An underwater acoustic sparse channel estimation variable step sparsity adaptive match tracking method

Abstract

The invention discloses an underwater acoustic sparse channel estimation variable step sparsity adaptive matching tracking method, which fully utilizes the underwater acoustic channel sparse multipathcharacteristic and avoids the waste of frequency spectrum resources caused by the excessive number of pilots in the traditional channel estimation technology. The method does not need sparseness as apriori information, and the size of the support set is the estimated sparseness at the end of iteration by expanding the support set through step size. In addition, the signal reconstruction processis divided into several stages by combining stage idea and variable step size, the number of atoms in the support set in a certain phase remains constant, and the adjacent phases gradually expand thesupport set by different step sizes. The invention improves the recovery accuracy on the premise of not significantly increasing the calculation amount, that is, obtains a better trade-off between thereconstruction accuracy and the calculation complexity. Compared with the prior classical greedy algorithm, the invention does not need sparseness as a prior information, and the step size adaptive change can give consideration to the algorithm accuracy and the operation efficiency.

Description

technical field [0001] The invention belongs to the field of underwater acoustic communication, and relates to a channel estimation method applied to an underwater acoustic communication system, and more specifically, relates to a variable step-size sparsity adaptive matching tracking method based on compressed sensing. Background technique [0002] In view of the good propagation characteristics of sound waves in water, at present, underwater wireless communication mostly uses sound waves as the information transmission carrier. However, the underwater acoustic channel is a complex channel with time, space and frequency changes, and its characteristics such as limited bandwidth and severe multi-channel expansion seriously affect the propagation of acoustic signals. Orthogonal Frequency Division Multiplexing (OFDM) technology, as a multi-carrier modulation technology, can effectively combat multipath interference, and has high spectrum utilization and transmission rate. It c...

AI Technical Summary

Problems solved by technology

It can be seen that the performance of the algorithm is affected by the step size. If the step size is too large, the estimated sparsity in the iterative process will easily exceed the real sparsity, resulting in overestimation, and the reconstruction accuracy will decrease. However, due to the small number of iterations, the amount of calculation is small; Small, the reconstruction accuracy is improved, but the number of iterations required by the algorithm to achieve the true sparsity increases, and the computational complexity also increases

[0004] To sum up, the fixed step size of the SAMP algorithm under the condition of unknown sparsity is difficult to take into account the accuracy and computational complexity of system reconstruction, and there is an urgent need for a reconstruction with a better balance between recovery accuracy and algorithm operation efficiency, and a simple structure algorithm

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