurement optimization method, and mobile terminal

Abstract

This invention provides a method for identifying abnormal neighboring cells, a method for optimizing neighboring cell measurement, and a mobile terminal. The method includes: acquiring the cell signal quality of a neighboring cell; determining a first deduction score based on the difference between the neighboring cell's cell signal quality and the serving cell's cell signal quality; evaluating the fluctuation amplitude of the neighboring cell's cell signal based on its cell signal quality, and determining a second deduction score based on the fluctuation amplitude; determining a health score for the neighboring cell based on the first and second deduction scores; and determining whether the neighboring cell is abnormal based on its health score. This invention can improve the accuracy of identifying abnormal neighboring cells, avoid terminal switching to abnormal neighboring cells, improve the reliability of terminal switching, and reduce the terminal's measurement power consumption and air interface overhead.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and more particularly to a method for identifying abnormal neighboring cells, a method for optimizing neighboring cell measurement, and a mobile terminal. Background Technology

[0002] In LTE / NR communication systems, when a terminal is in connected mode, it measures the surrounding neighboring cells. If the signal measurement value of a neighboring cell continuously meets the event reporting trigger threshold for a certain period of time, the terminal will report the neighboring cell measurement value to the network. The network then decides whether to allow the terminal to switch over based on the reported measurement value.

[0003] Due to the complex network environment of base stations, terminals often detect abnormal cells, such as cells with abnormal signals, incomplete system message broadcasts, or "poor" historical performance. These cells can lead to wasted terminal measurement resources and cell handover failures.

[0004] Therefore, it is necessary to improve the accuracy of identifying such "abnormal neighboring cells" based on existing technologies, thereby optimizing the measurement of neighboring cells and improving the reliability of cell handover. Summary of the Invention

[0005] This invention provides a method for identifying abnormal neighbor cells, a method for optimizing neighbor cell measurement, and a mobile terminal, which can improve the accuracy of identifying abnormal neighbor cells, thereby optimizing neighbor cell measurement and improving the reliability of cell handover.

[0006] The technical solution provided by this invention is as follows:

[0007] In a first aspect, this application provides a method for identifying abnormal neighboring cells, comprising: acquiring the cell signal quality of the neighboring cells; the cell signal quality includes at least one of the following: reference signal received power RSRP, reference signal received quality RSRQ, and signal-to-noise ratio SINR;

[0008] The first deduction point affecting the health of the neighboring cell is determined based on the difference between the signal quality of the neighboring cell and the signal quality of the serving cell.

[0009] The signal fluctuation amplitude of neighboring cells is assessed based on the signal quality of neighboring cells, and a second deduction point affecting the health of neighboring cells is determined based on the signal fluctuation amplitude.

[0010] The health score of the neighboring area is determined based on the first deduction score and the second deduction score;

[0011] Determine whether a neighboring area is abnormal based on its health score.

[0012] In some implementations, the amplitude of cell signal fluctuations in neighboring cells is assessed based on the cell signal quality of neighboring cells, including:

[0013] Calculate the standard deviation of the neighboring cell's signal quality over a recent period and use it as the amplitude of the neighboring cell's signal fluctuation.

[0014] In some implementations, before determining the health score of the neighboring area based on the first deduction score and the second deduction score, the method further includes:

[0015] Obtain the decoding failure rate of the Physical Downlink Control Channel (PDCCH) of the neighboring cell, and determine the third deduction score that affects the health of the neighboring cell based on the decoding failure rate;

[0016] The health score of the neighboring area is determined based on the first deduction score and the second deduction score, including: determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the third deduction score.

[0017] In some implementations, before determining the health score of the neighboring area based on the first deduction score and the second deduction score, the method further includes:

[0018] Obtain frequency information from surrounding neighboring cells;

[0019] Based on the frequency information of the surrounding neighboring cells and the frequency information of the serving cell, determine whether there are cells with the same frequency as the neighboring cells in the serving cell and other surrounding neighboring cells;

[0020] If there is a cell with the same frequency as the neighboring cell, and the neighboring cell has met the triggering conditions for event reporting, then the fourth deduction point affecting the health of the neighboring cell will be determined based on the potential co-frequency interference of the neighboring cell.

