Single carrier frequency domain balanced transmission system for remote unmanned aerial vehicle image transmission

Abstract

The invention relates to the technical field of data transmission, in particular to a single-carrier frequency domain balanced transmission system for remote unmanned aerial vehicle image transmission, which comprises a transmitting end module, a receiving end module and an auxiliary module, compared with the defects that in the prior art, a fixed coding mode is mostly adopted in the aspect of error correction coding and is difficult to adapt to a dynamically changing channel environment, so that the anti-interference capability is insufficient, the transmission efficiency is low and the like under a complex channel condition, the technical scheme that the Polar code and the LDPC code are selected according to the channel state to carry out error correction coding is adopted, and the error correction coding efficiency is improved. Dynamically selecting a coding scheme based on a preset SNR threshold value and a machine learning model; the code rate of the Polar code is adjusted according to SNR, a reliable bit position table is preloaded, and CRC is combined to assist SCL decoding; the QC-LDPC code is used for the LDPC code, layered decoding reduces delay, incremental redundancy retransmission is triggered in a severe channel, different channel environments can be flexibly adapted, the coding strategy is dynamically adjusted, the transmission efficiency and reliability are improved, and meanwhile the low power consumption requirement is considered.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data transmission, and in particular to a single-carrier frequency domain equalization transmission system for remote unmanned aerial vehicle image transmission. BACKGROUND

[0002] With the rapid development of unmanned aerial vehicle technology, its application in the field of remote image transmission (image transmission) is continuously deepening, and has been widely penetrated into many important fields such as military reconnaissance, disaster relief, geographic mapping, agricultural monitoring, and film shooting. However, the unmanned aerial vehicle is often in a complex and changeable wireless channel environment during flight, and the signal transmission faces multiple challenges such as multipath fading, Doppler shift, co-frequency interference and noise, which seriously restricts the reliability, real-time performance and clarity of image transmission.

[0003] In the existing unmanned aerial vehicle image transmission technology, error correction coding, as a key means to improve data transmission robustness, still generally adopts a fixed coding strategy, that is, a single coding algorithm (such as convolution code or LDPC code) and a preset fixed code rate are used. This static coding mechanism lacks the ability to adapt to the dynamic changes of the channel state. When the unmanned aerial vehicle moves at high speed, causing significant Doppler shift, or flies through complex environments such as cities and forests, encountering strong multipath effect and interference, the fixed coding scheme cannot flexibly adjust the redundancy and error correction strength, resulting in a sharp rise in bit error rate, a decrease in effective transmission rate, and even phenomena such as video stuttering, screen flickering or interruption, which cannot meet the needs of high-quality image transmission applications.

[0004] In the face of increasing requirements for image resolution and frame rate, as well as strict requirements in high-reliability, low-latency application scenarios (such as real-time target tracking, precise operation, etc.), the shortcomings of traditional image transmission technology in adaptability and intelligent anti-interference are increasingly prominent. Therefore, an intelligent transmission technology that can real-time perceive channel changes and dynamically adjust coding and modulation strategies is urgently needed to significantly improve the transmission efficiency, anti-interference ability and overall reliability of the system in complex environments, and to promote the development of unmanned aerial vehicle image transmission technology in a more efficient, stable and safe direction. SUMMARY

[0005] In order to overcome the problems raised in the above background art, the present application proposes a single-carrier frequency domain equalization transmission system for remote unmanned aerial vehicle image transmission.

[0006] The technical solution of the present application is: a single-carrier frequency domain equalization transmission system for remote unmanned aerial vehicle image transmission, comprising: A transmitting end module is responsible for compressing, encoding and modulating image data into a single-carrier signal, inserting a cyclic prefix and transmitting radio frequency to ensure that the signal is resistant to multipath interference and adapts to wireless channel transmission. The receiving end module is used for synchronization, cyclic prefix removal and frequency domain equalization of the received signal, demodulation and decoding of the original image data, overcoming the influence of Doppler frequency offset and channel distortion; The auxiliary module dynamically optimizes modulation parameters, inserts pilot signals to assist synchronization and channel estimation, improves security and reliability through encryption and retransmission mechanisms, and manages power consumption to prolong battery life.

[0007] As a preferred embodiment, the transmitting end module specifically comprises: A11: a source encoding module, responsible for compressing and encoding image and video data collected by the unmanned aerial vehicle camera; A12: a channel encoding module, used for using error correction coding technology to enhance transmission reliability and resist channel noise and interference; A13: a modulation module, used for mapping the encoded data to symbols and dynamically adjusting the modulation mode according to the channel condition; A14: a single carrier modulation module, used for generating a single carrier signal and converting frequency domain symbols to time domain signals through inverse fast Fourier transform; A15: a cyclic prefix insertion module, used for adding a cyclic prefix in front of the time domain signal to eliminate inter-symbol interference caused by multipath interference; A16: a radio frequency front end module, including digital-to-analog conversion, frequency up-conversion, power amplifier and transmitting antenna, used for converting baseband signals to high frequency radio frequency signals and transmitting them.

[0008] As a preferred embodiment, the receiving end module specifically comprises: A21: a radio frequency front end module, used for receiving antenna, low noise amplifier, frequency down-conversion, analog-to-digital conversion, and restoring radio frequency signals to baseband digital signals; A22: a cyclic prefix removal module, used for removing the cyclic prefix and retaining the valid symbol data; A23: an FFT module, used for converting time domain signals to frequency domain through FFT to prepare for frequency domain equalization; A24: a channel estimation and equalization module, used for estimating channel response using pilot or training sequence and compensating channel distortion through equalization algorithm to eliminate multipath effect; A25: a demodulation module, used for demodulating the equalized frequency domain symbols to bit stream; A26: a channel decoding module, used for decoding error correction code to restore the original data stream; A27: a source decoding module, used for decompressing image and video data to restore them to a displayable format.

