Iterative SAGE-Based Joint MCFOs and Channel Estimation for Full-Duplex Two-Way Multi-Relay Systems in Highly Mobile Environment

Two-way relay network based on full-duplex technique has the potential to enhance the spectral efficiency significantly, and increase capacity in future 5G mobile communication systems. However, the self-interference of full-duplex communication severely limits the performance of a two-way relay network. The cancellation of self-interference for multi-relay full-duplex two-way relay systems in highly mobile environment is very challenging due to time-frequency doubly selective channel on the one hand and multiple carrier frequency offsets on the other hand. In this paper, we propose a novel semi-blind estimator to jointly estimate multiple carrier frequency offsets and doubly selective self-interference channels in highly mobile two-way relay systems with orthogonal frequency-division multiplexing modulation in the presence of residual self-interference. We use discrete prolate spheroidal basis expansion model to capture rapid time variations of the channel. The proposed iterative space-alternating generalized expectation maximization-based semi-blind algorithm uses received data symbols along with received pilot symbols to obtain improved frequency offsets and channel estimate with significantly less number of pilot overhead. The proposed estimator converges in almost two iterations and achieves significant improvement over the pilot-based method. The Cramer-Rao lower bounds of the semi-blind joint estimation are also derived.