In this paper, we present an intelligent reflective surface (IRS)-assisted physical layer network coding (PNC) system in a two-way relaying channel (TWRC). Specifically, IRS is used to align the effective channels of the two received superimposed signals at the relay, which allows canceling the carrier phase offset (CPO) between the two received signals. The IRS phase shifts are optimized to maximize the received PNC signal amplitude while having a zero CPO constraint. An efficient manifold optimization-based approach is proposed to solve this problem, where the optimization is performed on the complex circle manifold. Moreover, we improve the performance of channel-coded IRS-assisted PNC by introducing the weighted non-binary PNC (WN-PNC) scheme, where the binary data are mapped to, and encoded over, Galois Fields (GFs). We present two WN-PNC cases where the data is encoded over GF(4) and GF(8), then modulated using quadrature phase shift keying (QPSK) and 8-quadrature amplitude modulation (8-QAM), respectively. We also design proper PNC mapping functions for both cases, ensuring that no PNC ambiguity can occur at the relay. Our simulation results show the efficacy of the proposed manifold optimization-based approach and the error performance improvement of the WN-PNC over the binary PNC case.


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    Title :

    Design of IRS-Assisted Non-Binary Channel-Coded Physical Layer Network Coding


    Contributors:


    Publication date :

    2023-06-01


    Size :

    1271683 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English






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