Uplink subsystem complexity reduction method based on PCMA technology

Abstract

The invention discloses an uplink subsystem complexity reduction method based on a PCMA technology, and relates to the technical field of high-capacity wireless transmission system design and complexity control, and the method comprises the following steps: collecting uplink signal parameters through spectrum analysis, bit error rate test and MIMO detection, obtaining channel characteristics through a pilot frequency and a Gray sequence, and obtaining the complexity of a high-capacity wireless transmission system; baseband data are generated, scene features are extracted, Wiener filtering and iterative soft decision feedback algorithms are adopted to optimize filtering and coding, channel and coding performance is evaluated, transmission strategies are dynamically adjusted through a gigabit network interface, clocks are unified, synchronization is optimized, and the complexity of a PCMA uplink system is reduced. The complexity of an uplink subsystem is effectively reduced through the PCMA technology, the efficiency and the stability of a high-capacity wireless transmission system are improved, efficient utilization of resources and improvement of synchronization precision are achieved by accurately collecting signal parameters, optimizing filtering and coding and dynamically adjusting a transmission strategy, and the method is suitable for large-scale popularization and application. And powerful support is provided for the development of a wireless communication system.

Description

Technical Field

[0001] The present invention relates to the technical field of high-capacity wireless transmission system design and complexity control, and in particular to a method for reducing the complexity of an uplink subsystem based on PCMA technology. Background Art

[0002] The uplink subsystem is a critical communications component, primarily referring to the physical path through which signals are transmitted from mobile stations to base stations or the network. In mobile communications systems, the uplink subsystem is responsible for transmitting data, signals, and control information generated by user equipment (UE) to the base station or core network. This system involves multiple technical factors, such as handset transmit power, antenna gain, path loss, and base station receiver sensitivity, all of which collectively impact the quality and performance of the uplink. Furthermore, the uplink subsystem employs a range of advanced technologies to optimize data transmission, such as adaptive modulation and coding, OFDMA, MIMO, and power control. These technologies enable the uplink to adapt to varying signal quality and interference environments, thereby improving data transmission efficiency and reliability. In summary, the uplink subsystem is a crucial component for enabling two-way communication in mobile communications systems, and optimizing its performance is crucial for improving overall communication quality.

[0003] To address the increased complexity of traditional uplink subsystems in high data rates, multiple antennas, and complex channel environments, existing technologies primarily address this by adding signal processing algorithms and optimizing hardware design. While these approaches improve the system's data processing capabilities and stability to a certain extent, they still lead to increased processing latency and power consumption under high loads. This is because as data rates increase and the number of antennas increases, traditional algorithms and hardware designs become inadequate for processing large amounts of data and multi-dimensional signals, leading to a decline in overall system performance and a compromised user experience. Therefore, to more effectively address this challenge, a method for reducing uplink subsystem complexity based on PCMA technology has been proposed. Summary of the Invention

[0004] The present invention aims to provide a method for reducing the complexity of an uplink subsystem based on PCMA technology to solve the problems raised in the above background technology.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is: a method for reducing the complexity of an uplink subsystem based on PCMA technology, comprising the following steps:

[0006] S1. Use a spectrum analyzer to collect uplink signal bandwidth, spectrum distribution, and single-channel bandwidth data. Use a bit error rate test program to collect receiving end bit error rate data. Use MIMO detection to collect the signal-to-noise ratio parameters of pilot symbols and data symbols in real time. Use pilot sequences and Golay complementary sequences to collect the channel response, delay, and frequency offset parameters of the asymmetric PCMA system.

[0007] S2. Generate raw baseband data through phase shifter and multipath delay simulation, remove DC offset and baseline drift, and classify and extract scene features;

[0008] S3: Adopt the Wiener filter algorithm, dynamically optimize the filter parameters based on the scene characteristics, use the pilot-assisted iterative soft decision feedback algorithm, select the feedback strategy based on the scene characteristics, apply turbo codes and low-density parity-check codes, and allocate coding resources based on the scene requirements;

[0009] S4. Compare the channel estimation performance in different scenarios by calculating the normalized mean square error and calculate the extreme performance of the coding scheme in different scenarios;

[0010] S5. Through the Gigabit Ethernet interface, the transmission strategy is dynamically adjusted based on the scenario characteristics. Based on the clock source configuration, the frequency and sampling clock of the transmitting and receiving ends are unified, and the synchronization mechanism is optimized according to the scenario characteristics.

[0011] A further improvement of the technical solution of the present invention is that: in S1, the process of collecting uplink signal bandwidth, spectrum distribution, and single-channel bandwidth data using a spectrum analyzer, collecting receiving end bit error rate data using a bit error rate test program, collecting signal-to-noise ratio parameters of pilot symbols and data symbols in real time through MIMO detection, and collecting channel response, delay, and frequency offset parameters of an asymmetric PCMA system using a pilot sequence and a Golay complementary sequence includes the following steps:

[0012] Deploy spectrum analyzers at the RF module output ports on both the transmitter and receiver ends. Adjust the RF module clock source frequency to adjust the uplink subsystem operating frequency. Observe the signal spectrum displayed by the spectrum analyzer to verify that the single-channel bandwidth is 33 MHz and the total bandwidth covers 100 MHz. Set the spectrum analyzer center frequency to 14.45 GHz and the resolution to 100 kHz. Record the signal spectrum power distribution and out-of-band noise suppression in real time.

[0013] The transmitting PC cyclically sends fixed data packets to the service board in the baseband processing cabinet through the Gigabit Ethernet interface. The baseband processing cabinet encodes and modulates the data packets before transmitting them through the RF module. The receiving PC receives the data packets through the service board, compares the bit differences between the received data packets and the original data packets, counts the number of bit errors, and calculates the bit error rate.

