An improved time-domain channel estimation using compressive sensing based on wavelet transform multicarrier modulation system

Compared with OFDM, wavelet-based multi-carrier modulation system, due to the utilization of wavelet basis to construct the channels, have not only the orthogonal sub-channels but also the orthogonal transmission symbols of each sub-channel, which means it can resist ICI effectively without inserting CP. These characteristics brings great improvement of the system spectrum utilization and makes wavelet-based multi-carrier modulation system get wide attention. But the widespread use of the system is limited by high complexity of its channel estimation technology. In this paper, an improved time-domain channel estimation technique based on compressive sensing is proposed. According to the estimation feature of compressive sensing, pilot symbols are randomly inserted in time-domain, and the number of pilot symbols depends on the channel sparseness. Using the quasi-Toeplitz to construct the observation matrix makes CS channel estimation has better BER performance than traditional method. Furthermore, constructing index set using the received pilot signal and the local pilot by cross-correlation and estimating the number of iterations of the OMP reconstruction algorithm that reduces the number of iterations and the time required for the algorithm under the same reconstruction rate. In general, an improved time-domain CS channel estimation for wavelet transform multi-carrier modulation effectively reduces the system overhead and improves the precision of spectrum utilization, greatly improves the accuracy of channel estimation.