A wireless communication signal transmission system and method based on adaptive modulation

Abstract

The application relates to the technical field of wireless communication, and discloses a wireless communication signal transmission system and method based on adaptive modulation, which comprises a likelihood ratio extraction module, a queue monitoring module, a parameter adaptive control module and a constellation mapping module; the likelihood ratio extraction module acquires a log-likelihood ratio sequence; the queue monitoring module determines a buffer queue depth; the parameter adaptive control module adjusts a sliding integral register accumulation period according to the buffer queue depth, and uses the sliding integral register to implement time domain integral processing on the log-likelihood ratio sequence to generate a channel quality representation parameter, and then determines a target modulation order; the application cross-layer correlates the data backlog level with the baseband statistical time scale, reduces the dependence on explicit channel state information feedback, reduces control signaling overhead, smoothes transient impulse noise interference through a dynamic accumulation mechanism, prevents buffer overflow, and improves the transmission net throughput rate of digital information in a high concurrency environment.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication technology, and in particular relates to a wireless communication signal transmission system and method based on adaptive modulation. Background Technology

[0002] In current digital information transmission systems, adaptive modulation and coding architectures typically determine the corresponding modulation order and coding rate by obtaining quality indicators generated from channel estimation and looking up tables. During this process, the receiver calculates channel state information and sends control signaling to the transmitter via a feedback link, allowing the transmitter to adjust the mapping logic of subsequent data packets. However, in industrial scenarios with massive numbers of communication nodes, this explicit feedback mechanism generates high protocol overhead, significantly crowding out the effective payload of physical frames. Due to the prevalence of microsecond-level pulse interference in industrial environments, the corresponding channel physical characteristics usually shift when the periodic feedback-based instructions reach the transmitter, causing modulation strategies to lag and fail. The more fundamental technical bottleneck stems from the mismatch between the statistical inertia of the digital baseband processing stage and the dynamics of the service flow.

[0003] In conventional designs, the statistical window length for evaluating demodulation confidence is pre-fixed. While this rigid window ensures statistical stability, it ignores the real-time backlog pressure on the medium access control layer's data buffer queue. When sudden interference causes channel degradation and a surge in pending data, the physical layer still uses a fixed statistical period to determine the modulation order, leading to a sharp decrease in the number of bits carried by a single symbol, thereby triggering buffer overflow and packet loss. For example, Chinese invention patent application CN102497251A discloses an adaptive modulation and coding method in a wireless mesh network, which determines the signal-to-noise ratio fed back by the physical layer by setting high and low bit queue thresholds in the link layer buffer. The initial rate is offset to balance the overflow rate and the packet loss rate. However, the core decision-making benchmark of this scheme still implicitly relies on the signal-to-noise ratio (SNR) of the physical layer feedback, a transient indicator. Moreover, its correction logic is based on a fixed statistical window. In a non-ideal industrial electromagnetic environment, transient pulses can cause drastic jumps in the SNR estimation. This rate post-processing adjustment method based on a fixed threshold cannot smooth out the fluctuations in statistical indicators caused by interference from the source. When faced with extreme conditions where business backlogs and transient interference overlap, this logical rigidity can easily induce frequent oscillations in the modulation order, which in turn exacerbates the risk of buffer overflow and packet loss.

[0004] Therefore, the technical problem to be solved by this invention is how to use the demodulation characteristics of the receiver to replace explicit feedback and reconstruct the time inertia of baseband statistics based on the queuing pressure of the medium access control layer in order to block the reduced-order oscillation caused by transient interference and improve the system throughput performance. Summary of the Invention

[0005] This invention provides a wireless communication signal transmission system based on adaptive modulation, comprising: The likelihood ratio extraction module is used to obtain the log-likelihood ratio sequence from the received digital baseband signal; The queue monitoring module is used to determine the cache queue depth of the media access control layer in real time. The parameter adaptive control module is used to determine the accumulation period of the sliding integral register based on the mapping relationship between the buffer queue depth and the baseband statistical time scale. The parameter adaptive control module achieves parameter adjustment through the following steps: Step 101, identify the preset interval to which the buffer queue depth belongs; Step 102, match the corresponding sliding integral step size according to the preset interval to determine the accumulation period of the sliding integral register; The parameter adaptive control module is used to perform time-domain accumulation of the log-likelihood ratio sequence using the sliding integral register with the accumulation period to output the channel quality characterization parameter; The parameter adaptive control module is also used to determine the target modulation order according to the association rule between the channel quality characterization parameter and the buffer queue depth, and output the modulation switching command; The constellation mapping module is used to map the bit stream to be transmitted to the signal constellation diagram corresponding to the target modulation order according to the modulation switching command.