[0014] The receiving antenna board extracts the pilot OFDM symbols and transmits them to the PC. The PC uses the preamble sequence to complete initial timing synchronization and frequency offset correction. The PC performs MIMO detection on the received data OFDM symbols, calculates the detection matrix based on the minimum mean square error algorithm, and outputs the signal-to-noise ratio of the pilot and data symbols in real time.

[0015] A single-tone sequence P1 and a Golay complementary sequence P2 are inserted into the outbound link frame of the uplink subsystem. The receiving end uses pilot signals to perform parameter estimation. After P1 undergoes FFT calculations, the frequency offset is calculated using the single-tone position deviation to achieve initial delay compensation. The autocorrelation characteristics of P2 are utilized to extract the delay spread and path amplitude fading parameters using a fast correlator. The multipath gain and virtual delay are jointly calculated, and the channel response is modeled as a multipath superposition model, where the path gain is a complex random variable, the total power is normalized, and the delay parameter is determined by the system frequency domain. The pseudo-inverse of the channel matrix is ​​calculated point by point in the frequency domain. Combined with the time-domain autocorrelation characteristics of the pilot sequence, a joint channel impulse response matrix is ​​constructed.

[0016] A further improvement of the technical solution of the present invention is that in S2, the process of generating original baseband data by using a phase shifter and multipath delay simulation and removing DC offset and baseline drift includes:

[0017] In indoor scenarios, the transmitting antenna and receiving end are connected through two sets of phase shifters, each containing four phase-adjustable units, to simulate signal phase changes. The RF signal from the transmitting antenna is split by the first set of phase shifters, with its power reduced to 1 / 2. The second set of phase shifters then adjusts the phase. The four signals are then superimposed at the output port of the second set of phase shifters to simulate the phase noise and power attenuation characteristics of multipath signals. The superimposed baseband signal is filtered through a digital filter to remove the DC component, and linear interpolation is used to compensate for baseline drift. The receiving end then extracts the static channel phase noise parameters from the superimposed baseband signal.

[0018] In outdoor scenarios, the transmitting antenna board has an embedded multipath delay module. The delay parameters and amplitude weights of the main path and multipath are configured through software. The main path signal is transmitted directly, and the multipath signal is delayed by N sampling points and multiplied by a complex amplitude factor. The main and multipath signals are superimposed to form baseband data with delay spread. The receiving end performs multipath separation on the superimposed baseband signal and calculates the number of delayed sampling points based on the multipath delay spread requirements. The superimposed signal is high-pass filtered using an infinite impulse response filter with a cutoff frequency of 0.1 Hz. The baseline is extracted based on the signal envelope, and the baseline trend is estimated using a polynomial fitting method. The fitted value is subtracted from the original signal.

[0019] A further improvement of the technical solution of the present invention is that in S2, the process of classifying and extracting scene features includes:

[0020] For indoor scenarios, the received signal phase is sampled in the time domain to calculate the mean and variance of the phase offset and quantify the statistical characteristics of the phase noise. Based on the digitally filtered signal, the power contribution of each path is analyzed, and the single-path power contribution is calculated through time-domain energy integration.

[0021] For outdoor scenarios, the ratio of the multipath signal amplitude to the main path amplitude is calculated through a time domain correlator, and the distribution characteristics of the path gain are statistically analyzed. Based on the number of multipath delay sampling points, a frequency distribution histogram of the multipath delay is generated to quantify the delay spread range.

[0022] A further improvement of the technical solution of the present invention is that in S3, the process of using the Wiener filtering algorithm to dynamically optimize the filter parameters in combination with scene features includes:

[0023] In indoor scenarios, phase noise is considered an additional noise term, and the phase noise variance is derived from the time-domain sampling phase offset statistics. In the Wiener filter objective function, the phase noise variance is added to the noise power. The phase noise suppression weight factor is dynamically adjusted to solve for the optimal filter coefficient. When calculating the filter coefficient point by point in the frequency domain, the attenuation weight of the high-frequency band is increased.

[0024] In outdoor scenarios, an equivalent channel matrix containing the delay and gain parameters of the main path and multipath is constructed. Time-domain equalization constraints are introduced into the Wiener filter equation, the objective function is expanded, and the regularization factor is adjusted. Based on the frequency distribution histogram of multipath delay, the equalizer order is adjusted to cover the maximum delay spread range, and the optimal filter coefficients are solved.

[0025] A further improvement of the technical solution of the present invention is that in S3, the process of selecting a feedback strategy based on the scene characteristics based on the pilot-assisted iterative soft decision feedback algorithm includes:

[0026] A fast-converging soft decision mechanism is used for indoor channels. Based on the pilot-assisted initial channel estimation results, soft decision values ​​are generated. The low-power attenuation characteristic is exploited to reduce the order of the feedback filter, retain the feedback coefficient of the main path component, and shorten the iterative convergence time. In each iteration, the feedforward filter coefficient compensates for the frequency offset caused by phase noise, while the feedback filter coefficient corrects the main path residual error.

[0027] Dynamically adjust the feedback filter coefficients of the outdoor channel. Based on the equivalent channel matrix, the feedforward filter coefficients are solved through a set of linear equations. The feedback filter coefficients are dynamically weighted according to the path gain ratio. If the path amplitude attenuation is large, the feedback coefficient weight is reduced. If it is the main path and strong multipath component, the feedback coefficient weight is increased.

