Maximum Throughput Opportunistic Network Coding in Two-Way Relay Networks

TL;DR

This paper develops an optimal opportunistic network coding policy for two-way relay networks that maximizes throughput while respecting delay constraints, outperforming baseline schemes in efficiency and power use.

Contribution

It introduces a novel Markov chain model and formulates a linear programming approach to find the optimal coding policy under delay constraints.

Findings

Optimal policy significantly improves throughput, delay, and power consumption.

Outperforms baseline schemes in various traffic scenarios.

Provides a structured approach for delay-constrained throughput optimization.

Abstract

In this paper, we study Two-way relaying networks well-known for its throughput merits. In particular, we study the fundamental throughput delay trade-off in two-way relaying networks using opportunistic network coding. We characterize the optimal opportunistic network coding policy that maximizes the aggregate network throughput subject to an average packet delay constraint. Towards this objective, first, we consider a pair of nodes communicating through a common relay and develop a two dimensional Markov chain model capturing the buffers' length states at the two nodes. Second, we formulate an optimization problem for the delay constrained optimal throughput. Exploiting the structure of the problem, it can be cast as a linear programming problem. Third, we compare the optimal policy to two baseline schemes and show its merits with respect to throughput, average delay and power consumption. First, the optimal policy significantly outperforms the first baseline with respect to throughput, delay and power consumption. Moreover, it outperforms the second baseline with respect to the average delay and power consumption for asymmetrical traffic arrival rates.