[0009] As a preferred embodiment, the receiving end module further comprises a synchronization module, and the functions of the synchronization module include: A31: timing synchronization, determining the symbol starting position through training sequence and pilot; A32: Frequency synchronization, compensating Doppler frequency offset caused by high-speed movement of UAV; A33: Phase synchronization, eliminating carrier phase deviation.

[0010] As preferred, the auxiliary module specifically includes: A41: Adaptive control module, for dynamically adjusting modulation and coding scheme and transmission power parameters according to channel state information, optimizing transmission efficiency; A42: Pilot and training sequence insertion module, for inserting known pilot and training sequence in data frame, supporting synchronization and channel estimation at receiving end; A43: Re-transmission and redundancy module, for triggering automatic retransmission request and hybrid ARQ mechanism under poor channel conditions; A44: Encryption and security module, for encrypting and authenticating transmission data; A45: Power consumption management module, for optimizing transmission power and circuit power consumption, prolonging the endurance time of UAV.

[0011] As preferred, the sending end module specifically includes when working: S11: Data compression and packaging, compressing original image and video data through source coding, dividing into transmission blocks and adding check code; S12: Redundancy coding, selecting Polar code and LDPC code for error correction coding according to channel state, improving anti-interference ability; S13: Symbol mapping and modulation, mapping the coded binary data into complex symbols including QPSK and 16QAM, dynamically adjusting modulation order; S14: Generating single carrier signal, converting frequency domain symbol to time domain baseband signal through IFFT, setting zero to center frequency point to suppress spectral leakage; S15: Anti-multipath processing, inserting cyclic prefix at the head of time domain signal to eliminate inter-symbol interference caused by multipath propagation; S16: Radio frequency transmission; converting baseband signal to analog signal through DAC, up-converting to target frequency band, and transmitting through antenna after power amplification.

[0012] As preferred, the receiving end module specifically includes when working: S21: Signal reception and down-conversion, antenna capturing radio frequency signal, low-noise amplification, down-conversion and ADC sampling, restoring to digital baseband signal; S22: Synchronization calibration, including locating symbol starting position through sliding correlation peak of training sequence; estimating and compensating Doppler frequency offset through pilot; eliminating residual deviation by using Costas loop to track carrier phase; S23: Removing cyclic prefix, stripping off cyclic prefix at the head of signal, and retaining effective symbol data block; S24: Frequency domain conversion and equalization, perform FFT to convert time domain signal to frequency domain, estimate channel response based on pilot, compensate distortion using MMSE algorithm; S25: Demodulation and decoding, determine symbols as bit stream according to constellation, recover original data through SCL decoding, and check CRC to confirm integrity; S26: Image restoration, recombine data blocks and decompress, output displayable video frames through H.265 decoder.

[0013] As preferred, the auxiliary module includes, when working, specifically: S31: Dynamic parameter optimization, real-time monitoring of channel state, adjustment of modulation and coding scheme and transmission power, balance of rate and reliability.

[0014] S32: Pilot and training sequence management, periodic insertion of pilot symbols and special training sequences in data frames, auxiliary synchronization and channel estimation at receiving end; S33: Re-transmission and redundancy control, trigger HARQ mechanism, retransmit incremental redundancy data in poor channel, and improve fault tolerance rate in combination with FEC; S34: Security encryption, encrypt data stream using AES-256, and implement identity authentication through HMAC-SHA1; S35: Power consumption optimization, dynamically reduce transmission power according to battery status, turn off radio frequency circuit when idle, and prolong the endurance time of unmanned aerial vehicle.

[0015] As preferred, when selecting Polar code and LDPC code for error correction coding according to channel state to improve anti-interference ability, it specifically includes: S41: Channel assessment and feedback: receiving end real-time monitoring of SNR, Doppler shift, feedback to sending end through control channel; S42: Coding scheme decision, based on preset SNR threshold and machine learning model, dynamically select Polar code and LDPC code; S43: Polar code configuration, adjust code rate according to SNR, pre-load reliable bit position table, and assist SCL decoding with CRC; S44: LDPC code configuration, use QC-LDPC code, hierarchical decoding to reduce delay, trigger incremental redundancy retransmission in poor channel; S45: Encoding switching and implementation, insert encoding type identifier, realize low delay switching by hardware multiplexing FPGA; S46: Performance verification and optimization, offline simulation to verify BER boundary, online threshold tuning, prefer LDPC code in low power mode to prolong endurance.

[0016] As preferred, when adjusting code rate according to SNR, the principle formula is: ; Where R is the code rate, k is the information bit length, n is the length of the encoded codeword, and f(SNR) indicates that the code rate is a function of the signal-to-noise ratio.

