Research On Adaptive Turbo Receiver Technology For MIMO Underwater Acoustic Communication

At present,the research direction of underwater communication is mainly to realize high-speed and reliable communication of underwater information.The underwater acoustic channel is a time-varying,space-varying,frequency-varying fading channel with severe bandwidth limitation and severe noise interference.Receivers with equalization technique can compensate for channel variations,overcome inter-symbol interference and channel distortion,and the Turbo equalization technology is always using in underwater communication too.Equalization techniques overcome inter-symbol interference,and MIMO technology can increase the data transmission rate.The existing Turbo equalization receiver has problems of high computational complexity;slow convergence rate and failure to make full use of the sparse characteristics of underwater acoustic channels.In this paper,the direct adaptive Turbo equalization technique and the sparse fast self-optimization algorithm are applied to MIMO underwater acoustic communication,and starting the research on adaptive Turbo receiver technology in MIMO.Firstly,there is the traditional Least Mean Square?LMS?algorithm introduced and starting to deduct the theory of the algorithm.For the sparse characteristics of the underwater acoustic channel,the zero norm least mean square??₀-LMS?using the channel sparsity characteristic is introduced.The theory of the algorithm is introduced.The step size of the LMS algorithm has a great influence on the algorithm.In order to make the step size of the algorithm adaptively change with the change of the system,a fast self-optimizing LMS algorithm?Fast Self-Optimized LMS?,referred to as FOLMS algorithm.Combined with the characteristics of channel sparsity and adaptive change of step size,an improved algorithm zero-norm fast self-optimization LMS??₀-FOLMS?algorithm is proposed to improve the algorithm's estimate ability of sparse system.The tracking ability and convergence speed of the algorithm are important criteria for the evaluation algorithm.The normalized LMS?PNLMS?algorithm has faster initial convergence speed and tracking ability,and then considering the sparse characteristics and adaptive step size method to propose an improved ratio,The normalized fast self-optimizing LMS?IPFONLMS?algorithm and the norm-improved proportional normalized fast self-optimizing LMS??₀-IPFONLMS?algorithm can improve the convergence and tracking ability of the algorithm.Finally,each algorithm is being simulated and compared,and analysis its convergence speed and steady state.Then,research on adaptive Turbo receiver technology in MIMO was carried out.The two kinds of Turbo equalization technique in underwater acoustic communication are introduced and compared,and the direct adaptive Turbo equalization technique is adopted for the low complexity requirements.The transmission and reception models of single-carrier MIMO communication systems,the structure of direct adaptive equalizers in MIMO systems,and how to apply sparse fast self-optimizing LMS algorithms to MIMO systems and direct adaptive equalization to estimate noise variance and mean are studied.Finally,the performance of the direct adaptive MIMO receiver is verified by simulation.Finally,test data processing and analysis are performed.The performance of the sparse fast self-optimization algorithm is verified by processing the southeast sea experiment data of Xiamen.By comparing each adaptive algorithm using the MIMO receiver and the number of successfully recovered data,the tracking ability and convergence of the proposed are verified to be improved,and the MIMO receiver based on the improved algorithm can recover more data packets than the MIMO receiver that is based on the LMS algorithm.