[0006] Preferably, the likelihood ratio extraction module includes a discreteness analysis unit, which is used to calculate the variance of the log-likelihood ratio sequence within the sampling window; the parameter adaptive control module uses the variance as the input value of the channel quality characterization parameter.

[0007] Preferably, the sliding integral register includes multiple shift registers with different delay periods and an accumulator configured with a limiting operator; the parameter adaptive control module is used to implement the following refinement steps: step 1021, when the buffer queue depth increases, the number of effective taps of the shift register is increased to extend the accumulation period; step 1022, the limiting operator is used to nonlinearly suppress the pulse interference amplitude in the log-likelihood ratio sequence.

[0008] Preferably, the parameter adaptive control module further includes a time delay compensation unit, which is used to calculate the baseband processing time delay deviation based on the length of the accumulation period, and use the baseband processing time delay deviation to correct the triggering time of the modulation switching command, so as to eliminate the control lag introduced by long period statistics.

[0009] Preferably, the queue monitoring module is also used to calculate the rate of change of the buffer queue depth; the parameter adaptive control module is used to implement the following emergency preprocessing steps when the rate of change exceeds the preset slope threshold: Step 103: shorten the accumulation period of the sliding integral register to improve the system's response sensitivity to sudden channel deterioration.

[0010] Preferably, the constellation mapping module supports QAM and PSK modulation modes; the modulation switching command includes a power scaling factor for constellation coordinates, and the constellation mapping module adjusts the average power spectral density of the transmitted signal when switching the target modulation order according to the power scaling factor.

[0011] Preferably, the system further includes a protocol feedback module, which encapsulates the channel quality characterization parameters into implicit channel state information and feeds the implicit channel state information back to the transmitter to reduce the overhead ratio of pilot sequences in the physical layer frame structure.

[0012] Preferably, the likelihood ratio extraction module is also used to perform confidence weighting on the log-likelihood ratio sequence to reduce the weighting effect of non-Gaussian impulse noise on the extraction process of channel quality characterization parameters.

[0013] Preferably, the system also includes a closed-loop monitoring module for real-time monitoring of the bit error rate after the target modulation order is switched; when the bit error rate is continuously higher than the preset bit error threshold within 10ms and the buffer queue depth is greater than the preset overflow warning value, the closed-loop monitoring module is used to reset the accumulation period to 1 basic transmission frame period.

[0014] A wireless communication signal transmission method based on adaptive modulation includes the following steps: Step 1001: Obtain the log-likelihood ratio sequence from the received digital baseband signal; Step 1002: Determine the cache queue depth of the media access control layer in real time; Step 1003: Determine the accumulation period of the sliding integral register based on the mapping relationship between the cache queue depth and the baseband statistical time scale. Step 1003 specifically includes the following sub-steps: Sub-step 10031: Identify the preset interval to which the cache queue depth belongs; Sub-step 10032: Match the corresponding sliding integral step size according to the preset interval to determine the accumulation period of the sliding integral register. Step 1004: Using a sliding integral register with an accumulation period, the log-likelihood ratio sequence is accumulated in the time domain to output channel quality characterization parameters. Step 1005: Determine the target modulation order based on the correlation rules between channel quality characterization parameters and buffer queue depth, and generate modulation switching instructions; Step 1006: According to the modulation switching instruction, map the bit stream to be transmitted to the signal constellation diagram corresponding to the target modulation order.

[0015] Compared with existing technologies, the wireless communication signal transmission system based on adaptive modulation of the present invention has the following advantages: 1. In wireless communication signal transmission, the method of extracting implicit channel features from the soft decision decoding sequence of the received signal is adopted to replace the reliance on explicit probe of pilot sequence and high-frequency feedback of channel state information in the traditional architecture. This avoids the frequent occupation of physical frame payload time slots by control signaling, reduces the protocol overhead of digital baseband processing from the data source, and improves the effective net throughput of digital information transmission while maintaining service continuity.

[0016] 2. By cross-linking the buffer queue depth of the media access control layer with the demodulation confidence of the physical layer, the timing disconnect between the physical layer modulation decision and the link layer traffic status is broken. This enables the modulation order switching logic to be non-linearly triggered according to the data backlog, effectively avoiding modulation order reduction due to blindly pursuing channel matching under complex interference conditions. It also prevents buffer overflow and data packet loss caused by a sudden reduction in the number of bits carried by a single symbol, thereby enhancing the stability of message delivery in high-concurrency scenarios.

