Frequency Offset and Channel Estimation in Cooperative Relay Networks

Abstract

A new joint frequency offset and channel estimator for cooperative relay networks operating over time-varying multipath channels based on Gauss–Hermite integration (GHI) and approximate Rao-Blackwellization (GHI-ARB) is proposed. The resulting algorithm incorporates parallel Schmidt–Kalman filters (SKFs) to separate all interfering links at the destination receiver. In each SKF, Rao-Blackwellization is conditioned on a GHI integration point. Using the Rao-Blackwellization for the frequency offset in the Gauss–Hermite filter (GHF), a joint channel and frequency offset can be efficiently estimated by the proposed GHI-approximate Rao-Blackwellization-based SKF (GHI-ARB-SKF) in the relay network. Simulation results show the superiority of the proposed GHI-ARB-SKF over a Rao-Blackwellized unscented-Kalman-filter (GHI-ARB-UKF)-based approach.