Wireless Network-Coded Accumulate-Compute and Forward Two-Way Relaying

TL;DR

This paper extends physical layer network coding to an accumulate-compute-and-forward protocol in two-way relaying, using Latin squares to represent coding maps, and optimizes performance based on channel conditions.

Contribution

It introduces a Latin square-based framework for network coding maps in an accumulate-compute-and-forward protocol, extending previous two-way relaying approaches.

Findings

Latin squares represent all valid network coding maps satisfying the exclusive law.

The proposed quantization method optimizes relay performance across channel realizations.

The approach reduces the complexity of finding all suitable network coding maps.

Abstract

The design of modulation schemes for the physical layer network-coded two way wireless relaying scenario is considered. It was observed by Koike-Akino et al. for the two way relaying scenario, that adaptively changing the network coding map used at the relay according to the channel conditions greatly reduces the impact of multiple access interference which occurs at the relay during the MA Phase and all these network coding maps should satisfy a requirement called exclusive law. We extend this approach to an Accumulate-Compute and Forward protocol which employs two phases: Multiple Access (MA) phase consisting of two channel uses with independent messages in each channel use, and Broadcast (BC) phase having one channel use. Assuming that the two users transmit points from the same 4-PSK constellation, every such network coding map that satisfies the exclusive law can be represented by a Latin Square with side 16, and conversely, this relationship can be used to get the network coding maps satisfying the exclusive law. Two methods of obtaining this network coding map to be used at the relay are discussed. Using the structural properties of the Latin Squares for a given set of parameters, the problem of finding all the required maps is reduced to finding a small set of maps. Having obtained all the Latin Squares, the set of all possible channel realizations is quantized, depending on which one of the Latin Squares obtained optimizes the performance. The quantization thus obtained, is shown to be the same as the one obtained in [7] for the 2-stage bidirectional relaying.