Adaptive Underwater Acoustic Communication Based On Weighted Fractional Order Fourier Transform Technical Research

The traditional SC-FDE(single carrier frequency domain equalization)system and OFDM(Orthogonal Frequency Division Multiplexing)system have their own advantages and disadvantages,in the changing channel conditions can not take into account multi-party interference factors,weighted fractional order Fourier transform through the changing fractional order value to combine the two systems into one,Different fractional order values can be made into SC-FDE systems,OFDM systems,or hybrid systems containing both.In this paper,the adaptive modulation technique is applied to the weighted fractional order Fourier transform system to realize the adaptive selection of fractional order followed by modulation mode.Adaptation is generally considered to be a Markov decision problem,which can introduce reinforcement learning into the system to achieve the purpose of adaptation.Through the reinforcement learning method,the weighted fractional Fourier transform system can change the modulation mode of the transmitter and the fractional order of the system according to the real-time status information of the channel,so as to realize the low bit error rate and robust underwater acoustic communication.Firstly,this paper introduces the structural principle and overall communication flow of the weighted fractional Fourier transform hybrid carrier system,showing that the bit error rate performance is better than that of the SC-FDE system and the OFDM system.The traditional linear equilibrium and block iterative decision feedback nonlinear equilibrium methods are introduced,and several methods are compared to select the equilibrium method suitable for the hybrid system.Secondly,this paper studies the adaptive underwater acoustic communication technology based on weighted fractional order Fourier transform.The adaptive modulation problem to be realized in this paper is abstractly mapped into a reinforcement learning model,the Q-learning algorithm in reinforcement learning is selected,and the output signal-to-noise ratio after equilibrium is used as the indicator of the feedback channel state,and a weighted fractional Fourier transform adaptive underwater acoustic communication algorithm is constructed according to the different performance requirements of the system.Finally,the simulation test research and modeling in this paper are based on the measured sound velocity profile of the Arctic site,and the experiment uses the Songhua River data to verify the effectiveness of the algorithm studied.It can be seen from the experimental results that compared with the single SC-FDE or OFDM adaptive underwater acoustic communication system based on the minimum bit error rate strategy,the hybrid system based on the Q-learning algorithm can select the fractional order and modulation mode that makes the bit error rate reach the lowest in the current channel environment.Based on the maximum throughput criterion strategy,hybrid carrier systems can choose the fractional order and modulation method that makes the system throughput highest compared to traditional single-carrier or multi-carrier adaptive underwater acoustic communication systems.The adaptive communication algorithm studied in this paper can adjust the strategy according to different needs to achieve high-quality transmission of underwater information.