[0017] 3. By utilizing the urgency of transmission, the logic for acquiring baseband statistical characteristics is physically reconstructed. The accumulation period of the sliding integral register is dynamically extended according to the queue depth. Based on the receiver's statistical smoothing capability for high-frequency transient pulse noise, this flexible scaling mechanism based on the time-domain integral window transforms the modulation oscillation that was originally bound to be triggered into statistical lag processing on the time axis. Without modifying the hardware circuit, the synergistic effect of digital domain limiting and long window filtering is used to win a physical window for absorbing instantaneous burst services, thereby achieving deep coupling and reliable decoupling between communication link layers. Attached Figure Description

[0018] Figure 1 This is a flowchart of the signal transmission method for adaptive adjustment of the buffer queue depth according to the present invention; Figure 2 This is the modulation parameter control logic diagram of the present invention, which takes into account both stationary statistics and burst response. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0020] It should be noted that all directional and positional terms used in this invention, such as: up, down, left, right, front, back, vertical, horizontal, inner, outer, top, bottom, transverse, longitudinal, center, etc., are only used to explain the relative positional relationship and connection between components in a specific state (as shown in the accompanying drawings). They are only for the convenience of describing this invention and do not require that this invention be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention. In addition, the descriptions of "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated.

[0021] In the description of this invention, unless otherwise explicitly specified and limited, the terms installation, connection, and linking should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections; they can refer to direct connections or indirect connections through an intermediate medium; they can refer to the internal communication between two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.

[0022] In the description of this specification, references to the terms "an embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0023] An adaptive modulation-based wireless communication signal transmission system includes: The likelihood ratio extraction module is used to obtain the log-likelihood ratio sequence from the received digital baseband signal; The queue monitoring module is used to determine the cache queue depth of the media access control layer in real time. The parameter adaptive control module is used to determine the accumulation period of the sliding integral register based on the mapping relationship between the buffer queue depth and the baseband statistical time scale. The parameter adaptive control module achieves parameter adjustment through the following steps: Step 101, identify the preset interval to which the buffer queue depth belongs; Step 102, match the corresponding sliding integral step size according to the preset interval to determine the accumulation period of the sliding integral register; The parameter adaptive control module is used to perform time-domain accumulation of the log-likelihood ratio sequence using the sliding integral register with the accumulation period to output the channel quality characterization parameter; The parameter adaptive control module is also used to determine the target modulation order according to the association rule between the channel quality characterization parameter and the buffer queue depth, and output the modulation switching command; The constellation mapping module is used to map the bit stream to be transmitted to the signal constellation diagram corresponding to the target modulation order according to the modulation switching command.

[0024] Preferably, the likelihood ratio extraction module includes a discreteness analysis unit, which is used to calculate the variance of the log-likelihood ratio sequence within the sampling window; the parameter adaptive control module uses the variance as the input value of the channel quality characterization parameter.

[0025] Preferably, the sliding integral register includes multiple shift registers with different delay periods and an accumulator configured with a limiting operator; the parameter adaptive control module is used to implement the following refinement steps: Step 1021: When the buffer queue depth increases, the number of effective taps of the shift register is increased to extend the accumulation period; Step 1022: The amplitude of the impulse interference in the log-likelihood ratio sequence is nonlinearly suppressed using the limiting operator.

[0026] Preferably, the parameter adaptive control module further includes a time delay compensation unit, which is used to calculate the baseband processing time delay deviation based on the length of the accumulation period, and use the baseband processing time delay deviation to correct the triggering time of the modulation switching command, so as to eliminate the control lag introduced by long period statistics.

[0027] Preferably, the queue monitoring module is also used to calculate the rate of change of the buffer queue depth; the parameter adaptive control module is used to implement the following emergency preprocessing steps when the rate of change exceeds the preset slope threshold: Step 103: shorten the accumulation period of the sliding integral register to improve the system's response sensitivity to sudden channel deterioration.

[0028] Preferably, the constellation mapping module supports QAM and PSK modulation modes; the modulation switching command includes a power scaling factor for constellation coordinates, and the constellation mapping module adjusts the average power spectral density of the transmitted signal when switching the target modulation order according to the power scaling factor.

[0029] Preferably, the system further includes a protocol feedback module, which encapsulates the channel quality characterization parameters into implicit channel state information and feeds the implicit channel state information back to the transmitter to reduce the overhead ratio of pilot sequences in the physical layer frame structure.

[0030] Preferably, the likelihood ratio extraction module is also used to perform confidence weighting on the log-likelihood ratio sequence to reduce the weighting effect of non-Gaussian impulse noise on the extraction process of channel quality characterization parameters.

[0031] Preferably, the system also includes a closed-loop monitoring module for real-time monitoring of the bit error rate after the target modulation order is switched; when the bit error rate is continuously higher than the preset bit error threshold within 10ms and the buffer queue depth is greater than the preset overflow warning value, the closed-loop monitoring module is used to reset the accumulation period to 1 basic transmission frame period.