[0028] A further improvement of the technical solution of the present invention is that in S3, the process of applying turbo codes and low-density parity-check codes and allocating coding resources in combination with scenario requirements includes:

[0029] In indoor scenarios, a 1 / 8-efficiency low-density parity-check code and a sparse check matrix structure are used. Error correction is achieved between check nodes and variable nodes through an iterative message passing algorithm. The transmitter encodes information bits using a 1 / 8-efficiency low-density parity-check code to generate redundant check bits. The receiver, based on a belief propagation algorithm and using pilot-assisted phase noise variance parameters, dynamically adjusts the prior probabilities of variable nodes to suppress the propagation of soft-decision errors caused by phase jitter.

[0030] In outdoor scenarios, a recursive systematic convolutional code with a 1 / 3 efficiency is used. The information bits are converted into systematic bits and check bits of two recursive convolutional codes through a turbo code encoder. The interleaver is designed with a random permutation pattern to disperse burst errors caused by multipath interference. The receiver dynamically adjusts the iterative decoding weights based on a soft-input soft-output algorithm, combined with the path gain and delay parameters of the generalized channel impulse response matrix.

[0031] A further improvement of the technical solution of the present invention is that in S4, the process of comparing the channel estimation performance in different scenarios by calculating the normalized mean square error and calculating the limit performance of the coding scheme in different scenarios includes:

[0032] Based on the pilot-assisted generalized channel response estimation results, the mean square error of the actual channel impulse response and the estimated value are compared. The phase noise suppression effect is quantified by comparing the mean square error values ​​before and after Wiener filtering optimization. If the mean square error is reduced after filtering, it is considered that the suppression of high-frequency phase jitter is effective. The critical signal-to-noise ratio is set to -4.5dB to simulate phase noise interference in a low signal-to-noise ratio environment. The transmitter generates data packets using low-density parity-check code encoding and cyclically sends a fixed bit stream. The receiver counts the proportion of error-free transmissions and calculates the error-free probability. If the error-free probability at -4.5dB is ≥99.9%, the coding scheme's phase noise immunity meets the standard. If the error-free probability at -4.5dB is <99.9%, the coding scheme's phase noise immunity fails to meet the standard.

[0033] The equalized channel response and the actual response are substituted into the mean square error formula to calculate the intersymbol interference residual error. The multipath delay compensation effect is verified by the matching degree between the equalizer order and the delay distribution histogram. If the mean square error decreases with increasing equalization order, it is considered that the error spread suppression capability has improved. The critical signal-to-noise ratio is set to -5dB to simulate multipath delay spread and amplitude fading environments. The transmitter generates data packets using turbo coding, and the receiver performs iterative decoding based on the soft-input soft-output algorithm. The bit error rate fluctuation range of 1000 consecutive transmissions at the critical signal-to-noise ratio is calculated. If the fluctuation standard deviation is ≤0.1%, the stability is determined to be met. If the fluctuation standard deviation is >0.1%, the stability is determined to be unsatisfactory.

[0034] A further improvement of the technical solution of the present invention is that in S5, the process of dynamically adjusting the transmission strategy by combining the scene characteristics through the Gigabit Ethernet interface includes:

[0035] Based on the pilot-assisted generalized channel response estimation results, the normalized mean square error and signal-to-noise ratio of the current channel in indoor scenarios are calculated. When the signal-to-noise ratio is ≥20dB, 64QAM high-order modulation is activated to increase the bit carrying capacity per symbol. Combined with the error correction capabilities of low-density parity-check codes, the proportion of redundant check bits is reduced, increasing the physical layer effective data rate to 80% of the theoretical peak value. Instructions are sent to the baseband processing cabinet via the Gigabit Ethernet interface to adjust the coding and modulation parameters of the service board and synchronously update the clock source frequency and symbol rate of the RF module.

[0036] Based on the multipath delay parameters extracted by the fast correlator, a delay distribution histogram is generated and the maximum delay spread is calculated. When the maximum delay spread is ≥300ns, QPSK modulation is switched to reduce the symbol rate to adapt to the channel coherence time. Turbo codes are used to increase the parity bit ratio, reducing the service data rate to 70% of the peak value. The equalizer order is adjusted based on the delay distribution histogram and the information is sent to the feedback filter of the baseband processing cabinet via the Gigabit Ethernet interface.

[0037] The receiving end transmits channel state information to the transmitting end through the Gigabit Ethernet interface. The channel state information includes the phase noise variance of indoor scenarios, the delay distribution histogram of outdoor scenarios, and the current SNR value. The service board of the baseband processing cabinet dynamically loads the pre-stored coding and modulation configuration file according to the instructions, adjusts the symbol rate through the clock source of the RF module, and aligns the timing of the transmitting and receiving ends.

[0038] A further improvement of the technical solution of the present invention is that in S5, the process of unifying the transceiver frequency and sampling clock based on the clock source configuration and optimizing the synchronization mechanism according to the scenario characteristics includes:

[0039] The clock source module in the baseband processing cabinet configures the clock frequency and sampling rate of the transmitter and receiver to align their frequencies. The clock source modules on both ends output reference frequencies between 14.400 GHz and 14.500 GHz, respectively. A spectrum analyzer monitors frequency deviation and dynamically adjusts the clock source output to the target frequency. Based on the FFT results of the pilot sequence P1, the sampling clock deviation between the transmitter and receiver is calculated. The sampling clock phase on the receiver is corrected using a phase-locked loop (PLL) to achieve symbol-level synchronization between the transmitter and receiver.

[0040] The synchronization period in indoor scenarios is shortened to accommodate low-latency environments. The pilot sequence P1 is inserted more frequently in the outbound link frame, shortening the synchronization period from the default 100ms to 20ms. Based on the single-tone position deviation of the pilot sequence P1, the frequency offset compensation parameters are updated in real time, reducing the number of synchronization iterations and shortening the synchronization process convergence time to less than 5ms.

