CN-121984626-A - Repeater self-diagnosis optimization module and closed-loop control method thereof

CN121984626ACN 121984626 ACN121984626 ACN 121984626ACN-121984626-A

Abstract

The invention provides a self-diagnosis optimizing module of a repeater and a closed-loop control method thereof, wherein a signal acquisition module is connected with a radio frequency output end of the repeater through a directional coupler and used for coupling downlink output signals in real time and carrying out down-conversion and analog-to-digital conversion, a signal quality analysis module is connected with the signal acquisition module and used for analyzing signals, a rate test module is connected with the signal acquisition module and used for measuring data transmission rates of an uplink and a downlink, a control unit is used for receiving RSRP/SINR data of the signal quality analysis module and rate data of the rate test module, a data storage unit is used for storing preset RSRP threshold value, SINR threshold value, uplink rate threshold value, downlink rate threshold value and a parameter mapping table generated through machine learning pre-training, and a control unit is used for generating gain adjustment instructions, filtering optimization instructions and DPD coefficient updating instructions to form a closed-loop control link.

Inventors

XIE PENGYANG
CHEN JINQUAN
XU FUCHE
TAN JINSHENG
LIAO XIAOKANG
LI HUAGUI
CHEN QUNFENG
ZHANG JIANRONG

Assignees

中邮科通信技术股份有限公司

Dates

Publication Date: 20260505
Application Date: 20260207

Claims (10)