[0017] The beneficial effects of this invention are: 1. Compared to existing technologies that mostly use fixed coding methods for error correction, which are difficult to adapt to dynamically changing channel environments and result in insufficient anti-interference capability and low transmission efficiency under complex channel conditions, this solution adopts a technical approach that selects Polar codes and LDPC codes for error correction coding based on channel conditions. Specifically, it monitors and feeds back channel parameters in real time through channel assessment and feedback; dynamically selects the coding scheme based on a preset SNR threshold and machine learning model; adjusts the code rate of Polar codes according to SNR, preloads a reliable bit position table, and combines CRC to assist SCL decoding; uses QC-LDPC codes and layered decoding for LDPC codes to reduce latency and trigger incremental redundant retransmission under adverse channel conditions; inserts a coding type identifier, and uses FPGA for low-latency switching; verifies the BER boundary through offline simulation, optimizes the threshold online, and prioritizes LDPC codes in low-power mode to extend battery life. This solution has significant advantages, can flexibly adapt to different channel environments, dynamically adjust the coding strategy, effectively improve anti-interference capability, reduce bit error rate, improve transmission efficiency and reliability, and at the same time take into account low power consumption requirements and extend device battery life, making it particularly suitable for scenarios with high requirements for communication quality and stability. 2. Compared to existing technologies where the receiver module lacks a comprehensive and effective synchronization mechanism, inaccurate timing, frequency, and phase synchronization in complex communication environments can easily lead to signal demodulation errors, data loss, and affect communication quality and stability. This solution adds a synchronization module to the receiver module, employing timing synchronization to determine the symbol start position through training sequences and pilots, frequency synchronization to compensate for Doppler frequency offset caused by the high-speed movement of the UAV, and phase synchronization to eliminate carrier phase deviation. This solution has significant advantages: timing synchronization can accurately determine the symbol start position, ensuring the accuracy of subsequent signal processing; frequency synchronization can effectively compensate for Doppler frequency offset, avoiding signal distortion and demodulation errors caused by frequency shift; and phase synchronization can eliminate carrier phase deviation, ensuring signal phase stability. This comprehensively improves the receiver module's ability to accurately receive and process signals, enhancing the reliability and stability of the communication system, and is particularly suitable for the communication needs of high-speed mobile scenarios such as UAVs. 3, The radio frequency signal is captured by the antenna, amplified by low noise, down-converted and sampled by ADC to restore the digital baseband signal, providing a reliable data basis for subsequent processing; synchronization calibration uses training sequences, pilots and Costas loops to realize symbol starting position positioning, Doppler frequency offset compensation and carrier phase deviation elimination, ensuring accurate signal synchronization and improving demodulation accuracy; removing the cyclic prefix of the signal head to retain the effective symbol data block and avoid interference with subsequent processing; frequency domain conversion and equalization convert the time domain signal to the frequency domain, estimate the channel response based on the pilot, and compensate for distortion using the MMSE algorithm to effectively combat channel multipath effects and noise interference; demodulation and decoding determine the symbol as a bit stream according to the constellation diagram, recover the original data through SCL decoding and check the CRC to confirm the integrity, and ensure accurate data recovery; image restoration reorganizes the data block and decompresses it through the H.265 decoder to output a displayable video frame, allowing users to intuitively obtain the required information, and the entire process ensures that the receiving end can efficiently and accurately receive and process signals; 4, In order to solve the problem of resource waste or low transmission efficiency caused by the difficulty of traditional image transmission system to adapt to channel changes by adopting fixed modulation and coding strategy, the adaptive control module is introduced, which can monitor the channel state in real time and dynamically adjust the modulation and coding scheme and transmit power, thereby optimizing the spectral efficiency and link performance while ensuring transmission reliability; 5, In order to solve the problem of limited endurance time caused by the extensive power consumption management of the existing unmanned aerial vehicle image transmission system, the power consumption management module dynamically optimizes the transmit power and circuit switching strategy, effectively reduces the system energy consumption while maintaining the communication quality, significantly prolongs the mission endurance time of the unmanned aerial vehicle, and improves the practicality and sustainable operation ability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0018] Fig. 1 The structure schematic diagram of the single-carrier frequency domain equalization transmission system for remote unmanned aerial vehicle image transmission of the present application is shown. Fig. 2 The working flowchart of the sending end module in the single-carrier frequency domain equalization transmission system for remote unmanned aerial vehicle image transmission of the present application is shown. DETAILED DESCRIPTION

[0019] The present application will be further described below in conjunction with the drawings and examples.

[0020] Please refer to Figs. 1-2 The present application provides an embodiment: a single-carrier frequency domain equalization transmission system for remote unmanned aerial vehicle image transmission, comprising: The sending end module is responsible for compressing, encoding and modulating the image data into a single-carrier signal, inserting a cyclic prefix and transmitting it by radio frequency, ensuring that the signal is resistant to multipath interference and suitable for wireless channel transmission; The receiving end module is used for synchronization, cyclic prefix removal and frequency domain equalization of the received signal, demodulation and decoding to restore the original image data, overcoming the influence of Doppler frequency offset and channel distortion; The auxiliary module dynamically optimizes modulation parameters, inserts pilot signals to assist synchronization and channel estimation, improves security and reliability through encryption and retransmission mechanism, and manages power consumption to prolong the endurance.

[0021] As described above, the transmitting end module in the application compresses, encodes, modulates and adds a cyclic prefix to the image data and transmits it by radio frequency, which can effectively resist multipath interference and adapt to wireless channels; the receiving end module synchronizes, removes the cyclic prefix, equalizes the frequency domain, demodulates and decodes the signal, which can overcome Doppler frequency offset and channel distortion; the auxiliary module dynamically optimizes modulation parameters, inserts pilot signals to assist synchronization and channel estimation, improves security and reliability through encryption and retransmission mechanism, and manages power consumption to prolong the endurance, which overall guarantees the efficient, stable, safe and long-endurance operation of remote unmanned aerial vehicle image transmission.