[0032] A wireless communication signal transmission method based on adaptive modulation includes the following steps: Step 1001: Obtain the log-likelihood ratio sequence from the received digital baseband signal; Step 1002: Determine the cache queue depth of the media access control layer in real time; Step 1003: Determine the accumulation period of the sliding integral register based on the mapping relationship between the cache queue depth and the baseband statistical time scale. Step 1003 specifically includes the following sub-steps: Sub-step 10031: Identify the preset interval to which the cache queue depth belongs; Sub-step 10032: Match the corresponding sliding integral step size according to the preset interval to determine the accumulation period of the sliding integral register. Step 1004: Using a sliding integral register with an accumulation period, the log-likelihood ratio sequence is accumulated in the time domain to output channel quality characterization parameters. Step 1005: Determine the target modulation order based on the correlation rules between channel quality characterization parameters and buffer queue depth, and generate modulation switching instructions; Step 1006: According to the modulation switching instruction, map the bit stream to be transmitted to the signal constellation diagram corresponding to the target modulation order.

[0033] Example 1: When the system faces data transmission conditions in an industrial IoT environment with high-frequency microsecond-level transient impulse noise and high-concurrency access, spatial electromagnetic interference causes a sharp shift in the physical channel characteristics of the communication link, leading to high-load data backlog at the medium access control layer. Conventional systems with fixed channel impairment perception window lengths for digital baseband processing units cannot balance channel assessment accuracy with burst throughput timeliness, resulting in frequent buffer overflows. The likelihood ratio extraction module obtains the log-likelihood ratio sequence from the received digital baseband signal. The queue monitoring module determines the buffer queue depth of the medium access control layer in real time. The above feature extraction actions establish a correlation between baseband channel perception and link layer queuing status, transforming the logic of maintaining the system's net transmission throughput into a process of dynamically adjusting the digital baseband statistical time scale. The parameter adaptive control module reads the buffer queue... The module identifies the preset interval to which the buffer queue depth belongs, and determines the accumulation period of the sliding integral register by matching the corresponding sliding integral step size according to the preset interval. When the buffer queue depth increases and reaches the set overflow warning value, and the log-likelihood ratio sequence diverges, the parameter adaptive control module outputs the register control word according to the mapping relationship, increases the effective tap number of the shift register to extend the accumulation period, and simultaneously enables the amplitude limiting operator configured on the data path of the sliding integral register, using the set reference amplitude threshold to truncate the amplitude extremum signal caused by non-stationary impulse noise in the log-likelihood ratio sequence. The parameter adaptive control module uses the sliding integral register with the accumulation period to perform time-domain accumulation on the amplitude-limited log-likelihood ratio sequence. The discreteness analysis unit calculates the variance of the sequence in the current sampling window and uses it as the input value of the channel quality characterization parameter.

[0034] Based on the principle of power spectrum additivity of stationary random processes, the receiver's digital baseband processing unit separates independent and uncorrelated noise interference sources. The discreteness analysis unit extracts the slowly varying phase offset of the pilot subcarriers in the log-likelihood ratio sequence. A built-in loop filter smooths the output phase error estimate. A multiplier subtracts the background phase noise variance component caused by local RF crystal drift from the total variance calculation result, outputting the net variance value characterizing the spatial channel fading features as the input value. To accurately isolate the influence of crystal drift, the extraction of the background phase noise variance component is performed in idle time slots. The likelihood ratio extraction module monitors the rotation trend of the known pilot sequence in the complex plane, uses a digital phase-locked loop to extract the cumulative phase error caused by frequency deviation, and calculates the second moment of this error within a static reference window, thereby locking in the inherent background of the local hardware. The variance value, due to the time-dependent temperature stability of crystal oscillator drift over a short period, is stored in a temporary register and subtracted from the total observation variance during subsequent service transmission. This ensures that the target modulation order locked later is only affected by external spatial channel loss. Based on the bit error rate limit model of multi-level orthogonal amplitude modulation theory, the parameter adaptive control module reads the static signal-to-noise ratio mapping threshold array pre-written to the non-volatile storage medium and extracts the proportional coefficient of the current buffer queue depth occupying the maximum buffer capacity. The arithmetic unit uses the proportional coefficient multiplied by a set margin constant to generate a compensation bias. The compensation bias is subtracted from the values ​​of each element in the static signal-to-noise ratio mapping threshold array to generate a multi-level dynamic decision threshold. The parameter adaptive control module compares the net variance value with the multi-level dynamic decision threshold to lock the target modulation order that matches the current channel fading state.

