Application of compressive sensing to tow-way relay channel estimation
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Abstract
An Amplify and Forward Two-Way Relay Network is one where two nodes transmit data to each other via an intermediate relay. The relay amplifies the superimposed data from both the nodes before sending it to both the nodes. A method for the estimation of channel is proposed for Amplify and Forward Two-Way Relay Network (AF-TWRN). The proposed method utilizes the fact that the channel in the case of AF-TWRN shows sparse characteristic. The sparse multipath channel is estimated in the case of AF-TWRN using compressive sensing (CS) reconstruction algorithm, namely Iterative Hard Thresholding (IHT). MSE based performance of these methods in estimating the composite AF-TWRN channel was calculated and compared to that using Compressive Sampling Matching Pursuit (CoSaMP) and Orthogonal Matching Pursuit (OMP). IHT and CoSaMP are seen to perform slightly better than OMP with lesser computational complexity than OMP. It was also shown that all three CS based estimation methods perform better than the traditional Least Squares (LS) method in the estimation of Sparse AF-TWRN channel. A low complexity detection strategy was proposed