[0041] Redundant synchronization signals are added for outdoor scenarios to combat multipath interference. In addition to the regular pilot sequences P1 and P2, redundant pilot symbols are inserted into the outbound link frame, shortening the interval to 1 / 4 of the original design. The maximum delay spread of multipath signals is calculated based on the delay distribution histogram, and the synchronization signal interval is adjusted to half of the maximum delay spread.

[0042] Due to the adoption of the above technical solution, the present invention has the following technical advancements compared to the prior art:

[0043] 1. The present invention provides an uplink subsystem complexity reduction method based on PCMA technology. By accurately collecting various parameters of the uplink signal and effectively obtaining channel characteristics using pilot sequences and Gray complementary sequences, the accuracy of channel estimation can be significantly improved. While reducing system complexity, the stability and reliability of data transmission are ensured, effectively solving the performance degradation problem caused by inaccurate channel estimation in traditional systems.

[0044] 2. The present invention provides a method for reducing the complexity of the uplink subsystem based on PCMA technology. By dynamically optimizing filter parameters and selecting feedback strategies, combined with advanced coding technologies such as turbo codes and low-density parity-check codes, it can flexibly allocate coding resources according to scenario characteristics, which not only further reduces system complexity, but also significantly improves data transmission efficiency and spectrum utilization, and enhances the system's adaptability to different environments.

[0045] 3. The present invention provides a method for reducing the complexity of the uplink subsystem based on PCMA technology, which realizes the adjustment of dynamic transmission strategy through the Gigabit Ethernet interface, unifies the frequency and sampling clock of the transmitting and receiving ends, and optimizes the synchronization mechanism to ensure the real-time and synchronization of data transmission, effectively avoids the performance loss caused by transmission delay and synchronization error, and improves the stability of the overall system and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0047] Figure 1Flowchart of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] Examples, such as Figure 1 As shown, the present invention provides a method for reducing the complexity of an uplink subsystem based on PCMA technology, comprising the following steps:

[0050] S1. Use a spectrum analyzer to collect uplink signal bandwidth, spectrum distribution, and single-channel bandwidth data. Use a bit error rate test program to collect bit error rate data at the receiving end. Use MIMO detection to collect the signal-to-noise ratio parameters of pilot symbols and data symbols in real time. Use pilot sequences and Gray complementary sequences to collect the channel response, delay, and frequency offset parameters of the asymmetric PCMA system. Deploy spectrum analyzers at the output ports of the RF modules at the transmitter and receiver ends respectively. Adjust the clock source frequency of the RF module to slide the operating frequency of the uplink subsystem. Observe the signal spectrum range displayed by the spectrum analyzer to verify that the single-channel bandwidth is 33MHz and the total bandwidth covers 100MHz. Set the center frequency of the spectrum analyzer to 14.45GHz and the resolution to 100kHz. Record the power distribution of the signal spectrum and the out-of-band noise suppression in real time. The transmitting PC cyclically sends fixed data packets to the service board of the baseband processing cabinet through the Gigabit Ethernet interface. After coding and modulation by the baseband processing cabinet, the data packets are transmitted through the RF module. The receiving PC receives the data packets through the service board and compares them with the received data packets. The receiving end extracts the pilot OFDM symbols from the original data packet, counts the number of bit errors, and calculates the bit error rate. The receiving antenna board extracts the pilot OFDM symbols and transmits them to the PC. The PC uses the preamble sequence to complete initial timing synchronization and frequency offset correction. The PC performs MIMO detection on the received data OFDM symbols, calculates the detection matrix based on the minimum mean square error algorithm, and outputs the signal-to-noise ratio of the pilot and data symbols in real time. The single-tone sequence P1 and the Gray complementary sequence P2 are inserted into the outbound link frame of the uplink subsystem. The receiving end completes parameter estimation with the assistance of the pilot. After P1 undergoes FFT operation, the frequency offset is calculated based on the single-tone position deviation to complete the initial delay compensation. The autocorrelation characteristics of P2 are used to extract the delay spread and path amplitude fading parameters through a fast correlator. The multipath gain and virtual delay are jointly calculated, and the channel response is modeled as a multipath superposition model, where the path gain is a complex random variable, the total power is normalized, and the delay parameter is determined by the system frequency domain. The pseudo-inverse of the channel matrix is ​​calculated point by point in the frequency domain. Combined with the time-domain autocorrelation characteristics of the pilot sequence, the joint channel impulse response matrix is ​​constructed.

[0051] S2. Generate original baseband data through phase shifter and multipath delay simulation, remove DC offset and baseline drift, and classify and extract scene features. In indoor scenarios, the transmitting antenna and the receiving end are connected through two groups of phase shifters containing 4 phase adjustable units respectively to simulate signal phase changes. The RF signal of the transmitting antenna is split by the first group of phase shifters, and the power is reduced to 1 / 2. The phase is adjusted by the second group of phase shifters. The output port of the second group of phase shifters superimposes the 4 signals to simulate the phase noise and power attenuation characteristics of the multipath signal. The superimposed baseband signal is filtered out of the DC component by a digital filter, and the baseline drift is compensated by linear interpolation. The receiving end extracts the static channel phase noise parameters through the superimposed baseband signal. In outdoor scenarios, the transmitting antenna board has an embedded multipath delay module. The delay parameters and amplitude weights of the main path and multipath are configured by software. The main path signal is transmitted directly, and the multipath signal is delayed by N sampling points and multiplied by The complex amplitude factor is used to superimpose the main path and multipath signals to form baseband data with delay spread. The receiver performs multipath separation on the superimposed baseband signal and calculates the number of delay sampling points based on the multipath delay spread requirements. The superimposed signal is high-pass filtered using an infinite impulse response filter with a cutoff frequency of 0.1 Hz. The baseline is extracted based on the signal envelope, and the baseline trend is estimated using a polynomial fitting method. The fitted value is subtracted from the original signal. For indoor scenarios, the phase of the received signal is sampled in the time domain, the mean and variance of the phase offset are calculated, and the statistical characteristics of the phase noise are quantified. Based on the digitally filtered signal, the power contribution of each path is analyzed, and the single-path power contribution is calculated through time-domain energy integration. For outdoor scenarios, the ratio of the multipath signal amplitude to the main path amplitude is calculated using a time-domain correlator. The distribution characteristics of the path gain are statistically analyzed. Based on the number of multipath delay sampling points, a frequency distribution histogram of the multipath delay is generated to quantify the delay spread range.

