A Partial Amplify and Forward Cooperative Communication Strategy Based on Blind Signal Detection

Abstract

Due to the great potential in extending propagation distance and enhancing the link reliability, amplify and forward (AF) cooperative communications have attracted much attention recently. However, the existing studies mainly focus on the energy consumption analysis and optimization, and also the channels used in communications are based on Rayleigh/Rician fading model, and/or it was usually supposed that the channel state information (CSI) is known or can be acquired by a training sequence. In this paper, blind signal detection for AF cooperative communication systems based on time division multiple access (TDMA) is studied, in which the channels are modeled as frequency selective fading and the CSI are unknown. A blind signal detection algorithm of partial amplify and forward (PAF) cooperative communication is proposed based on semidefinite relaxation (SDR). This method can recover the data without the training sequence and need not to implement blind equalization for the unknown channels. With the correlation between data of different links, the proposed method can obtain the optimal solution efficiently and achieve better performance of signal detection than the traditional algorithm. By simulations, the energy consumption efficiency as well as the overall system performance of the proposed strategy are verified.