Compressed Sensing Based Channel Estimation for Two-Way Relay Networks

In this letter, a novel channel estimation scheme based on compressed sensing (CS) theory is proposed for two-way relay networks (TWRN) in sparse frequency-selective fading channels. Unlike point-to-point systems, applying CS theory to sparse channel estimation in TWRN is much more challenging since the equivalent channels (terminal-relay-terminal) may be no longer sparse due to the linear convolutional operation. To solve this problem, instead of directly estimating the equivalent channels, a linear precoding based method is designed to firstly separate the individual channels between the terminals and the relay from the equivalent channels. CS theory is then applied to the time-domain channel estimation with much smaller number of pilot symbols. This scheme enables accurate channel estimation for TWRN with significant overhead reduction. Extensive numerical results are provided to substantiate the effectiveness of the proposed method.