[0021] The health score of the neighboring area is determined based on the first deduction score and the second deduction score, including: determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the fourth deduction score.

[0022] In some implementations, a fourth deduction point affecting the health of neighboring cells is determined based on potential co-channel interference from neighboring cells, including:

[0023] The fourth deduction point is determined based on the difference between the signal quality of the neighboring cell and the signal quality of the cell on the same frequency.

[0024] In some implementations, before determining the health score of the neighboring area based on the first deduction score and the second deduction score, the method further includes:

[0025] If the neighboring cell has met the triggering conditions for event reporting, then attempt to receive system messages from the neighboring cell;

[0026] The fifth deduction point affecting the health of the neighboring area is determined based on the reception of system messages in the neighboring area;

[0027] The health score of the neighboring area is determined based on the first deduction score and the second deduction score, including: determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the fifth deduction score.

[0028] In some implementations, determining whether a neighboring cell is abnormal based on its health score includes:

[0029] If the health score of a neighboring cell is less than the first threshold, the neighboring cell is judged to be the first abnormal cell.

[0030] If the health score of a neighboring cell is not less than the first threshold but less than the second threshold, then the neighboring cell is judged to be the second abnormal cell, where the second threshold is greater than the first threshold;

[0031] If the health score of a neighboring cell is not less than the second threshold but less than the third threshold, then the neighboring cell is judged to be a third abnormal cell, where the third threshold is greater than the second threshold.

[0032] Secondly, this application also provides a neighbor cell measurement optimization method, applied to a mobile terminal, comprising:

[0033] The first method for identifying abnormal neighboring cells is used to identify abnormal neighboring cells; if the neighboring cell is judged to be abnormal based on its health score, then the measurement of the neighboring cell is penalized.

[0034] In some implementations, penalizing measurements from neighboring cells includes:

[0035] If a neighboring cell is the first abnormal cell, then the neighboring cell will be added to the blacklist. The blacklist is used to prohibit the corresponding cell from being measured within a preset time.

[0036] If the neighboring cell is the second abnormal cell, then the event trigger threshold of the neighboring cell is increased, and / or the measurement period is extended;

[0037] If a neighboring cell is the third abnormal cell, then the candidate level of the neighboring cell is lowered.

[0038] Thirdly, this application also provides a mobile terminal, including: a memory for storing a computer program; and a processor for implementing the neighbor cell measurement optimization method described in the second aspect when running the computer program.

[0039] The present invention provides a method for identifying abnormal neighbor cells, an optimized method for neighbor cell measurement, and a mobile terminal, which can bring at least the following beneficial effects: The present invention evaluates the risk of switching to a neighbor cell from different dimensions, and sets a deduction score for each dimension that affects the health of the neighbor cell. By combining the deduction scores of each dimension, a health score for the neighbor cell is obtained; then, the health score of the neighbor cell is used to determine whether the neighbor cell is abnormal. By comprehensively analyzing multiple dimensions, the accuracy of abnormal neighbor cell detection is improved, and the omission of abnormal neighbor cells is reduced; furthermore, by imposing corresponding penalties on the measurement of abnormal neighbor cells, the power consumption of terminal measurement and air interface overhead are reduced, thereby improving the reliability of terminal handover. Attached Figure Description

[0040] The preferred embodiments will be described below in a clear and easy-to-understand manner, with reference to the accompanying drawings, to further explain the above-mentioned characteristics, technical features, advantages, and implementation methods of an abnormal neighboring cell identification method, a neighboring cell measurement optimization method, and a mobile terminal.

[0041] Figure 1 This is a flowchart of an embodiment of a method for identifying abnormal neighboring regions according to the present invention;

[0042] Figure 2 This is a flowchart of an embodiment of a neighbor cell measurement optimization method of the present invention;

[0043] Figure 3 This is a schematic diagram of the structure of an embodiment of a mobile terminal according to the present invention. Detailed Implementation

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without any creative effort.