[0022] As a preferred, the transmitting end module specifically includes: A11: a source encoding module, responsible for compressing and encoding image and video data collected by the unmanned aerial vehicle camera; A12: a channel encoding module, used for using error correction coding technology to enhance transmission reliability and resist channel noise and interference; A13: a modulation module, used for mapping the encoded data to symbols and dynamically adjusting the modulation mode according to the channel condition; A14: a single carrier modulation module, used for generating a single carrier signal and converting frequency domain symbols to time domain signals through inverse fast Fourier transform; A15: a cyclic prefix insertion module, used for adding a cyclic prefix in front of the time domain signal to eliminate inter-symbol interference caused by multipath interference; A16: a radio frequency front end module, including digital-to-analog conversion, frequency up-conversion, power amplifier and transmitting antenna, used for converting baseband signals to high frequency radio frequency signals and transmitting them.

[0023] As described above, the source coding module in the application compresses and encodes the image and video data collected by the unmanned aerial vehicle camera, effectively reducing the data volume and improving the transmission efficiency; the channel coding module uses error correction coding technology to enhance the transmission reliability, effectively against channel noise and interference, and ensures accurate data transmission; the modulation module dynamically adjusts the modulation mode according to the channel conditions, maps the encoded data to symbols, and optimizes the transmission performance; the single carrier modulation module generates a single carrier signal, and converts the frequency domain symbol to a time domain signal through inverse fast Fourier transform, meeting the specific transmission requirements; the cyclic prefix insertion module adds a cyclic prefix in front of the time domain signal to eliminate the inter-symbol interference caused by multipath interference and improve the signal quality; the radio frequency front end module converts the baseband signal to a high frequency radio frequency signal through digital-to-analog conversion, frequency up-conversion, power amplifier and transmitting antenna, and transmits the signal, realizing effective radiation transmission of the signal and ensuring that the entire sending end module can efficiently and reliably complete the data sending task.

[0024] As preferred, the receiving end module specifically includes: A21: a radio frequency front end module for receiving antenna, low noise amplifier, frequency down-conversion, analog-to-digital conversion, and restoring the radio frequency signal to baseband digital signal; A22: a cyclic prefix removal module for removing the cyclic prefix and retaining the effective symbol data; A23: an FFT module for converting the time domain signal to the frequency domain through FFT, preparing for frequency domain equalization; A24: a channel estimation and equalization module for estimating the channel response by using pilot or training sequence, compensating for channel distortion through equalization algorithm, and eliminating multipath effect; A25: a demodulation module for demodulating the equalized frequency domain symbol to bit stream; A26: a channel decoding module for decoding error correction code and recovering the original data stream; A27: a source decoding module for decompressing the image and video data and restoring them to a displayable format.

[0025] As described above, the radio frequency front-end module in the application accurately restores the radio frequency signal to the baseband digital signal through the receiving antenna, low noise amplifier, down-conversion and analog-to-digital conversion, and provides a reliable data basis for subsequent processing; the cyclic prefix removal module removes the cyclic prefix and accurately retains the valid symbol data, avoids the interference of the cyclic prefix on the subsequent processing, and improves the accuracy of data processing; the FFT module converts the time domain signal to the frequency domain through FFT, fully prepares for the frequency domain equalization, and helps to more efficiently process the signal; the channel estimation and equalization module estimates the channel response by using the pilot or training sequence, compensates for the channel distortion through the equalization algorithm, effectively eliminates the multipath effect, and improves the signal quality; the demodulation module demodulates the equalized frequency domain symbol into a bit stream, and accurately restores the signal; the channel decoding module decodes the error correction code, restores the original data stream, and ensures the integrity and accuracy of the data; the source decoding module decompresses the image and video data, restores it to a displayable format, and enables the user to intuitively obtain the required information. The entire receiving end module works cooperatively to ensure that the signal can be efficiently and accurately received and processed.

[0026] As a preferred, the receiving end module further comprises a synchronization module, and the functions of the synchronization module include: A31: timing synchronization, determining the symbol starting position through the training sequence and the pilot; A32: frequency synchronization, compensating for the Doppler frequency offset caused by the high-speed movement of the unmanned aerial vehicle; A33: phase synchronization, eliminating the carrier phase deviation.

[0027] As described above, the application has the advantages that the receiving end module is provided with a synchronization module, timing synchronization is used to determine the symbol starting position through the training sequence and the pilot, frequency synchronization compensates for the Doppler frequency offset caused by the high-speed movement of the unmanned aerial vehicle, and phase synchronization eliminates the carrier phase deviation. The timing synchronization can accurately determine the symbol starting position, ensuring the accuracy of subsequent signal processing; the frequency synchronization can effectively compensate for the Doppler frequency offset, avoiding signal distortion and demodulation errors caused by frequency offset; and the phase synchronization can eliminate the carrier phase deviation, ensuring the stability of the signal phase, thereby improving the accuracy of the receiving end module in receiving and processing the signal, enhancing the reliability and stability of the communication system, and being particularly suitable for the communication needs in the high-speed moving scenario of the unmanned aerial vehicle.

[0028] As a preferred, the auxiliary module specifically includes: A41: an adaptive control module, used for dynamically adjusting the modulation and coding scheme and the transmission power parameter according to the channel state information, and optimizing the transmission efficiency; A42: pilot and training sequence insertion module, for inserting known pilot and training sequence in data frame, supporting receiver synchronization and channel estimation; A43: retransmission and redundancy module, for triggering automatic repeat request and hybrid ARQ mechanism under poor channel conditions; A44: encryption and security module, for encrypting and identity authentication of transmission data; A45: power consumption management module, for optimizing transmission power and circuit power consumption, prolonging the endurance time of unmanned aerial vehicle.

