Abstract
In multiple-input multiple-output–orthogonal frequency-division multiplexing underwater acoustic communication systems, the correlation of the sampling matrix is the key of the channel estimation algorithm based on compressed sensing. To reduce the cross-correlation of the sampling matrix and improve the channel estimation performance, a pilot design algorithm for co-sparse channel estimation based on compressed sensing is proposed in this article. Based on the time-domain correlation of the channel, the channel estimation is modeled as a common sparse signal reconstruction problem. When replacing each pilot indices position, the algorithm selects multiple pilot indices with the least cross-correlation from the alternative positions to replace the current pilot indices position, and it uses the inner and outer two-layer loops to realize the bit-by-bit optimal replacement of the pilot. The simulation results show that the channel estimation mean squared error of pilot design algorithm for co-sparse channel estimation based on compressed sensing can be reduced by approximately 18 dB compared with the least square algorithm. Compared with the genetic algorithm and search space size methods, the structural sequence search proposed by pilot design algorithm for co-sparse channel estimation based on compressed sensing is used to design the pilot to complete the channel estimation. Thus, the mean squared error of the channel estimation can be reduced by 2 dB. At the same bit error rate of 0.03, the signal-to-noise ratio can be decreased by approximately 7 dB.
Highlights
There are many problems in the ocean channel, such as a strong multipath effect and narrow available bandwidth.[1,2,3] The single carrier modulation of an underwater acoustic (UWA) communication system has difficulties meeting the communication requirements for a high transmission rate
Multiple-input multipleoutput (MIMO)–orthogonal frequency-division multiplexing (OFDM) technology based on multi-input and multi-output has the advantages of multi-carrier high
In Choi et al.,[14] it is proposed that the smaller the cross-correlation of the sampling matrix is, the better the channel estimation algorithm based on the pilot design
Summary
There are many problems in the ocean channel, such as a strong multipath effect and narrow available bandwidth.[1,2,3] The single carrier modulation of an underwater acoustic (UWA) communication system has difficulties meeting the communication requirements for a high transmission rate. We can use the common sparsity of a UWA channel to reconstruct the common sparsity channel and obtain better channel estimation performance than channel reconstruction alone.[13] In addition, different from the traditional channel estimation method, the uniform pilot distribution achieves the optimal channel estimation performance, and the channel estimation performance of the CS algorithm depends on the cross-correlation of the sampling matrix. In Choi et al.,[14] it is proposed that the smaller the cross-correlation of the sampling matrix is, the better the channel estimation algorithm based on the pilot design. This method in land cannot directly applied into the UWA communication. It is impracticable in real underwater MIMO–OFDM due to the huge amount of computations caused by the large number of system subcarriers and pilot symbols
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