IRS-Assisted Physical Layer Network Coding Over Two-Way Relay Fading Channels - AlaaEldin, Mahmoud; Alsusa, Emad; Seddik, Karim G. (IEEE transactions on vehicular technology, 2022)
This article investigates the performance of intelligent reflective surfaces (IRS)-aided physical layer network coding (PNC) in two-way relaying channels (TWRC). Specifically, IRS is used to eliminate carrier phase offset (CPO) at the relay node. To this end, the IRS reflectors' phase shifts are optimized to align the received signals from two source nodes at the relay. This facilitates using a simple mapping function at the relay to map the superimposed signal to a network-coded signal. Two scenarios are considered, the first of which assumes that each source node is served by a separate IRS panel, while the second scenario considers the more challenging case where only one IRS panel is available for the two source nodes. In the latter case, the IRS panel is seen by both source nodes and its phase shifts are optimized to mitigate the CPO problem while maximizing the received signal amplitude at the relay. This optimization problem is formulated and solved over the complex circle manifold. Finally, we extend the IRS-assisted PNC system to include channel coding and higher modulation orders, for which a repeat accumulate (RA) channel-coded IRS-aided PNC scheme is proposed for general quadrature amplitude modulation (QAM) signals. A belief propagation (BP) based algorithm is designed to decode the network-coded sequences over a q-Ring using modular arithmetic. Our simulation results validate the theoretical error expressions derived for the two-IRS scenario as well as the efficacy of the proposed manifold optimization approach for the one-IRS scenario. The results also confirm the efficacy of the designed channel-coded IRS-aided PNC using high QAM modulation orders.