[0035] The parameter adaptive control module determines the target modulation order based on the association rule between channel quality characterization parameters and buffer queue depth, and outputs a modulation switching command. The constellation mapping module maps the bit stream to be transmitted to the signal constellation diagram corresponding to the target modulation order based on the modulation switching command. The buffer queue depth, as an input condition representing the time urgency of the service, changes the accumulation period of the sliding integral register. The extended accumulation period, together with the nonlinear suppression of the amplitude limiting operator, generates an anti-interference smoothing effect, filtering out invalid modulation downsampling commands induced by high-frequency variance jumps in baseband measurements. The synergy between the buffer queue depth and the log-likelihood ratio sequence in the hardware data stream transforms instantaneous burst interference into a statistical hysteresis response on the time axis. While maintaining the bit error rate set by the communication link, the system utilizes the integral delay characteristics of the underlying digital processing logic to suppress the sudden decrease in the number of bits carried by a single symbol, thus solving the problem of malicious interference. To address the constraints between poor channel matching and queuing overflow at the Media Access Control (MAC) layer, and to maintain message delivery stability in high-concurrency node environments, this invention utilizes the symmetric reciprocity of the channel in typical Time Division Duplex (TDD) communication scenarios of the Industrial Internet of Things (IIoT). It uses the downlink quality characteristics obtained by the receiver's likelihood ratio extraction module as a mirror reference for the uplink transmission environment. When the local receiver detects a divergence in the log-likelihood ratio sequence accompanied by local transmit buffer queue backlog, the parameter adaptive control module determines that both bidirectional links are under high-load interference. At this point, the system directly calls the local constellation mapping module to adjust the modulation order of the transmitted signal. This aims to achieve higher demodulation stability by reducing the amount of information carried by a single symbol, thereby alleviating the data backlog pressure at the MACC layer through immediate degradation of the local physical layer strategy without relying on remote feedback.

[0036] Example 2: This example constructs a software-defined radio architecture test platform, including a baseband signal generator, a multipath fading channel simulator, and a receiver digital baseband processing unit composed of a field-programmable gate array (FPGA). Using the multipath fading channel simulator, additive white Gaussian noise with a signal-to-noise ratio of 15dB to 25dB is superimposed based on the Rayleigh fading model. Transient pulse noise with a duration of 10μs and a peak amplitude 3.5 times that of the conventional signal level is periodically injected to reproduce the electromagnetic pulse impact state present in high-density industrial IoT. The initial value of the accumulation period of the sliding integral register in the parameter adaptive control module is set to balance the real-time capture of channel state changes with the unbiasedness of large-sample statistics. When the rate of change of the buffer queue depth output by the queue monitoring module is lower than the preset slope threshold, the accumulation period approaches the upper limit of the value range, obtaining a smoothed variance estimate under a stable channel. Based on this mapping rule, the system selects 128 symbol periods as the baseline accumulation period in the initial state, limiting the initial time scale of baseband channel sensing.

[0037] A multi-dimensional testing system was established, including a control group and three experimental groups. The control group used a static channel evaluation window of 128 symbol periods, removing the clipping operator. The first, second, and third experimental groups all used a parameter adaptive control module, setting gradient test states with buffer queue depth occupancy rates of 20%, 60%, and 90%, respectively. During the test period with injected transient impulse noise, the original log-likelihood ratio sequence output by the likelihood ratio extraction module was obtained, and a deviation distortion of 45.8 in the instantaneous variance of the original sequence was observed. In the control group, this distortion caused drastic fluctuations in the channel quality characterization parameters, triggering the system to reduce the modulation order from 64QAM to 16QAM. In the first and third experimental groups... In the second experimental group, the parameter adaptive control module output register control words respectively, setting the effective number of taps of the shift register to 128 and 64 respectively. The amplitude limiting operator on the data path was used to cut off pulse signals with amplitudes exceeding the set threshold, so that the log-likelihood ratio sequence variance input to the discreteness analysis unit was maintained at 4.2 and 4.6 respectively. In the third experimental group, the buffer queue depth reached 90% and the rate of change exceeded the preset slope threshold. The parameter adaptive control module reduced the effective number of taps to 32. Due to the constraint of the reduced sample size, the obtained sequence variance increased slightly to 5.3. The system maintained 64QAM modulation state. The hardware mechanism of the above-mentioned amplitude limiting operator combined with dynamic sliding step size filtered out the modulation down-order misjudgment signal caused by extreme noise.