[0052] S3. Use the Wiener filtering algorithm to dynamically optimize the filter parameters in combination with the scene characteristics. Based on the pilot-assisted iterative soft decision feedback algorithm, select the feedback strategy according to the scene characteristics, apply turbo code and low-density parity check code, and allocate coding resources in combination with the scene requirements. In indoor scenes, the phase noise is regarded as an additional noise term, and the phase noise variance is obtained by the time domain sampling phase offset statistics. In the Wiener filtering objective function, the phase noise variance is superimposed on the noise power, and the phase noise suppression weight factor is dynamically adjusted to solve the optimal filter coefficient. When calculating the filter coefficient point by point in the frequency domain, the attenuation weight of the high-frequency band is increased. For outdoor scenes, In this scenario, an equivalent channel matrix containing the delay and gain parameters of the main path and multipath is constructed, time domain equalization constraints are introduced into the Wiener filter equation, the objective function is expanded, the regularization factor is adjusted, and the equalizer order is adjusted according to the frequency distribution histogram of the multipath delay to cover the maximum delay extension range. The optimal filter coefficient is solved, and a fast-converging soft decision mechanism is adopted for indoor channels. Based on the initial channel estimation result assisted by the pilot, the soft decision value is generated. The low-power attenuation characteristic is utilized to reduce the feedback filter order, retain the main path component feedback coefficient, shorten the iterative convergence time, and in each iteration, the feedforward filter coefficient compensates for the phase noise The frequency deviation caused by the feedback filter coefficient is used to correct the residual error of the main path, and the feedback filter coefficient of the outdoor channel is dynamically adjusted. Based on the equivalent channel matrix, the feedforward filter coefficient is solved by the linear equation group, and the feedback filter coefficient is dynamically assigned weights according to the path gain ratio. If the path amplitude attenuation is large, its feedback coefficient weight is reduced. If it is the main path and strong multipath component, the feedback coefficient weight is increased. In the indoor scene, a 1 / 8 efficiency low-density parity check code is used, and a sparse check matrix structure is adopted. The check node and the variable node realize error correction through the iterative message passing algorithm. The transmitter transmits the information bits through a 1 / 8 efficiency low-density parity check code. Parity-check code encoding generates redundant check bits. The receiver, based on a belief propagation algorithm, utilizes pilot-assisted phase noise variance parameters to dynamically adjust the prior probabilities of variable nodes and suppress the propagation of soft-decision errors caused by phase jitter. In outdoor scenarios, a recursive systematic convolutional code with a 1 / 3 efficiency is used. Information bits are converted into systematic bits and two check bits for recursive convolutional codes via a turbo encoder. The interleaver is designed with a random permutation pattern to disperse burst errors caused by multipath interference. The receiver dynamically adjusts the iterative decoding weights based on a soft-input soft-output algorithm, combining the path gain and delay parameters of the generalized channel impulse response matrix.

[0053] S4. Compare the channel estimation performance in different scenarios through normalized mean square error calculation, count the limit performance of the coding scheme in different scenarios, compare the mean square error of the actual channel impulse response and the estimated value based on the pilot-assisted generalized channel response estimation result, quantify the phase noise suppression effect by comparing the mean square error values ​​before and after Wiener filtering optimization, if the mean square error is reduced after filtering, it is considered that the suppression of high-frequency phase jitter is effective, set the critical signal-to-noise ratio to -4.5dB, simulate the phase noise interference in a low signal-to-noise ratio environment, the transmitter generates a data packet through low-density parity check code encoding, and cyclically sends a fixed bit stream. The receiver counts the proportion of error-free transmission times and calculates the error-free probability. If the error-free probability at -4.5dB is ≥99.9%, it verifies that the coding scheme's anti-phase noise capability meets the standard. If If the error-free probability at -4.5 dB is less than 99.9%, the coding scheme's phase noise immunity is substandard. The equalized channel response and the actual response are substituted into the mean square error formula to calculate the intersymbol interference residual error. The multipath delay compensation effect is verified by the matching degree between the equalizer order and the delay distribution histogram. If the mean square error decreases with increasing equalization order, the error propagation suppression capability is considered to be improved. The critical signal-to-noise ratio is set to -5 dB, and a multipath delay spread and amplitude fading environment is simulated. The transmitter generates data packets using turbo coding, and the receiver iteratively decodes them using a soft-input, soft-output algorithm. The bit error rate fluctuation range for 1000 consecutive transmissions at the critical signal-to-noise ratio is calculated. If the fluctuation standard deviation is ≤0.1%, the stability is determined to be met. If the fluctuation standard deviation is greater than 0.1%, the stability is determined to be substandard.