[0029] As described above, the adaptive control module in the application dynamically adjusts the modulation and coding scheme and the transmission power parameter according to the channel state information, which can flexibly adapt to different channel environments, effectively optimize the transmission efficiency, and improve the communication quality; the pilot and training sequence insertion module inserts known pilot and training sequence in the data frame, which provides strong support for receiver synchronization and channel estimation, and guarantees accurate signal reception and processing; the retransmission and redundancy module triggers automatic repeat request and hybrid ARQ mechanism under poor channel conditions, reduces the risk of data loss, and enhances the reliability of data transmission; the encryption and security module encrypts and identity authenticates the transmission data, ensures the security and integrity of the data, and prevents information leakage and malicious attacks; the power consumption management module optimizes the transmission power and circuit power consumption, prolongs the endurance time of the unmanned aerial vehicle, improves the work efficiency and endurance of the unmanned aerial vehicle, and enables the unmanned aerial vehicle to run more stably, efficiently, safely and persistently in the communication process.

[0030] As a preferred, the sending end module includes the following steps when working: S11: data compression and packaging, compressing original image and video data through source coding, segmenting into transmission blocks and adding check code; S12: redundancy coding, selecting Polar code and LDPC code for error correction coding according to channel state, improving anti-interference ability; S13: symbol mapping and modulation, mapping the coded binary data into complex symbols including QPSK and 16QAM, and dynamically adjusting the modulation order; S14: generating a single carrier signal, converting frequency domain symbols into time domain baseband signals through IFFT, and setting the center frequency point to zero to suppress spectral leakage; S15: anti-multipath processing, inserting a cyclic prefix at the head of the time domain signal to eliminate inter-symbol interference caused by multipath propagation; S16: radio frequency transmission, converting the baseband signal into an analog signal through DAC, up-converting to the target frequency band, and transmitting by the antenna after power amplification.

[0031] As described above, the data compression and packaging in the application compresses the original image and video data through source coding, divides into transmission blocks and adds check codes to reduce data volume and facilitate error detection and correction, and improve transmission efficiency; the redundant coding selects Polar code and LDPC code for error correction coding according to the channel state, effectively enhances the anti-interference ability of transmission, and guarantees accurate data transmission; the symbol mapping and modulation map the binary data after coding into a plurality of complex symbols and dynamically adjust the modulation order, which can flexibly adapt to the channel condition and optimize the transmission performance; the generation of single carrier signal converts the frequency domain symbol into time domain baseband signal through IFFT and sets the center frequency point to zero, suppresses the spectrum leakage and improves the signal quality; the anti-multipath processing inserts the cyclic prefix in the head of the time domain signal to eliminate the inter-symbol interference caused by multipath propagation and ensure accurate demodulation of the signal; the radio frequency transmission converts the baseband signal into an analog signal through a series of processing and transmits it, realizes effective radiation transmission of the signal, and the whole process ensures that the sending end can efficiently and reliably complete the data sending task.

[0032] As preferred, the receiving end module, when working, specifically includes: S21: signal receiving and down-conversion, the antenna captures the radio frequency signal, which is restored to a digital baseband signal through low noise amplification, down-conversion and ADC sampling; S22: synchronization calibration, including locating the symbol start position through the sliding correlation peak of the training sequence; estimating and compensating the Doppler frequency offset through the pilot; eliminating the residual deviation by using the Costas loop to track the carrier phase; S23: removing the cyclic prefix, stripping the cyclic prefix in the signal head to retain the effective symbol data block; S24: frequency domain conversion and equalization, performing FFT to convert the time domain signal to the frequency domain, estimating the channel response based on the pilot, and compensating for distortion using the MMSE algorithm; S25: demodulation and decoding, determining the symbol as a bit stream according to the constellation diagram, recovering the original data through SCL decoding, and checking the integrity through CRC; S26: image restoration, recombining the data block and decompressing, and outputting the displayable video frame through the H.265 decoder.

[0033] As described above, the application captures radio frequency signals through the antenna, and restores them to digital baseband signals through low-noise amplification, down-conversion and ADC sampling, providing a reliable data basis for subsequent processing; synchronization calibration uses training sequences, pilots and Costas loops to realize symbol start position positioning, Doppler frequency offset compensation and carrier phase deviation elimination, ensuring accurate signal synchronization and improving demodulation accuracy; removing the cyclic prefix of the signal head to retain the effective symbol data block and avoid interference with subsequent processing; frequency domain conversion and equalization perform FFT to convert time domain signals to frequency domain, estimate the channel response based on the pilot, and compensate for distortion using the MMSE algorithm to effectively combat channel multipath effects and noise interference; demodulation and decoding determine the symbol as a bit stream according to the constellation diagram, recover the original data through SCL decoding and check the CRC to confirm the integrity, ensuring accurate data recovery; image restoration reorganizes the data block and decompresses it through the H.265 decoder to output a displayable video frame, allowing users to intuitively obtain the required information, and the entire process ensures that the receiving end can efficiently and accurately receive and process signals.

[0034] As a preferred, the auxiliary module, when working, specifically includes: S31: Dynamic parameter optimization, real-time monitoring of channel state, adjustment of modulation and coding scheme and transmission power, balance of rate and reliability.

[0035] S32: Pilot and training sequence management, periodic insertion of pilot symbols and special training sequences in the data frame, to assist the receiving end in synchronization and channel estimation; S33: Re-transmission and redundancy control, triggering the HARQ mechanism, retransmitting incremental redundancy data in poor channels, and combining FEC to improve fault tolerance; S34: Security encryption, using AES-256 to encrypt data streams, and implementing identity authentication through HMAC-SHA1; S35: Power consumption optimization, dynamically reducing transmission power according to battery status, turning off the radio frequency circuit when idle, and prolonging the endurance time of the unmanned aerial vehicle.