[0038] The media access control layer packet delivery rate and system bit error rate were obtained after each test group ran continuously for 1000ms. The test data showed that the average packet delivery rate of the control group was 78.4%, with buffer overflow and packet loss. The packet delivery rates of the first and second test groups reached 99.1% and 98.7%, respectively. The third test group was tested under extreme conditions, forcibly reducing the number of effective taps to below 16. The obtained channel quality characterization parameters deviated from the actual channel state, and the bit error rate increased exponentially and non-linearly, exceeding the 0.5% system tolerance threshold. The physical boundary for selecting the lower limit of the number of effective taps was established. The delay compensation unit in the parameter adaptive control module triggered the modulation switching command in advance based on the calculated 3.2μs baseband processing delay deviation, eliminating the control lag error introduced by long-cycle integration. The system directly correlated the data backlog with the baseband statistical time scale and dynamically reconstructed the integration horizon length of the sliding integral register according to the queue depth. Under the condition of maintaining the bit error rate constraint set in the communication link, the system suppressed the data flow overflow and loss phenomenon in the high-concurrency node access environment.

[0039] Example 3: When the system faces a sudden surge in concurrent transmission from high-density industrial IoT nodes, the packet arrival rate of the media access control layer exhibits a non-stationary Poisson distribution, and the buffer queue depth changes drastically within a very short time. If the system uses statically preset association mapping rules to adjust the baseband channel sensing window, it cannot accurately match the dynamic evolution of the physical layer processing rate and the link layer backlog rate, leading to control parameter switching lag and packet overflow. To establish a quantization mapping mechanism between the buffer queue depth and the sliding integral register accumulation period, the parameter adaptive control module incorporates a defined parameter calibration architecture; and obtains the maximum buffer size of the system's media access control layer. The capacity and single-symbol processing time of the digital baseband processing unit at the receiving end are considered. Based on the maximum buffer capacity, three intervals are divided according to an arithmetic progression. The first depth threshold, the second depth threshold, and the overflow warning value are established in sequence to construct the hard physical boundary for threshold determination. During the real-time transmission period, the queue monitoring module extracts the current buffer queue depth at a set sampling period, and the parameter adaptive control module determines the distribution state of the buffer queue depth. When the buffer queue depth is lower than the first depth threshold, the parameter adaptive control module outputs the basic register control word and sets the effective number of taps of the shift register to the maximum available hardware extreme value to obtain an extremely long integration window.

[0040] When the cache queue depth falls between the second depth threshold and the overflow warning value, an emergency defense degradation step is triggered. The parameter adaptive control module calculates the target tap number using a pre-configured exponential decay function, truncates the decimal part, rounds it down, and outputs the corresponding register control word. The delay compensation unit then calculates the target tap number according to the formula... Calculate the baseband processing delay deviation; where, This refers to the baseband processing delay deviation. The current number of valid taps; For single-symbol processing time, the delay compensation unit uses the acquired baseband processing delay deviation to pre-shift the timing of the modulation switching command triggered by the constellation mapping module. This pre-shifting of the trigger timing is essentially a phase pre-compensation for subsequent scheduling cycles after the current physical frame sequence. In the actual hardware execution process, the parameter adaptive control module inputs the calculated baseband processing delay deviation Δt to the underlying hardware timer. Before receiving the next frame synchronization signal, the timer pre-deducts a clock cycle count equivalent to Δt, thus enabling the constellation mapping module's enable logic earlier than the standard frame start boundary. This historical statistical-based timing... The advance cancellation of the future trigger moment ensures that the modulation command output after long-period sliding integral operation is precisely aligned in the time domain with the corresponding data stream to be transmitted at the physical signal RF output end. This compensates for the inherent link lag caused by the digital signal processing stage, ensuring alignment of the underlying RF time slot channels at both ends of the transmitter and receiver. When the protocol feedback module encapsulates implicit channel state information, it writes the physical frame sequence number generated by the medium access control layer into the data packet header structure. The transmitter parses the physical frame sequence number in the received message, tracks the timestamp using an internal symbol counter, and increments the hardware clock to the corresponding physical frame start boundary time, synchronously enabling modulation matching the target modulation order. The power scaling factor converts the bias voltage parameters of the RF power amplifier. Addressing the feedback lag issue caused by microsecond-level phase transitions in industrial environments, this invention encapsulates channel quality characterization parameters within the control frame of the Media Access Control layer via a protocol feedback module. This implicit feedback replaces the traditional explicit physical layer CSI reporting. In the processing flow, the transmitter does not blindly execute received modulation commands. Instead, it compares the channel state sampling point at the time the command was generated with the current clock offset, based on the physical frame sequence number within the message. If the offset is within the coherent time range, fine-grained modulation switching is performed; if the offset is too large, a closed-loop monitoring module intervenes, adjusting the signal according to the command. The queue backlog weight carried in the order forces a conservative reduction in order, thereby using the urgency information on the service side to offset the decision-making risk caused by the offset of channel physical characteristics. The above process, which defines the threshold benchmark based on hardware capacity and dynamically calculates the number of effective taps using an exponential decay function, eliminates the dependence of multi-dimensional parameter adjustment on empirical values. The modulation switching action is performed in advance based on the calculated baseband processing delay deviation, which offsets the inherent statistical lag caused by long-period sliding integral operation. Under the extreme constraint of the rapid increase in service traffic, the system realizes real-time dynamic reduction of the modulation order, avoiding the timing misalignment between the underlying baseband channel evaluation period and the upper-layer queue rapid backlog period.

