Compressed Channel Estimation for Sparse Multipath Non-Orthogonal Amplify-and-Forward Cooperative Networks

Coherent detection and demodulation at the receiver requires Channel State Information (CSI). The authors investigate channel estimation problem in sparse multipath Non-orthogonal Amplify-and-Forward (NAF) cooperative networks. Traditional linear estimation methods can obtain lower bound at the cost of spectrum efficiency which is becoming more and more scarcity. In this paper, system model is described from sparse representation perspective. Based on the compressed sensing theory, they propose several compressed channel estimation methods to exploit sparsity of the cooperative channels. Simulation results confirm the superiority of proposed methods than LS-based linear estimation method.