1. The repeater self-diagnosis optimizing module is characterized by comprising a control unit, a signal acquisition module, a signal quality analysis module, a rate test module, a parameter adjustment module and a data storage unit; The signal acquisition module is connected with the radio frequency output end of the repeater through a directional coupler and is used for coupling the downlink output signal in real time and performing down-conversion and analog-to-digital conversion; The signal quality analysis module is connected with the signal acquisition module and is used for analyzing the Reference Signal Received Power (RSRP) and the signal-to-interference-and-noise ratio (SINR) of the signals; the rate test module is connected with the signal acquisition module and is used for measuring the data transmission rates of an uplink and a downlink; The control unit is used for receiving the RSRP/SINR data of the signal quality analysis module and the rate data of the rate test module; the data storage unit stores a preset RSRP threshold, an SINR threshold, an uplink rate threshold, a downlink rate threshold and a parameter mapping table generated by machine learning pre-training; The control unit generates a gain adjustment instruction, a filtering optimization instruction and a DPD coefficient updating instruction, and enables the parameter adjustment module to form a closed-loop control link.
2. The repeater self-diagnosis optimizing module according to claim 1, wherein the control unit calculates the deviation amount and generates a performance deviation vector by comparing the RSRP/SINR/rate data with a preset threshold value, queries the parameter mapping table according to the performance deviation vector to generate a gain adjustment instruction, a filtering optimizing instruction and a DPD coefficient updating instruction, and issues the instructions to the parameter adjustment module, so that the parameter adjustment module forms a closed-loop control link.
3. The repeater self-diagnosis optimizing module according to claim 1, wherein the closed loop control link specifically comprises performing RSRP/SINR signal acquisition on the radio frequency output, performing RSRP/SINR analysis and rate test, and then enabling the control unit to generate a deviation vector and query a mapping table according to the analysis result and the test result.
4. The repeater self-diagnosis optimization module according to claim 3, wherein the closed loop control link specifically comprises: A gain control subunit for dynamically adjusting uplink and downlink gains; The filtering optimization subunit is used for optimizing out-of-band rejection parameters; A digital predistortion adjustment subunit for generating predistortion compensation coefficients; the parameter mapping table is used for establishing a mapping relation between a performance deviation vector and a parameter adjustment vector, the performance deviation vector comprises an RSRP deviation value, an SINR deviation value, an uplink rate deviation value and a downlink rate deviation value, and the parameter adjustment vector comprises a gain adjustment amount, a filtering parameter and a DPD coefficient.
5. The repeater self-diagnostic optimization module of claim 4, wherein said digital predistortion adjustment subunit comprises: the nonlinear characteristic analyzer is used for extracting an AM-AM/AM-PM characteristic curve based on the power amplifier output signal; a predistortion coefficient calculator for generating an inverse characteristic compensation coefficient based on the characteristic curve; the coefficient loader is used for loading the compensation coefficient into the baseband processing link; the compensation bandwidth of the DPD adjustment subunit is more than or equal to 100MHz; the data storage unit adopts a circulating storage structure, and periodically uses newly-added data to update the mapping table coefficients.
6. The repeater self-diagnosis optimizing module according to claim 4, wherein the procedure of updating DPD coefficients comprises the following steps; step a, collecting spectrum data of an output signal of a power amplifier; Step b, calculating nonlinear distortion degree; step c, inquiring a predistortion coefficient table to couple optimal compensation parameters in real time; step d, loading predistortion coefficients to a baseband processing link; Step e, verifying the distortion improving effect, and if the distortion improving effect does not reach the standard, carrying out iterative updating; In the step c, a predistortion coefficient table is stored in a data storage unit and comprises a baseband I/Q component compensation coefficient matrix; in step e, the iterative update uses a gradient descent algorithm.
7. The repeater self-diagnosis optimization module according to claim 4, wherein the data storage unit stores a preset RSRP threshold, SINR threshold, uplink rate threshold, downlink rate threshold, and a parameter map generated by machine learning pre-training.
8. The repeater self-diagnosis optimization module according to claim 4, wherein the parameter mapping table is generated by: step 1, collecting a historical data sample set, wherein samples of the historical data sample set comprise performance deviation vectors and corresponding optimal parameter adjustment vectors; step 2, training a multi-output regression model by adopting supervised learning, wherein the multi-output regression model takes a performance deviation vector as input and a parameter adjustment vector as output; and step 3, solidifying and storing the model parameters of the trained multi-output regression model as a parameter mapping table.
9. A closed loop control method of a repeater self-diagnosis optimizing module, which uses any one of claims 1,2,3, 4, 5,6, 7, 8, and is characterized by comprising the following steps; Step S1, coupling a radio frequency output signal of a repeater in real time through a directional coupler, and performing down-conversion processing on the coupled signal through a superheterodyne architecture, wherein the down-converted signal is subjected to digital processing through an ADC (analog-to-digital converter) to output a digital intermediate frequency signal; Step S2, the signal quality analysis module carries out arithmetic average on the power of the reference signal resource element RE of each sub-tone based on the 3GPPTS 36.214 standard, takes the average value of a plurality of continuous periods as the current RSRP value, adopts a formula of SINR=signal power/(interference power+noise power), The signal power is the average power of demodulation reference signals, the interference power is the signal power of the same-frequency adjacent cell, and the noise power is obtained through idle time slot measurement; the rate test module adopts UDP test packets to measure the rate, and the formula of the uplink rate to calculate the throughput is (total number of received packets is multiplied by packet length is multiplied by 8)/test duration; Measuring the downlink rate, namely adopting a calculation method which is the same as the uplink rate, and initiating a request to a base station by a repeater through a feedback link; Step S3, the control unit generates a performance deviation vector according to the measured data, and the deviation values of all parameters are calculated according to the following rules: The RSRP deviation value is defined as the difference between the actually measured RSRP value and a preset RSRP threshold value, wherein the preset RSRP threshold value is set according to a scene; SINR deviation value is defined as the difference between the measured SINR value and the preset SINR threshold value; the uplink rate deviation value is calculated according to the formula (actually measured uplink rate-uplink rate threshold)/uplink rate threshold multiplied by 100 percent; Calculating a downlink rate deviation value according to a formula (actually measured downlink rate-downlink rate threshold)/downlink rate threshold multiplied by 100 percent); s4, the control unit queries a parameter mapping table according to the performance deviation vector to generate an adjustment instruction; And the query strategy is to adopt accurate matching query when the absolute value of each deviation parameter is not more than 5%, and adopt K neighbor interpolation when any deviation exceeds the range, and take the weighted average value of a plurality of historical samples with nearest Euclidean distance as a parameter adjustment vector. The instruction priority mechanism is used for preferentially executing a DPD coefficient updating instruction if the DPD nonlinear error is not lower than 3%, executing a filtering optimization instruction if only the SINR deviation is not more than-2 dB, and executing a gain adjustment instruction if only the rate deviation is not more than-10% or the RSRP deviation is not more than-5 dBm. And S5, executing a parameter adjustment instruction.
10. The method for closed loop control of a repeater self-diagnostic optimization module of claim 9, wherein in step S5, the parameter adjustment module executes the parameter adjustment command in the following manner: The gain control subunit outputs 0-3.3V control voltage through the DAC, and verifies the gain standard through the signal acquisition module; The filtering optimization subunit dynamically adjusts the capacitance value of the SAW filter matching circuit, measures an out-of-band rejection ratio once every time the preset quantity is adjusted, and reaches a target value; A DPD adjustment subunit, which is used for caching the current predistortion coefficient, loading a new coefficient to the baseband FPGA, and monitoring an AM-AM/AM-PM curve through a nonlinear characteristic analyzer, and storing the new coefficient if the nonlinear error after adjustment is not more than 1 percent; Step S5 is followed by step S6 of waiting for a control period of a preset duration and repeating steps S1 to S5 until one of the following termination conditions is met: The performance reaches the standard that in 3 continuous control periods (30 ms), the RSRP deviation is in the interval of [ -3dBm, +3dBm ], the SINR deviation is in the interval of [ -2dB, +2dB ], and the uplink and downlink rate deviation is in the interval of [ -5% ] and +5% ]; and (3) abnormal termination, namely triggering an alarm when the iteration times reach the preset times and still reach the standard, reporting a fault code through the communication module, and simultaneously automatically switching to a safety mode.