[0045] To keep the drawings concise, only the parts relevant to the invention are shown schematically in each figure, and they do not represent the actual structure of the product. Furthermore, for ease of understanding, in some figures, components with the same structure or function are shown only schematically, or only one is labeled. In this document, "a" can mean not only "only one" but also "more than one".

[0046] In LTE / NR communication systems, when a terminal is in connected mode, it measures the surrounding neighboring cells. If the signal measurement value of a neighboring cell continuously meets the event reporting trigger threshold for a certain period of time, the terminal will report the neighboring cell measurement value to the network. The network then decides whether to allow the terminal to switch over based on the reported measurement value.

[0047] Due to the complex network environment of base stations, terminals often detect abnormal cells, such as cells with abnormal signals, incomplete system message broadcasts, or "poor" historical performance. These cells can lead to wasted terminal measurement resources and cell handover failures.

[0048] To address this, the present invention evaluates the risk of switching to a neighboring cell from different dimensions. Each dimension corresponds to a deduction score that affects the health of the neighboring cell; the higher the risk, the higher the deduction score. The overall health score of the neighboring cell is then calculated by combining the deduction scores from each dimension. Finally, the health score of the neighboring cell is used to determine whether the neighboring cell is abnormal.

[0049] The above dimensions include the cell signal quality of neighboring cells, the DCI decoding failure rate of the physical layer control channel (PDCCH), the interference between neighboring cells on the same frequency, the stability of cell signal quality, the decoding status of system messages, and historical camping records. Any combination of these dimensions can be selected according to actual needs.

[0050] Because it integrates analysis from various dimensions, it can improve the accuracy of abnormal neighbor detection and reduce the omission of abnormal neighbor areas.

[0051] Furthermore, by imposing appropriate penalties on measurements of abnormal neighboring cells, terminal measurement power consumption and air interface overhead can be reduced, thereby improving the reliability of terminal handover.

[0052] The above technical concept will be explained in detail below with reference to the embodiments.

[0053] One embodiment of the present invention, such as Figure 1 As shown, a method for identifying abnormal neighboring regions includes:

[0054] Step S100: Obtain the cell signal quality of neighboring cells.

[0055] Cell signal quality can be characterized by one or more of the following: Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal-to-Noise Ratio (SINR).

[0056] When a mobile terminal is in connected mode, it needs to measure neighboring cells. By measuring neighboring cells, the RSRP, RSRQ, and SINR of the neighboring cells can be obtained.

[0057] Step S200 determines the first deduction score affecting the health of the neighboring cell based on the difference between the signal quality of the neighboring cell and the signal quality of the serving cell.

[0058] For example, if the signal quality of a cell is measured using RSRP (Residual Signal Ratio), the difference Δ is obtained by subtracting the RSRP of the serving cell from the RSRP of the neighboring cell. If the difference Δ >= -3dB, it indicates that the signal quality of the neighboring cell is acceptable, and the risk of switching to the neighboring cell is low; therefore, the first deduction score W1 = 0 is set. If the difference Δ < -3dB, it indicates that the signal quality of the neighboring cell is low and there are too many serving cells; therefore, switching to it is not recommended; therefore, the first deduction score W1 = 20 is set. The above values ​​are for illustrative purposes only and can be adjusted according to the actual scenario.

[0059] Step S300 determines the second deduction point that affects the health of the neighboring cell based on the fluctuation amplitude of the neighboring cell signal.

[0060] The signal fluctuation amplitude of neighboring cells can be assessed based on their signal quality. For example, the standard deviation σ of the neighboring cell's signal quality over a recent period T1 can be calculated and used as the signal fluctuation amplitude of the neighboring cell. The standard deviation σ can be calculated continuously using a sliding window method.