[0036] As described above, the dynamic parameter optimization of the application monitors the channel state in real time and adjusts the modulation and coding scheme and the transmission power, which can flexibly adapt to different channel environments, effectively balance between transmission rate and reliability, and improve the overall performance of communication; the pilot and training sequence management periodically inserts pilot symbols and special training sequences in the data frame, which provides strong support for synchronization and channel estimation at the receiving end, and guarantees accurate signal reception and processing; the retransmission and redundancy control triggers the HARQ mechanism, retransmits incremental redundancy data in poor channels, and combines FEC to effectively reduce the risk of data loss and enhance the fault tolerance and reliability of data transmission; the security encryption uses AES-256 to encrypt data streams and implements identity authentication through HMAC-SHA1, which ensures the security and integrity of data and prevents information leakage and malicious attacks; the power consumption optimization dynamically reduces the transmission power according to the battery state, and turns off the radio frequency circuit when idle, which significantly prolongs the endurance time of the unmanned aerial vehicle, improves the work efficiency and endurance of the unmanned aerial vehicle, and enables the unmanned aerial vehicle to operate more stably, efficiently, safely and persistently during communication.

[0037] As a preferred, when Polar code and LDPC code are selected for error correction coding according to channel state to improve interference rejection capability, it specifically includes: S41: Channel assessment and feedback: the receiving end monitors SNR and Doppler shift in real time, and feeds back to the sending end through the control channel; S42: Encoding scheme decision, dynamically select Polar code and LDPC code based on preset SNR threshold and machine learning model; S43: Polar code configuration, adjust code rate according to SNR, pre-load reliable bit position table, and combine CRC to assist SCL decoding; S44: LDPC code configuration, use QC-LDPC code, hierarchical decoding to reduce delay, trigger incremental redundancy retransmission in poor channel; S45: Encoding switching and implementation, insert encoding type identifier, realize low-delay switching by hardware multiplexing FPGA; S46: Performance verification and optimization, offline simulation verifies BER boundary, online threshold tuning, prefer LDPC code in low-power mode to prolong endurance.

[0038] As a preferred, when adjusting the code rate according to SNR, the principle formula is: ; Wherein, R is the code rate, k is the information bit length, n is the code word length after coding, and f(SNR) represents that the code rate is a function of signal-to-noise ratio.

[0039] As described above, the present application adopts a fixed coding mode in error correction coding, which is difficult to adapt to dynamic channel environment, resulting in insufficient anti-interference ability and low transmission efficiency in complex channel conditions. The present application adopts a technical solution of selecting Polar code and LDPC code for error correction coding according to channel state. Specifically, the channel parameters are monitored and fed back in real time through channel assessment and feedback; the coding scheme is dynamically selected based on the preset SNR threshold and machine learning model; the Polar code is adjusted in code rate according to SNR, the reliable bit position table is preloaded, and the CRC auxiliary SCL decoding is combined; the QC-LDPC code is used for the LDPC code, the delay is reduced through hierarchical decoding, and the incremental redundancy retransmission is triggered in poor channel; the coding type identifier is inserted, the low-delay switching is realized through hardware multiplexing FPGA; the BER boundary is verified through offline simulation, the threshold is optimized online, and the LDPC code is preferred in low-power mode to prolong the endurance. The present application has the following advantages: it can adapt to different channel environments, dynamically adjust the coding strategy, effectively improve the anti-interference ability, reduce the error rate, improve the transmission efficiency and reliability, and at the same time, it can meet the low-power demand and prolong the endurance time of the equipment. It is especially suitable for scenes with high requirements for communication quality and stability.

[0040] Embodiment: Application of a single-carrier frequency domain equalization transmission system for remote unmanned aerial vehicle image transmission in power line inspection The present embodiment describes a complete remote unmanned aerial vehicle image transmission system, which is applied to automatically inspect high-voltage transmission lines. In this scenario, the unmanned aerial vehicle needs to cruise within a range of 5-10 kilometers from the ground receiving station, transmit back 1080p high-definition video stream in real time, overcome multipath fading in suburban environment, Doppler frequency shift caused by high-speed movement of the unmanned aerial vehicle, and ensure the safety and low power consumption of data transmission.

[0041] The system workflow is as follows: 1. Sender (unmanned aerial vehicle side) workflow: The high-definition camera carried by the unmanned aerial vehicle collects the original video stream. First, the source coding module is started, and the video data is efficiently compressed by using the H.265 / HEVC coding standard, the data is divided into multiple transmission blocks, and CRC check code is calculated and added for each block.

[0042] The compressed data is sent to the channel coding module. The auxiliary module of the system starts to intervene. The adaptive control module selects to use the Polar code with code rate R=0.5 through coding scheme decision according to the channel state information (including SNR=18dB and small Doppler frequency shift) fed back by the receiving end in the last frame.

[0043] The coded bit stream enters the modulation module. The adaptive control module decides to use the 16QAM modulation mode with higher spectral efficiency according to the current good channel conditions. The module maps the binary bit stream into 16QAM complex symbols.

[0044] Subsequently, the symbol stream is fed into the single-carrier modulation module. The module performs IFFT (Inverse Fast Fourier Transform) to convert the frequency domain symbols into time domain baseband signals. To suppress spectral leakage, the center frequency point of the IFFT input is set to zero.

[0045] Next, the cyclic prefix insertion module adds a cyclic prefix with a length greater than the maximum multipath delay of the channel at the head of the generated time domain signal block to eliminate the inter-symbol interference caused by the reflection of the metal tower and trees around the transmission line.