[0041] Example 4: When the system faces early deployment conditions where there are spatial differences in the distribution of background noise, the parameter adaptive control module initiates the environmental noise baseline calibration procedure before establishing a service connection. It controls the receiving end digital baseband processing unit to collect background electromagnetic signals from idle channels. The likelihood ratio extraction module obtains the background noise log-likelihood ratio sequence from the background electromagnetic signals. The discreteness analysis unit calculates the background standard deviation of this sequence within a set time window. The parameter adaptive control module then applies the formula... Calculate the reference amplitude threshold; where, As the reference amplitude threshold, The baseline standard deviation, The preset proportional coefficient has a value range of 2.5 to 4.0; the parameter adaptive control module writes the acquired reference amplitude threshold into the internal register of the amplitude limiting operator, replacing the static judgment threshold.

[0042] After baseline calibration, the control parameter mapping rule construction step is triggered. The test sequence generator injects a message stream with a gradient increase into the medium access control layer. The queue monitoring module outputs the buffer queue depth corresponding to each injection rate. The parameter adaptive control module traverses the control combination of effective tap number and modulation order at each depth state. The internal verification unit records the bit error rate and message delivery rate corresponding to each control combination, eliminates combinations with bit error rate exceeding the system tolerance, and extracts the effective tap number and target modulation order that maximize the message delivery rate as the preferred control parameters. The parameter adaptive control module stores the buffer queue depth and preferred control parameters in a hardware lookup table. During system operation, the control parameters matching the current operating condition are retrieved from the hardware lookup table based on the real-time queue accumulation status.

[0043] Example 5: When the system faces an initial offline debugging condition where the initial control parameter matrix is ​​empty, the queue monitoring module extracts the total bit capacity of the media access control layer hardware buffer and the set maximum tolerable queuing delay; the queue monitoring module multiplies the total bit capacity by the margin tolerance ratio to calculate the effective buffer capacity; the queue monitoring module divides the effective buffer capacity by the maximum tolerable queuing delay to obtain the baseline accumulation rate in bits per second; the queue monitoring module writes the baseline accumulation rate into an internal register and uses it as a preset slope threshold for judging the queue backlog situation, thus constructing a physical criterion for queue status monitoring.

[0044] The write action triggering parameter adaptive control module starts the algorithm parameter configuration steps for the preset slope threshold; the parameter adaptive control module extracts the available buffer margin between the second depth threshold and the overflow warning value, uses the available buffer margin and the current cache queue depth to construct a dynamic independent variable, calculates the product of the maximum available hardware tap number and the nonlinear decay factor, and determines the target tap number. The calculation formula is as follows: ;in, The target number of taps. This represents the maximum number of available taps in the shift register. It is a natural constant; The attenuation control coefficient is... This represents the current cache queue depth. The second depth threshold, As an overflow warning value, the parameter adaptive control module inputs the output result to the truncation and rounding operator to obtain the corresponding integer register control word; the internal verification unit injects a test message into the media access control layer to verify that when the current buffer queue depth approaches the overflow warning value, the number of effective taps of the shift register converges to the set minimum working threshold according to the nonlinear accelerated decrease law; the system solidifies the dynamic order reduction mathematical path to deal with extreme value states, and maintains the processing accuracy of the modulation switching algorithm in the runtime domain by using the determined attenuation mapping logic.

[0045] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.

Claims

1. A wireless communication signal transmission system based on adaptive modulation, characterized in that, include: The likelihood ratio extraction module is used to obtain the log-likelihood ratio sequence from the received digital baseband signal; The queue monitoring module is used to determine the cache queue depth of the media access control layer in real time. The parameter adaptive control module is used to determine the accumulation period of the sliding integral register based on the mapping relationship between the buffer queue depth and the baseband statistical time scale. The parameter adaptive control module achieves parameter adjustment through the following steps: Step 101, identify the preset interval to which the buffer queue depth belongs; Step 102, match the corresponding sliding integral step size according to the preset interval to determine the accumulation period of the sliding integral register; The sliding integral register includes multiple shift registers with different delay periods and an accumulator configured with a limiting operator; The parameter adaptive control module is used to implement the following refinement steps: Step 1021, when the buffer queue depth increases, increase the number of effective taps of the shift register to extend the accumulation period; Step 1022, use the limiting operator to perform nonlinear suppression of the impulse interference amplitude in the log-likelihood ratio sequence; The parameter adaptive control module is used to use the sliding integral register with the accumulation period to perform time-domain accumulation of the log-likelihood ratio sequence to output channel quality characterization parameters; The parameter adaptive control module is also used to determine the target modulation order according to the association rule between the channel quality characterization parameters and the buffer queue depth, and output modulation switching instructions; The constellation mapping module is used to map the bit stream to be transmitted to the signal constellation diagram corresponding to the target modulation order according to the modulation switching command.