[0054] S5. Through the Gigabit Ethernet interface, the transmission strategy is dynamically adjusted in combination with the scene characteristics. Based on the clock source configuration, the frequency and sampling clock of the transmitting and receiving ends are unified, and the synchronization mechanism is optimized according to the scene characteristics. Based on the pilot-assisted generalized channel response estimation results, the normalized mean square error and signal-to-noise ratio of the current channel in the indoor scene are calculated. When the signal-to-noise ratio is ≥20dB, 64QAM high-order modulation is activated to increase the bit carrying capacity of the unit symbol. Combined with the error correction capability of the low-density parity check code, the proportion of redundant check bits is reduced, and the effective data rate of the physical layer is increased to 80% of the theoretical peak value. Instructions are sent to the baseband processing cabinet through the Gigabit Ethernet interface to adjust the coding and modulation parameters of the service board and update synchronously. The clock source frequency and symbol rate of the RF module are used to generate a delay distribution histogram based on the multipath delay parameters extracted by the fast correlator. The maximum delay spread is calculated. When the maximum delay spread is ≥300ns, QPSK modulation is switched to reduce the symbol rate to adapt to the channel coherence time. The turbo code is used to increase the proportion of check bits and reduce the service data rate to 70% of the peak value. The equalizer order is adjusted according to the delay distribution histogram and sent to the feedback filter of the baseband processing cabinet through the Gigabit Ethernet interface. The receiving end transmits channel state information to the transmitting end through the Gigabit Ethernet interface. The channel state information includes the phase noise variance of the indoor scene, the delay distribution histogram of the outdoor scene and the current SN R value, the business board of the baseband processing cabinet dynamically loads the pre-stored coding and modulation configuration file according to the instruction, adjusts the symbol rate through the clock source of the RF module, and aligns the timing of the transceiver. Through the clock source module of the baseband processing cabinet, configure the clock frequency and sampling rate of the transmitter and receiver to make the frequency points of the transmitter and receiver consistent. The clock source modules of the transmitter and receiver respectively output the reference frequency of 14.400GHz to 14.500GHz. The frequency deviation is monitored by the spectrum analyzer, and the clock source output is dynamically adjusted to the target frequency point. Based on the FFT operation result of the pilot sequence P1, the sampling clock deviation of the transmitter and receiver is calculated, and the sampling clock phase of the receiver is corrected through the phase-locked loop to achieve symbol-level synchronization of the transmitter and receiver. First, the synchronization period in indoor scenarios is shortened to match the low-latency environment. The insertion frequency of the pilot sequence P1 is increased in the outbound link frame, shortening the synchronization period from the default 100ms to 20ms. Based on the single-tone position deviation of the pilot sequence P1, the frequency offset compensation parameters are updated in real time, reducing the number of synchronization iterations and shortening the synchronization process convergence time to less than 5ms. Redundant synchronization signals are added in outdoor scenarios to cope with multipath interference. In addition to the regular pilot sequences P1 and P2, redundant pilot symbols are inserted in the outbound link frame, and the interval is shortened to 1 / 4 of the original design. The maximum delay spread of the multipath signal is calculated based on the delay distribution histogram, and the synchronization signal interval is adjusted to half of the maximum delay spread.

[0055] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for reducing the complexity of an uplink subsystem based on PCMA technology, characterized in that: The following steps are involved: S1. Use a spectrum analyzer to collect uplink signal bandwidth, spectrum distribution, and single-channel bandwidth data. Use a bit error rate test program to collect receiving end bit error rate data. Use MIMO detection to collect the signal-to-noise ratio parameters of pilot symbols and data symbols in real time. Use pilot sequences and Golay complementary sequences to collect the channel response, delay, and frequency offset parameters of the asymmetric PCMA system. S2. Generate raw baseband data through phase shifter and multipath delay simulation, remove DC offset and baseline drift, and classify and extract scene features; S3: Adopt the Wiener filter algorithm, dynamically optimize the filter parameters based on the scene characteristics, use the pilot-assisted iterative soft decision feedback algorithm, select the feedback strategy based on the scene characteristics, apply turbo codes and low-density parity-check codes, and allocate coding resources based on the scene requirements; S4. Compare the channel estimation performance in different scenarios by calculating the normalized mean square error and calculate the extreme performance of the coding scheme in different scenarios; S5. Through the Gigabit Ethernet interface, the transmission strategy is dynamically adjusted based on the scenario characteristics. Based on the clock source configuration, the frequency and sampling clock of the transmitting and receiving ends are unified, and the synchronization mechanism is optimized according to the scenario characteristics.

2. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 1, characterized in that: In S1, the process of collecting uplink signal bandwidth, spectrum distribution, and single-channel bandwidth data using a spectrum analyzer, collecting receiving end bit error rate data using a bit error rate test program, collecting signal-to-noise ratio parameters of pilot symbols and data symbols in real time through MIMO detection, and collecting channel response, delay, and frequency offset parameters of the asymmetric PCMA system using a pilot sequence and a Golay complementary sequence includes: Deploy spectrum analyzers at the RF module output ports on both the transmitter and receiver ends. Adjust the RF module clock source frequency to adjust the uplink subsystem operating frequency. Observe the signal spectrum displayed by the spectrum analyzer to verify that the single-channel bandwidth is 33 MHz and the total bandwidth covers 100 MHz. Set the spectrum analyzer center frequency to 14.45 GHz and the resolution to 100 kHz. Record the signal spectrum power distribution and out-of-band noise suppression in real time. The transmitting PC cyclically sends fixed data packets to the service board in the baseband processing cabinet through the Gigabit Ethernet interface. The baseband processing cabinet encodes and modulates the data packets before transmitting them through the RF module. The receiving PC receives the data packets through the service board, compares the bit differences between the received data packets and the original data packets, counts the number of bit errors, and calculates the bit error rate. The receiving antenna board extracts the pilot OFDM symbols and transmits them to the PC. The PC uses the preamble sequence to complete initial timing synchronization and frequency offset correction. The PC performs MIMO detection on the received data OFDM symbols, calculates the detection matrix based on the minimum mean square error algorithm, and outputs the signal-to-noise ratio of the pilot and data symbols in real time. A single-tone sequence P1 and a Golay complementary sequence P2 are inserted into the outbound link frame of the uplink subsystem. The receiving end uses pilot signals to perform parameter estimation. After P1 undergoes FFT calculations, the frequency offset is calculated using the single-tone position deviation to achieve initial delay compensation. The autocorrelation characteristics of P2 are utilized to extract the delay spread and path amplitude fading parameters using a fast correlator. The multipath gain and virtual delay are jointly calculated, and the channel response is modeled as a multipath superposition model, where the path gain is a complex random variable, the total power is normalized, and the delay parameter is determined by the system frequency domain. The pseudo-inverse of the channel matrix is ​​calculated point by point in the frequency domain. Combined with the time-domain autocorrelation characteristics of the pilot sequence, a joint channel impulse response matrix is ​​constructed.

3. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 2, characterized in that: In S2, the process of generating original baseband data through phase shifter and multipath delay simulation and removing DC offset and baseline drift includes: In indoor scenarios, the transmitting antenna and receiving end are connected through two sets of phase shifters, each containing four phase-adjustable units, to simulate signal phase changes. The RF signal from the transmitting antenna is split by the first set of phase shifters, with its power reduced to 1 / 2. The second set of phase shifters then adjusts the phase. The four signals are then superimposed at the output port of the second set of phase shifters to simulate the phase noise and power attenuation characteristics of multipath signals. The superimposed baseband signal is filtered through a digital filter to remove the DC component, and linear interpolation is used to compensate for baseline drift. The receiving end then extracts the static channel phase noise parameters from the superimposed baseband signal. In outdoor scenarios, the transmitting antenna board has an embedded multipath delay module. The delay parameters and amplitude weights of the main path and multipath are configured through software. The main path signal is transmitted directly, and the multipath signal is delayed by N sampling points and multiplied by a complex amplitude factor. The main and multipath signals are superimposed to form baseband data with delay spread. The receiving end performs multipath separation on the superimposed baseband signal and calculates the number of delayed sampling points based on the multipath delay spread requirements. The superimposed signal is high-pass filtered using an infinite impulse response filter with a cutoff frequency of 0.1 Hz. The baseline is extracted based on the signal envelope, and the baseline trend is estimated using a polynomial fitting method. The fitted value is subtracted from the original signal.

4. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 3, characterized in that: In S2, the process of classifying and extracting scene features includes: For indoor scenarios, the received signal phase is sampled in the time domain to calculate the mean and variance of the phase offset and quantify the statistical characteristics of the phase noise. Based on the digitally filtered signal, the power contribution of each path is analyzed, and the single-path power contribution is calculated through time-domain energy integration. For outdoor scenarios, the ratio of the multipath signal amplitude to the main path amplitude is calculated through a time domain correlator, and the distribution characteristics of the path gain are statistically analyzed. Based on the number of multipath delay sampling points, a frequency distribution histogram of the multipath delay is generated to quantify the delay spread range.

5. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 4, characterized in that: In S3, the process of using the Wiener filtering algorithm to dynamically optimize the filter parameters in combination with scene features includes: In indoor scenarios, phase noise is considered an additional noise term, and the phase noise variance is derived from the time-domain sampling phase offset statistics. In the Wiener filter objective function, the phase noise variance is added to the noise power. The phase noise suppression weight factor is dynamically adjusted to solve for the optimal filter coefficient. When calculating the filter coefficient point by point in the frequency domain, the attenuation weight of the high-frequency band is increased. In outdoor scenarios, an equivalent channel matrix containing the delay and gain parameters of the main path and multipath is constructed. Time-domain equalization constraints are introduced into the Wiener filter equation, the objective function is expanded, and the regularization factor is adjusted. Based on the frequency distribution histogram of multipath delay, the equalizer order is adjusted to cover the maximum delay spread range, and the optimal filter coefficients are solved.

6. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 5, characterized in that: In S3, the process of selecting a feedback strategy based on scenario characteristics using the pilot-assisted iterative soft decision feedback algorithm includes: A fast-converging soft decision mechanism is used for indoor channels. Based on the pilot-assisted initial channel estimation results, soft decision values ​​are generated. The low-power attenuation characteristic is exploited to reduce the order of the feedback filter, retain the feedback coefficient of the main path component, and shorten the iterative convergence time. In each iteration, the feedforward filter coefficient compensates for the frequency offset caused by phase noise, while the feedback filter coefficient corrects the main path residual error. Dynamically adjust the feedback filter coefficients of the outdoor channel. Based on the equivalent channel matrix, the feedforward filter coefficients are solved through a set of linear equations. The feedback filter coefficients are dynamically weighted according to the path gain ratio. If the path amplitude attenuation is large, the feedback coefficient weight is reduced. If it is the main path and strong multipath component, the feedback coefficient weight is increased.

7. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 6, characterized in that: In S3, the process of applying turbo codes and low-density parity-check codes and allocating coding resources in accordance with scenario requirements includes: In indoor scenarios, a 1 / 8-efficiency low-density parity-check code and a sparse check matrix structure are used. Error correction is achieved between check nodes and variable nodes through an iterative message passing algorithm. The transmitter encodes information bits using a 1 / 8-efficiency low-density parity-check code to generate redundant check bits. The receiver, based on a belief propagation algorithm and using pilot-assisted phase noise variance parameters, dynamically adjusts the prior probabilities of variable nodes to suppress the propagation of soft-decision errors caused by phase jitter. In outdoor scenarios, a recursive systematic convolutional code with a 1 / 3 efficiency is used. The information bits are converted into systematic bits and check bits of two recursive convolutional codes through a turbo code encoder. The interleaver is designed with a random permutation pattern to disperse burst errors caused by multipath interference. The receiver dynamically adjusts the iterative decoding weights based on a soft-input soft-output algorithm, combined with the path gain and delay parameters of the generalized channel impulse response matrix.

8. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 7, characterized in that: In S4, the process of comparing the channel estimation performance in different scenarios by calculating the normalized mean square error and calculating the limit performance of the coding scheme in different scenarios includes: Based on the pilot-assisted generalized channel response estimation results, the mean square error of the actual channel impulse response and the estimated value are compared. The phase noise suppression effect is quantified by comparing the mean square error values ​​before and after Wiener filtering optimization. If the mean square error is reduced after filtering, it is considered that the suppression of high-frequency phase jitter is effective. The critical signal-to-noise ratio is set to -4.5dB to simulate phase noise interference in a low signal-to-noise ratio environment. The transmitter generates data packets using low-density parity-check code encoding and cyclically sends a fixed bit stream. The receiver counts the proportion of error-free transmissions and calculates the error-free probability. If the error-free probability at -4.5dB is ≥99.9%, the coding scheme's phase noise immunity meets the standard. If the error-free probability at -4.5dB is <99.9%, the coding scheme's phase noise immunity fails to meet the standard. The equalized channel response and the actual response are substituted into the mean square error formula to calculate the intersymbol interference residual error. The multipath delay compensation effect is verified by the matching degree between the equalizer order and the delay distribution histogram. If the mean square error decreases with increasing equalization order, it is considered that the error spread suppression capability has improved. The critical signal-to-noise ratio is set to -5dB to simulate multipath delay spread and amplitude fading environments. The transmitter generates data packets using turbo coding, and the receiver performs iterative decoding based on the soft-input soft-output algorithm. The bit error rate fluctuation range of 1000 consecutive transmissions at the critical signal-to-noise ratio is calculated. If the fluctuation standard deviation is ≤0.1%, the stability is determined to be met. If the fluctuation standard deviation is >0.1%, the stability is determined to be unsatisfactory.

9. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 8, characterized in that: In S5, the process of dynamically adjusting the transmission strategy based on the scenario characteristics through the Gigabit Ethernet interface includes: Based on the pilot-assisted generalized channel response estimation results, the normalized mean square error and signal-to-noise ratio of the current channel in indoor scenarios are calculated. When the signal-to-noise ratio is ≥20dB, 64QAM high-order modulation is activated to increase the bit carrying capacity per symbol. Combined with the error correction capabilities of low-density parity-check codes, the proportion of redundant check bits is reduced, increasing the physical layer effective data rate to 80% of the theoretical peak value. Instructions are sent to the baseband processing cabinet via the Gigabit Ethernet interface to adjust the coding and modulation parameters of the service board and synchronously update the clock source frequency and symbol rate of the RF module. Based on the multipath delay parameters extracted by the fast correlator, a delay distribution histogram is generated and the maximum delay spread is calculated. When the maximum delay spread is ≥300ns, QPSK modulation is switched to reduce the symbol rate to adapt to the channel coherence time. Turbo codes are used to increase the parity bit ratio, reducing the service data rate to 70% of the peak value. The equalizer order is adjusted based on the delay distribution histogram and the information is sent to the feedback filter of the baseband processing cabinet via the Gigabit Ethernet interface. The receiving end transmits channel state information to the transmitting end through the Gigabit Ethernet interface. The channel state information includes the phase noise variance of indoor scenarios, the delay distribution histogram of outdoor scenarios, and the current SNR value. The service board of the baseband processing cabinet dynamically loads the pre-stored coding and modulation configuration file according to the instructions, adjusts the symbol rate through the clock source of the RF module, and aligns the timing of the transmitting and receiving ends.

10. The method for reducing uplink subsystem complexity based on PCMA technology according to claim 9, characterized in that: In S5, based on the clock source configuration, the frequency points and sampling clocks of the transmitting and receiving ends are unified, and the synchronization mechanism is optimized according to the scenario characteristics. The process includes: The clock source module in the baseband processing cabinet configures the clock frequency and sampling rate of the transmitter and receiver to align their frequencies. The clock source modules on both ends output reference frequencies between 14.400 GHz and 14.500 GHz, respectively. A spectrum analyzer monitors frequency deviation and dynamically adjusts the clock source output to the target frequency. Based on the FFT results of the pilot sequence P1, the sampling clock deviation between the transmitter and receiver is calculated. The sampling clock phase on the receiver is corrected using a phase-locked loop (PLL) to achieve symbol-level synchronization between the transmitter and receiver. The synchronization period in indoor scenarios is shortened to accommodate low-latency environments. The pilot sequence P1 is inserted more frequently in the outbound link frame, shortening the synchronization period from the default 100ms to 20ms. Based on the single-tone position deviation of the pilot sequence P1, the frequency offset compensation parameters are updated in real time, reducing the number of synchronization iterations and shortening the synchronization process convergence time to less than 5ms. Redundant synchronization signals are added for outdoor scenarios to combat multipath interference. In addition to the regular pilot sequences P1 and P2, redundant pilot symbols are inserted into the outbound link frame, shortening the interval to 1 / 4 of the original design. The maximum delay spread of multipath signals is calculated based on the delay distribution histogram, and the synchronization signal interval is adjusted to half of the maximum delay spread.

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