[0046] Before signal transmission, the pilot and training sequence insertion module inserts known pilot symbols and special training sequences for synchronization at the predetermined position of the data frame. At the same time, the encryption and security module uses the AES-256 algorithm to encrypt the entire data stream, and generates an authentication code through HMAC-SHA1 and attaches it to the frame header to achieve identity authentication and data integrity protection.

[0047] Finally, the processed baseband signal is sent to the radio frequency front-end module. The signal is converted to an analog signal by DAC, up-converted to the 2.4GHz civilian drone frequency band, amplified by the power amplifier, and then transmitted by the omnidirectional antenna. Throughout the process, the power management module continuously monitors the drone battery power, and dynamically uses a lower transmission power under the condition of good current signal quality to save energy.

[0048] 2. Wireless channel transmission: The signal is transmitted in space and encounters multiple paths reflected by the tower, and due to the movement of the drone at a speed of 60km / h, a Doppler frequency shift of about 200Hz is generated. The system naturally has anti-multipath capability thanks to the cyclic prefix and frequency domain equalization design. To overcome the Doppler effect, the synchronization mechanism at the receiving end will play a key role.

[0049] 3. Receiving end (ground station side) workflow: The ground station receiving antenna captures the weak radio frequency signal. The radio frequency front-end module first amplifies it with low noise, then down-converts it, and then restores it to a digital baseband signal through ADC sampling.

[0050] Subsequently, the synchronization module begins to work. It identifies the known training sequence in the data frame through the sliding correlator, accurately locates the starting position of each symbol (timing synchronization), then estimates the 200Hz frequency offset of the current signal and compensates for it (frequency synchronization) using the pilot symbol. Finally, the Costas loop is used to track and eliminate the slight carrier phase deviation (phase synchronization).

[0051] After synchronization is completed, the cyclic prefix removal module accurately strips the cyclic prefix at the head of the signal, leaving the valid symbol data block.

[0052] The CP-removed data block is sent to the FFT module, which converts it back to a frequency domain signal. The channel estimation and equalization module (A24) estimates the channel frequency response (H(f)) using the known pilot symbols inserted in the frame, and uses the MMSE (minimum mean square error) equalization algorithm to compensate for distortion in the frequency domain signal, effectively eliminating the effects of multipath and noise.

[0053] The equalized pure frequency domain symbol is judged by the demodulation module according to the 16QAM constellation diagram, and restored to a binary bit stream. The channel decoding module identifies that the Polar code is used at the sending end according to the frame header identification, and then uses the CRC-aided SCL (serial cancellation list) decoding algorithm for decoding. After decoding, the CRC is checked to confirm that the frame data is complete and error-free.

[0054] Finally, the original data stream recovered by the source decoding module is decompressed by H.265, reorganized into complete 1080p video frames, and output to the ground station's monitoring display.

[0055] 4. Full cooperation of auxiliary modules: Throughout the process, the auxiliary modules work continuously: The receiving end feeds back the SNR, Doppler shift, and other information of the current channel to the sending end drone through the control channel.

[0056] When the drone flies into a strong interference area causing the SNR to drop sharply, the adaptive control module of the sending end switches the modulation mode from 16QAM to the more robust QPSK and the error correction coding from Polar code to LDPC code, which performs better in low SNR, according to the feedback.

[0057] Due to poor channel conditions, individual data packets cannot be correctly decoded despite efforts, so the receiving end retransmission and redundancy control module triggers the HARQ mechanism to send an NACK signal to the sending end. Upon receiving the NACK signal, the sending end does not resend the entire data packet, but transmits a part of the incremental redundancy information, which is combined with the previously received error data for decoding, significantly improving the decoding success rate and avoiding video stuttering.

[0058] The embodiments of the present application are described in detail above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the spirit of the present application.

Claims

1. A single-carrier frequency-domain equalization transmission system for image transmission from a remote unmanned aerial vehicle (UAV); characterized in that: Including: The transmitting module is responsible for compressing, encoding, and modulating image data into a single-carrier signal. By inserting a cyclic prefix and radio frequency transmission, it ensures that the signal is resistant to multipath interference and adapted to wireless channel transmission. The receiver module is used to synchronize the received signal, remove the cyclic prefix and perform frequency domain equalization, demodulate and decode to restore the original image data, and overcome the effects of Doppler frequency offset and channel distortion. The auxiliary module dynamically optimizes modulation parameters, inserts pilots for auxiliary synchronization and channel estimation, improves security and reliability through encryption and retransmission mechanisms, and manages power consumption to extend battery life.

2. The single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 1, characterized in that: The sending module specifically includes: A11: Source coding module, responsible for compressing and encoding the image and video data captured by the drone's camera; A12: Channel coding module, used to employ error correction coding techniques to enhance transmission reliability and combat channel noise and interference; A13: Modulation module, used to map encoded data to symbols and dynamically adjust the modulation scheme according to channel conditions; A14: Single-carrier modulation module, used to generate single-carrier signals and convert frequency domain symbols into time domain signals through inverse fast Fourier transform; A15: Cyclic prefix insertion module, used to add a cyclic prefix to the time-domain signal to eliminate inter-symbol interference caused by multipath interference; A16: Radio frequency front-end module, including digital-to-analog converter, up-converter, power amplifier and transmitting antenna, used to convert baseband signals into high-frequency radio frequency signals and transmit them.

3. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 2, characterized in that: The receiver module specifically includes: A21: Radio frequency front-end module, used for receiving antenna, low noise amplifier, downconversion, analog-to-digital conversion, to restore radio frequency signals to baseband digital signals; A22: Cyclic prefix removal module, used to remove cyclic prefixes while retaining valid symbol data; A23: FFT module, used to convert time-domain signals to frequency domain using FFT, in preparation for frequency domain equalization; A24: Channel estimation and equalization module, used to estimate the channel response using pilots or training sequences, and to compensate for channel distortion and eliminate multipath effects through equalization algorithms; A25: Demodulation module, used to demodulate the equalized frequency domain symbols into a bit stream; A26: Channel decoding module, used to decode error correction codes and restore the original data stream; A27: Source decoding module, used to decompress image and video data and restore it to a displayable format.

4. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 3, characterized in that: The receiver module also includes a synchronization module, whose functions include: A31: Timing synchronization, determining the symbol start position through training sequences and pilot signals; A32: Frequency synchronization to compensate for Doppler frequency shift caused by the high-speed movement of the drone; A33: Phase synchronization, eliminating carrier phase deviation.

5. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 4, characterized in that: The auxiliary modules specifically include: A41: Adaptive control module, used to dynamically adjust the modulation and coding scheme and transmit power parameters according to channel state information to optimize transmission efficiency; A42: Pilot and training sequence insertion module, used to insert known pilots and training sequences into data frames, supporting receiver synchronization and channel estimation; A43: Retransmission and redundancy module, used to trigger automatic retransmission requests and hybrid ARQ mechanism under poor channel conditions; A44: Encryption and Security Module, used for encrypting transmitted data and authenticating identity; A45: Power management module, used to optimize transmit power and circuit power consumption, extending the drone's flight time.

6. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 5, characterized in that: When the sending module is working, it specifically includes: S11: Data compression and encapsulation, compressing the original image and video data through source coding, dividing it into transport blocks and adding check codes; S12: Redundancy coding, Polar code and LDPC code are selected for error correction coding according to the channel state to improve anti-interference capability; S13: Symbol mapping and modulation, which maps the encoded binary data into complex symbols including QPSK and 16QAM, and dynamically adjusts the modulation order; S14: Generate a single-carrier signal, convert the frequency domain symbol to a time domain baseband signal through IFFT, and set the center frequency to zero to suppress spectral leakage; S15: Anti-multipath processing, inserting a cyclic prefix at the beginning of the time-domain signal to eliminate inter-symbol interference caused by multipath propagation; S16: Radio frequency transmission; the baseband signal is converted into an analog signal via a DAC, up-converted to the target frequency band, and then transmitted by the antenna after power amplification.

7. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 6, characterized in that: When the receiver module is working, it specifically includes: S21: Signal reception and downconversion. The antenna captures the radio frequency signal, which is then amplified by low noise, downconverted, and sampled by the ADC to restore it to a digital baseband signal. S22: Synchronous calibration, including locating the symbol start position through the sliding correlation peak of the training sequence; estimating and compensating for Doppler frequency offset through pilot signals; and using a Costas loop to track the carrier phase and eliminate residual bias. S23: Remove the cyclic prefix, strip the cyclic prefix from the signal header, and retain the valid symbolic data block; S24: Frequency domain conversion and equalization. Perform FFT to convert the time domain signal to the frequency domain, estimate the channel response based on the pilot, and use the MMSE algorithm to compensate for distortion. S25: Demodulation and decoding, determining the symbols as bit streams according to the constellation diagram, recovering the original data through SCL decoding, and verifying integrity by CRC check; S26: Image restoration, data block reconstruction and decompression, output displayable video frames through H.265 decoder.

8. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 7, characterized in that: The auxiliary module, when in operation, specifically includes: S31: Dynamic parameter optimization, real-time monitoring of channel status, adjustment of modulation and coding scheme and transmit power, balancing rate and reliability. S32: Pilot and training sequence management, periodically inserting pilot symbols and special training sequences into data frames to assist receiver synchronization and channel estimation; S33: Retransmission and redundancy control, triggering the HARQ mechanism to retransmit incremental redundant data under poor channel conditions, combined with FEC to improve fault tolerance; S34: Secure encryption, using AES-256 to encrypt the data stream and HMAC-SHA1 to achieve authentication; S35: Power consumption optimization, dynamically reduces transmission power based on battery status, shuts down RF circuitry when idle, and extends drone flight time.

9. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 8, characterized in that: When selecting Polar codes and LDPC codes for error correction coding based on channel conditions to improve anti-interference capabilities, the specific steps include: S41: Channel assessment and feedback: The receiver monitors SNR and Doppler frequency shift in real time and feeds them back to the transmitter through the control channel; S42: Encoding scheme decision, dynamically selecting Polar code and LDPC code based on preset SNR threshold and machine learning model; S43: Polar code configuration, adjusting the code rate according to SNR, preloading a reliable bit position table, and combining CRC-assisted SCL decoding; S44: LDPC code configuration, using QC-LDPC code, layered decoding to reduce latency, triggering incremental redundant retransmission under poor channel conditions; S45: Encoding switching and implementation, inserting encoding type identifiers, and using FPGA for low-latency switching; S46: Performance verification and optimization, offline simulation to verify BER boundaries, online threshold tuning, and prioritizing LDPC codes in low-power mode to extend battery life.

10. A single-carrier frequency-domain equalization transmission system for remote UAV image transmission according to claim 9, characterized in that: When adjusting the bitrate based on SNR, the underlying formula is: ; Where R is the code rate, k is the information bit length, n is the length of the encoded codeword, and f(SNR) indicates that the code rate is a function of the signal-to-noise ratio.

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