[0061] For example, if σ > 3, it indicates that the signal is slightly unstable and is judged as low risk, and the second deduction score W2 = 15 is set; if σ > 6, it indicates that the signal is moderately unstable and is judged as medium risk, and the second deduction score W2 = 30 is set; if σ > 9, it indicates that the signal is severely unstable and is judged as high risk, and the second deduction score W2 = 100 is set.

[0062] Step S400 determines the health score of the neighboring area based on the first deduction score and the second deduction score.

[0063] One approach is to assign a maximum health score to a neighboring area if all aspects of the neighboring area are normal. The neighboring area's health score = maximum score - first deduction score - second deduction score. For example, if the maximum score is 100, the first deduction score is 20, and the second deduction score is 40, then the neighboring area's health score = 100 - 20 - 40 = 60.

[0064] Another approach is to set the health score as: full score - w1 * first deduction score - w2 * second deduction score, where w1 and w2 are the weights of the corresponding dimensions. The weights can be set according to the importance of each dimension, thus increasing the weight of important dimensions.

[0065] Step S500 determines whether a neighboring cell is abnormal based on its health score.

[0066] For example, if the health score of a neighboring area is less than a threshold, then that neighboring area is abnormal; otherwise, it is normal.

[0067] One implementation method is as follows: if the health score of a neighboring cell is less than a first threshold, the neighboring cell is determined to be a first abnormal cell; if the health score of a neighboring cell is not less than the first threshold, but less than a second threshold, the neighboring cell is determined to be a second abnormal cell, wherein the second threshold is greater than the first threshold.

[0068] For example, if the health score of a neighboring cell is less than 20 (the first threshold), it is considered the first abnormal cell; if the health score of a neighboring cell is less than or equal to 20 and less than 50 (the second threshold), it is considered the second abnormal cell; if the health score of a neighboring cell is greater than or equal to 50, it is considered a normal cell.

[0069] In this embodiment, the risk of switching to a neighboring cell is evaluated from two dimensions: the signal quality of the neighboring cell and the stability of the signal quality of the neighboring cell. The corresponding deduction score is determined, and then the health score of the neighboring cell is determined by combining the deduction scores of the two dimensions. The health score of the neighboring cell is used to determine whether the neighboring cell is abnormal. Compared with the identification of a single dimension, the accuracy of identifying abnormal neighboring cells can be improved.

[0070] In one embodiment, the method further includes the following step prior to step S400:

[0071] Step S310 obtains the decoding failure rate of the physical downlink control channel (PDCCH) of the neighboring cell, and determines the third deduction score W3 that affects the health of the neighboring cell based on the decoding failure rate.

[0072] Step S400 includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the third deduction score.

[0073] Specifically, when a mobile terminal measures neighboring cells in connected mode, it performs restricted blind detection on the PDCCH of neighboring cells during measurement intervals or dedicated probe time slots. It attempts to decode the downlink control information (DCI) carried by the PDCCH using temporary radio network identifiers (RNTIs) such as random access radio network identifiers (RA-RNTI, paging radio network identifiers (P-RNTI), and system message radio network identifiers (SI-RNTI). If decoding fails, there is a risk of downlink data loss or service interruption on that cell.

[0074] The DCI decoding failure rate of neighboring cells over a period of time T2 is statistically analyzed, and the cell risk level is determined based on the decoding failure rate.

[0075] For example, a DCI decoding failure rate of 0-10% is considered low risk, so W3 = 10;

[0076] The DCI decoding failure rate (11 ~ 40%) is classified as medium risk, W3 = 30;

[0077] The DCI decoding failure rate (41 ~ 100%) is considered high risk, and W3 = 100.

[0078] Health Score = Full Score - First Deduction Score - Second Deduction Score - Third Deduction Score.

[0079] In one embodiment, prior to step S400:

[0080] Step S321: Obtain frequency information of surrounding neighboring cells;

[0081] Step S322: Based on the frequency information of the surrounding neighboring cells and the frequency information of the serving cell, determine whether there are any cells with the same frequency as the neighboring cells among the serving cell and other surrounding neighboring cells.