2. The wireless communication signal transmission system based on adaptive modulation according to claim 1, characterized in that, The likelihood ratio extraction module includes a dispersion analysis unit, which is used to calculate the variance of the log-likelihood ratio sequence within the sampling window; The parameter adaptive control module uses variance as the input value for the channel quality characterization parameter.

3. The wireless communication signal transmission system based on adaptive modulation according to claim 1, characterized in that, The parameter adaptive control module also includes a time delay compensation unit. The time delay compensation unit is used to calculate the baseband processing time delay deviation based on the length of the accumulation period, and to use the baseband processing time delay deviation to correct the triggering time of the modulation switching command, so as to eliminate the control lag introduced by long period statistics.

4. The wireless communication signal transmission system based on adaptive modulation according to claim 1, characterized in that, The queue monitoring module is also used to calculate the rate of change of the buffer queue depth; the parameter adaptive control module is used to implement the following emergency preprocessing steps when the rate of change exceeds the preset slope threshold: Step 103, shorten the accumulation period of the sliding integral register to improve the system's response sensitivity to sudden channel deterioration.

5. The wireless communication signal transmission system based on adaptive modulation according to claim 1, characterized in that, The constellation mapping module supports QAM and PSK modulation modes; the modulation switching command includes a power scaling factor for constellation coordinates. The constellation mapping module adjusts the average power spectral density of the transmitted signal when switching the target modulation order based on the power scaling factor.

6. The wireless communication signal transmission system based on adaptive modulation according to claim 1, characterized in that, The system also includes a protocol feedback module, which encapsulates channel quality characterization parameters into implicit channel state information and feeds the implicit channel state information back to the transmitter to reduce the overhead ratio of pilot sequences in the physical layer frame structure.

7. The wireless communication signal transmission system based on adaptive modulation according to claim 1, characterized in that, The likelihood ratio extraction module is also used to perform confidence weighting on the log-likelihood ratio sequence to reduce the weighting effect of non-Gaussian impulse noise on the extraction process of channel quality characterization parameters.

8. The wireless communication signal transmission system based on adaptive modulation according to claim 1, characterized in that, The system also includes a closed-loop monitoring module, which is used to monitor the bit error rate after the target modulation order is switched in real time. When the bit error rate is higher than the preset bit error threshold for 10ms and the buffer queue depth is greater than the preset overflow warning value, the closed-loop monitoring module is used to reset the accumulation period to 1 basic transmission frame period.

9. A method for transmitting wireless communication signals based on adaptive modulation, used to implement the wireless communication signal transmission system based on adaptive modulation as described in claim 1, characterized in that, Includes the following steps: Step 1001: Obtain the log-likelihood ratio sequence from the received digital baseband signal; Step 1002: Determine the cache queue depth of the media access control layer in real time; Step 1003: Based on the mapping relationship between the buffer queue depth and the baseband statistical time scale, determine the accumulation period of the sliding integral register. Step 1003 specifically includes the following sub-steps: Sub-step 10031: Identify the preset interval to which the buffer queue depth belongs; Sub-step 10032: Match the corresponding sliding integral step size according to the preset interval to determine the accumulation period of the sliding integral register; The sliding integral register includes multiple shift registers with different delay periods and an accumulator configured with a limiting operator; The parameter adaptive control module is used to implement the following refined steps: Step 1021: When the buffer queue depth increases, increase the number of effective taps of the shift register to extend the accumulation period; Step 1022: Use the limiting operator to perform nonlinear suppression of the impulse interference amplitude in the log-likelihood ratio sequence; Step 1004: Using a sliding integral register with an accumulation period, the log-likelihood ratio sequence is accumulated in the time domain to output channel quality characterization parameters. Step 1005: Determine the target modulation order based on the correlation rules between channel quality characterization parameters and buffer queue depth, and generate modulation switching instructions; Step 1006: According to the modulation switching instruction, map the bit stream to be transmitted to the signal constellation diagram corresponding to the target modulation order.

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