Complex Linear Physical-Layer Network Coding

preprint2016arXivOpen access

Abstract

This paper presents the results of a comprehensive investigation of complex linear physical-layer network (PNC) in two-way relay channels (TWRC). A critical question at relay R is as follows: "Given channel gain ratio η=hA/hBη= h_A/h_B, where hAh_A and hBh_B are the complex channel gains from nodes A and B to relay R, respectively, what is the optimal coefficients (α,β)(α,β) that minimizes the symbol error rate (SER) of wN=αwA+βwBw_N=αw_A+βw_B when we attempt to detect wNw_N in the presence of noise?" Our contributions with respect to this question are as follows: (1) We put forth a general Gaussian-integer formulation for complex linear PNC in which α,β,wA,wBα,β,w_A, w_B, and wNw_N are elements of a finite field of Gaussian integers, that is, the field of Z[i]/q\mathbb{Z}[i]/q where qq is a Gaussian prime. Previous vector formulation, in which wAw_A, wBw_B, and wNw_N were represented by 22-dimensional vectors and αα and ββ were represented by 2×22\times 2 matrices, corresponds to a subcase of our Gaussian-integer formulation where qq is real prime only. Extension to Gaussian prime qq, where qq can be complex, gives us a larger set of signal constellations to achieve different rates at different SNR. (2) We show how to divide the complex plane of ηη into different Voronoi regions such that the ηη within each Voronoi region share the same optimal PNC mapping (αopt,βopt)(α_{opt},β_{opt}). We uncover the structure of the Voronoi regions that allows us to compute a minimum-distance metric that characterizes the SER of wNw_N under optimal PNC mapping (αopt,βopt)(α_{opt},β_{opt}). Overall, the contributions in (1) and (2) yield a toolset for a comprehensive understanding of complex linear PNC in Z[i]/q\mathbb{Z}[i]/q. We believe investigation of linear PNC beyond Z[i]/q\mathbb{Z}[i]/q can follow the same approach.

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