Iterative Identification of Sparse Mobile Channels for TDS-OFDM Systems

Abstract

Spectral efficiency improvement is essential for mobile systems development in the light of growing demand for high data transmission rate. The Time-domain synchronous OFDM transmission system increases bandwidth utilization by time-domain channel estimation without any support from frequency-domain pilot signals. Channel identification methods use a training sequence, added at the beginning of every OFDM symbol. Sparse nature of the channel impulse response, which manifests itself during wireless broadband transmission, enables one to implement compressed sensing techniques for channel identification. Channel sparsity reduces the number of measurement samples required in channel reconstruction procedure, but they should be taken from the inter-block interference (IBI) free part of the received training sequence. If maximum delay spread of the channel is comparable with the length of the training sequence, the number of measurements within the IBI-free region may be insufficient for accurate channel identification. This paper discusses a new iterative approach to sparse channels estimation, which uses the measurements from outside the IBI-free region. The proposed solution is examined for simulated transmission over randomly generated doubly-selective channels when compared with the conventional CS technique and perfect channel state information condition. The experiments reveal an enhancement of the transmission quality in terms of SER for slow-time selective channels when both delays and gains of the channel impulse response are estimated with the orthogonal matching pursuit algorithm. Further improvement, also for transmission over moderate varying channels, is observed when the path delays are found in advance. A suitable frame structure is proposed to do so.