[0082] If, in step S323, there exists a cell with the same frequency as the neighboring cell, and the neighboring cell has met the triggering conditions for event reporting, then the fourth deduction point W4 affecting the health of the neighboring cell is determined based on the potential co-channel interference of the neighboring cell.

[0083] The fourth deduction point W4 can be determined based on the difference between the signal quality of the neighboring cell and the signal quality of the cell with the same frequency.

[0084] Step S400 includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the fourth deduction score.

[0085] For example: Health Score = Full Score - First Deduction Score - Second Deduction Score - Fourth Deduction Score.

[0086] In one embodiment, prior to step S400:

[0087] If the neighboring cell has met the triggering conditions for event reporting, then attempt to receive system messages from the neighboring cell in step S330.

[0088] Step S331 determines the fifth deduction point W5 that affects the health of the neighboring cell based on the reception of system messages from the neighboring cell.

[0089] System messages include the main message block (MIB), SIB1, and SIB2. System messages from neighboring cells may be received successfully or may fail to be received. System message reception failures include, but are not limited to: reaching the maximum number of reception attempts, system message reception timeout, system message verification error, and system message decoding failure.

[0090] If the failure to receive system messages is considered a high risk, and the neighboring cell is no longer considered in the next T2 time period, then the fifth deduction score W5 = 100 (the maximum health score = 100) can be set.

[0091] If the system message is successfully received, and the risk of switching to that neighboring cell is considered low, then W5=0 is set.

[0092] In some embodiments, when the system message is successfully received, the basic information of the cell, such as PLMN and TAC, is further checked. The basic information of the cell can be used to check whether the neighboring cell is a fake base station cell. If it is a fake base station cell, the risk of switching to the neighboring cell is high, so W5 can be set to 100.

[0093] Step S400 includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the fifth deduction score. For example, health score = full score - first deduction score - second deduction score - fifth deduction score.

[0094] In one embodiment, prior to step S400:

[0095] Step S340 determines the sixth deduction point W6 that affects the health of the neighboring area based on the historical residence data of the neighboring area.

[0096] For example, check the historical dwell time of neighboring cells within the most recent T3 time period to see if there are any connection establishment failures or abnormal network disconnections. If so, and the current signal quality of the neighboring cell has not significantly improved compared to the time of the problem, the improvement standard can be determined by the UE based on the historical signal quality change trend. For example, if the measurement value does not improve by more than a preset dB value for M consecutive times, it is judged as medium risk, and the sixth deduction score W6 = 20 is set.

[0097] Step S400 includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the sixth deduction score. For example: Health score = Full score - First deduction score - Second deduction score - Sixth deduction score.

[0098] In one embodiment, prior to step S400:

[0099] Step S310: Obtain the decoding failure rate of the physical downlink control channel (PDCCH) of the neighboring cell, and determine the third deduction score W3 that affects the health of the neighboring cell based on the decoding failure rate;

[0100] Step S321: Obtain frequency information of surrounding neighboring cells;

[0101] Step S322: Based on the frequency information of the surrounding neighboring cells and the frequency information of the serving cell, determine whether there are any cells with the same frequency as the neighboring cells among the serving cell and other surrounding neighboring cells.

[0102] If there is a cell with the same frequency as the neighboring cell in step S323, and the neighboring cell has met the triggering conditions for event reporting, then the fourth deduction score W4 affecting the health of the neighboring cell is determined based on the potential co-channel interference of the neighboring cell.

[0103] If the neighboring cell has met the triggering conditions for event reporting, then attempt to receive system messages from the neighboring cell in step S330.

[0104] Step S331 determines the fifth deduction point W5 that affects the health of the neighboring cell based on the reception of system messages from the neighboring cell;

[0105] Step S340 determines the sixth deduction point W6 that affects the health of the neighboring area based on the historical residence data of the neighboring area.

[0106] Step S400 includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, the third deduction score, the fourth deduction score, the fifth deduction score, and the sixth deduction score.

