Compressed sensing pilot frequency design method based on tabu search

Abstract

The invention provides a compressed sensing pilot design method based on tabu search, which comprises the steps of S1, determining a tabu length l and an iteration frequency u, clearing a tabu table,and generating an initial solution; S2, determining whether the number of iterations reaches u or not, if so, outputting a pilot pattern and stopping searching, and otherwise, executing S3; S3, in thenon-tabu object, obtaining a candidate solution by applying a neighborhood criterion, recording a measurement matrix cross-correlation value mu of the candidate solution, and adding the measurement matrix cross-correlation value mu into a tabu table; S4, updating the tabu table, subtracting 1 from all the elements of which the values are greater than 0, and setting a numerical value in the tabu table corresponding to the object newly added into the tabu table as a tabu length; and S5, determining whether a aspiration criterion is met or not, if so, recording the pilot frequency pattern as anoutput pilot frequency, taking a mu value as a new minimum value of the aspiration criterion, adding 1 to the number of iterations, and executing the step S2. According to the method, a smaller mu value can be obtained under the same operand, and the corresponding pilot frequency pattern is used for compressed sensing channel estimation to obtain a lower channel estimation error.

Description

technical field [0001] The invention relates to a method for designing compressed sensing pilots, in particular to a method for designing compressed sensing pilots based on tabu search, and belongs to the technical field of underwater acoustic communication. Background technique [0002] As a sampling and compression technique, compressed sensing can reconstruct the original signal through a restoration algorithm after sampling a sparse signal at a rate lower than the Nyquist sampling rate. In the wireless channel, the multipath channel is sparse, so the compressed sensing signal can be reconstructed by a small number of observations, so it can be applied to channel estimation. Compared with the traditional least squares method, the sparse channel estimation based on compressed sensing can achieve better performance under the same number of pilots. [0003] Pilot channel estimation based on compressed sensing has been widely studied and applied. One of the main research dir...

AI Technical Summary

Problems solved by technology

Since it is necessary to search and calculate the pilot position from a large number of data positions, if all calculations are performed using the exhaustive method, the amount of calculation will increase severely

The existing traditional search algorithm is mainly based on random search and greedy algorithm, in order to achieve a smaller μ value, more searches are required

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