Description

Repeater self-diagnosis optimization module and closed-loop control method thereof Technical Field The invention relates to the technical field of mobile communication, in particular to a repeater self-diagnosis optimization module and a closed-loop control method thereof. Background With the large-scale deployment of the 5G network, the repeater serves as key equipment for expanding the coverage of the base station, and plays an important role in the scenes of indoor deep coverage, tunnel communication and the like. However, the existing repeater faces the following technical bottlenecks in practical application: 1. parameter rigidification, namely a fixed gain strategy cannot dynamically adapt to channel variation, so that RSRP/SINR of an edge area is suddenly reduced; 2. the distortion correction is slow, namely the nonlinear distortion of the power amplifier depends on offline DPD calibration (> 100 ms), the service is required to be interrupted, and the real-time change cannot be tracked; 3. the gain control, the filter suppression and the DPD compensation are independently adjusted due to the lack of coordination, and a linkage mechanism is absent; the existing solution has the defect that the threshold of the scheme 1 triggers gain adjustment, and only responds to the RSRP threshold to cause oscillation (such as over-high gain, increased interference and deteriorated SINR). Offline DPD calibration is prone to service interruption, cannot compensate temperature drift in real time, but adjusting parameters by using a preset rule base is not flexible enough, and is difficult to cover complex interference scenes. Disclosure of Invention The invention provides a repeater self-diagnosis optimization module and a closed-loop control method thereof, which can realize millisecond-level self-adaptive optimization of repeater equipment in a dynamic environment. The invention adopts the following technical scheme. A repeater self-diagnosis optimizing module comprises a control unit, a signal acquisition module, a signal quality analysis module, a rate test module, a parameter adjustment module and a data storage unit; The signal acquisition module is connected with the radio frequency output end of the repeater through a directional coupler and is used for coupling the downlink output signal in real time and performing down-conversion and analog-to-digital conversion (ADC); the signal quality analysis module is connected with the signal acquisition module and is used for analyzing Reference Signal Received Power (RSRP) and signal-to-interference-and-noise ratio (SINR) of the signals; the rate test module is connected with the signal acquisition module and is used for measuring the data transmission rates of an uplink and a downlink; the control unit adopts an ARM processor and is used for receiving the RSRP/SINR data of the signal quality analysis module and the rate data of the rate test module; the data storage unit stores a preset RSRP threshold, an SINR threshold, an uplink rate threshold, a downlink rate threshold and a parameter mapping table generated by machine learning pre-training; The control unit generates a gain adjustment instruction, a filtering optimization instruction and a DPD coefficient updating instruction, and enables the parameter adjustment module to form a closed-loop control link. The control unit calculates the deviation amount and generates a performance deviation vector by comparing the RSRP/SINR/rate data with a preset threshold value, queries the parameter mapping table according to the performance deviation vector to generate a gain adjustment instruction, a filtering optimization instruction and a DPD coefficient updating instruction, and issues the instructions to the parameter adjustment module, so that the parameter adjustment module forms a closed-loop control link. The closed loop control link specifically comprises the steps of carrying out RSRP/SINR signal acquisition on radio frequency output, carrying out RSRP/SINR analysis and rate test, enabling a control unit to generate a deviation vector and query a mapping table according to an analysis result and a test result, namely, radio frequency output, signal acquisition, RSRP/SINR analysis and rate test, enabling the control unit to generate the deviation vector and query the mapping table, enabling a parameter adjustment module to execute gain/filtering/DPD adjustment, and carrying out radio frequency signal output after adjustment. The closed loop control link specifically comprises the following components: A gain control subunit for dynamically adjusting uplink and downlink gains; The filtering optimization subunit is used for optimizing out-of-band rejection parameters; a Digital Predistortion (DPD) adjustment subunit for generating predistortion compensation coefficients; The parameter mapping table is used for establishing a mapping relation between a performance deviation vector and a parameter adjustment vector, w