[0107] Alternatively, several deduction scores from the first to the sixth can be selected and combined according to certain principles, such as deduction scores with high probability of occurrence or significant impact. This can reduce the consumption of terminal resources. The selected deduction scores are determined based on air interface physical conditions, historical dwell times, etc., and then the health score of neighboring cells is determined based on the selected deduction scores.

[0108] In one embodiment, step S500 includes:

[0109] If the health score of a neighboring cell is less than the first threshold, the neighboring cell is judged to be the first abnormal cell.

[0110] If the health score of a neighboring cell is not less than the first threshold but less than the second threshold, then the neighboring cell is judged to be the second abnormal cell, where the second threshold is greater than the first threshold;

[0111] If the health score of a neighboring cell is not less than the second threshold but less than the third threshold, then the neighboring cell is judged to be a third abnormal cell, where the third threshold is greater than the second threshold.

[0112] One embodiment of the present invention, such as Figure 2 As shown, a neighbor cell measurement optimization method, applied to a mobile terminal, includes:

[0113] Step S10 uses the abnormal neighbor identification method described in any of the foregoing embodiments to identify abnormal neighbor cells;

[0114] If a neighboring cell is determined to be abnormal based on its health score in step S20, then the measurement of the abnormal neighboring cell will be penalized.

[0115] Penalty measures include, but are not limited to, at least one of the following: adding to a blacklist, raising the event trigger threshold for neighboring cells, extending the measurement cycle, and lowering the candidate level of neighboring cells. The blacklist is used to prohibit the corresponding cell from being measured within a preset time period.

[0116] In one embodiment, step S20 includes:

[0117] If a neighboring cell is the first abnormal cell, then the neighboring cell will be added to the blacklist. The blacklist is used to prohibit the corresponding cell from being measured within a preset time.

[0118] If the neighboring cell is the second abnormal cell, then the event trigger threshold of the neighboring cell is increased, and / or the measurement period is extended.

[0119] In one embodiment, step S20 includes:

[0120] If a neighboring cell is the first abnormal cell, then the neighboring cell will be added to the blacklist. The blacklist is used to prohibit the corresponding cell from being measured within a preset time.

[0121] If the neighboring cell is the second abnormal cell, then the event trigger threshold of the neighboring cell is increased, and / or the measurement period is extended;

[0122] If a neighboring cell is the third abnormal cell, then the candidate level of the neighboring cell is lowered.

[0123] One embodiment of the present invention, such as Figure 3 As shown, a mobile terminal includes:

[0124] Memory 10 is used to store computer program 20;

[0125] The processor 30 is used to implement the neighbor cell measurement optimization method described in any of the foregoing embodiments when running the computer program 20.

[0126] The memory 10 can be any internal storage unit and / or external storage device capable of storing data and programs. For example, the memory 10 can be a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD card), or a flash memory card.

[0127] Depending on the requirements, the processor 30 may be a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a general-purpose processor, or other logic devices.

[0128] It should be noted that the above embodiments can be freely combined as needed. The above are merely preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for identifying abnormal neighboring cells, applied to a mobile terminal, characterized in that, include: The cell signal quality of the neighboring cell is obtained by measuring the neighboring cell; the cell signal quality includes at least one of the following: Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal-to-Noise Ratio (SINR); The first deduction score affecting the health of the neighboring cell is determined based on the difference between the cell signal quality of the neighboring cell and the cell signal quality of the serving cell. The fluctuation range of the cell signal in the neighboring cell is evaluated based on the cell signal quality of the neighboring cell, and a second deduction score affecting the health of the neighboring cell is determined based on the fluctuation range of the cell signal. By performing restricted blind detection on the PDCCH of the neighboring cell during the measurement gap or dedicated detection time slot when measuring the neighboring cell in the connected state, the decoding failure rate of the physical downlink control channel (PDCCH) of the neighboring cell is obtained, and a third deduction score affecting the health of the neighboring cell is determined based on the decoding failure rate. The health score of the neighboring area is determined based on the first deduction score, the second deduction score, and the third deduction score; The health score of the neighboring cells is used to determine whether the neighboring cells are abnormal, so that the measurement of abnormal neighboring cells can be penalized.

