Proper

Abstract

2-way relaying networks are design for bandwidth efficient use of the available spectrum, since it allow for data exchange between two users with the involvement of an intermediate relay node. Due to superposition of signals in the relay node, the received signal at the user terminals is affected by multiple parameters like channel gains, timing offsets, and carrier frequency offsets which need to be estimate and compensate. Our proposed semi-blind estimator is based on the Gaussian maximum likelihood criterion which treats that data symbols as Gaussian-distributed nuisance parameters. To assist in the estimation of the individual channels, we adopt a superimposed training strategy at the relay. We have design the pilot vectors of the terminals and the relay to optimize the estimation performance. Moreover it we compare the semi-blind and pilot-based Cramer-Rao bounds (CRBs) to use as performance benchmarks. We use simulation result to show that the proposed method provides improvement in estimation accuracy over the conventional pilot-based estimation and it approaches the semi-blind CRB as SNR increases & the simulation results shows that the performance of the proposed estimators is related to the derived CRLBs at moderate to high SNR. It is also shows that the overall BER performance of the AF TWRN is close to a TWRN.