2. The method of identifying an abnormal neighboring cell according to claim 1, wherein, The step of evaluating the cell signal fluctuation amplitude of the neighboring cells based on the cell signal quality of the neighboring cells includes: Calculate the standard deviation of the cell signal quality of the neighboring cell over a recent period and use it as the cell signal fluctuation amplitude of the neighboring cell.

3. The method for identifying abnormal neighboring regions according to claim 1, characterized in that, Before determining the health score of the neighboring regions, the following steps are also included: The sixth deduction point affecting the health of the neighboring area is determined based on the historical residency situation of the neighboring area. The step of determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the third deduction score includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, the third deduction score, and the sixth deduction score.

4. The method for identifying abnormal neighboring regions according to claim 1, characterized in that, Before determining the health score of the neighboring regions, the following steps are also included: Obtain frequency information from surrounding neighboring cells; Based on the frequency information of the surrounding neighboring cells and the frequency information of the serving cell, determine whether there are any cells with the same frequency as the serving cell and other surrounding neighboring cells; If there is a cell with the same frequency as the neighboring cell, and the neighboring cell has met the triggering conditions for event reporting, then the fourth deduction point affecting the health of the neighboring cell is determined based on the potential co-frequency interference of the neighboring cell. Determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the third deduction score includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, the third deduction score, and the fourth deduction score.

5. The method for identifying abnormal neighboring regions according to claim 4, characterized in that, The determination of the fourth deduction point affecting the health of neighboring cells based on potential co-channel interference from neighboring cells includes: The fourth deduction score is determined based on the difference between the cell signal quality of the neighboring cell and the cell signal quality of its co-frequency cell.

6. The method for identifying abnormal neighboring regions according to claim 1, characterized in that, Before determining the health score of the neighboring regions, the following steps are also included: If the neighboring cell has met the event reporting triggering conditions, then attempt to receive the system message from the neighboring cell; The fifth deduction point affecting the health of the neighboring cell is determined based on the reception of system messages in the neighboring cell; The step of determining the health score of the neighboring area based on the first deduction score, the second deduction score, and the third deduction score includes: determining the health score of the neighboring area based on the first deduction score, the second deduction score, the third deduction score, and the fifth deduction score.

7. The method for identifying abnormal neighboring regions according to claim 1, characterized in that, The step of determining whether a neighboring region is abnormal based on its health score includes: If the health score of the neighboring cell is less than the first threshold, then the neighboring cell is determined to be the first abnormal cell; If the health score of the neighboring cell is not less than the first threshold but less than the second threshold, then the neighboring cell is determined to be a second abnormal cell, wherein the second threshold is greater than the first threshold; If the health score of the neighboring cell is not less than the second threshold but less than the third threshold, then the neighboring cell is determined to be a third abnormal cell, wherein the third threshold is greater than the second threshold.

8. A neighboring cell measurement optimization method, characterized in that, Applied to mobile terminals, including: The method for identifying abnormal neighboring regions as described in any one of claims 1 to 7 is used to identify abnormal neighboring regions. If a neighboring cell is determined to be abnormal based on its health score, then the measurement of that neighboring cell will be penalized.

9. The neighbor cell measurement optimization method according to claim 8, characterized in that, The penalty applied to the measurement of the neighboring cell includes: If the neighboring cell is the first abnormal cell, then the neighboring cell is added to the blacklist, and the blacklist is used to prohibit the corresponding cell from being measured within a preset time. If the neighboring cell is the second abnormal cell, then the event trigger threshold of the neighboring cell is increased, and / or the measurement period is extended; If the neighboring cell is the third abnormal cell, then the candidate level of the neighboring cell is reduced.

10. A mobile terminal, characterized in that, include: Memory, used to store computer programs; A processor for implementing the neighbor cell measurement optimization method as described in claim 8 or 9 when running the computer program.

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