Abstract

This paper addresses the joint power allocation issue in physical-layer network coding (PLNC) of multicast systems with two sources and two destinations communicating via a large number of distributed relays. By maximizing the achievable system rate, a constrained optimization problem is first formulated to jointly allocate powers for the source and relay terminals. Due to the nonconvex nature of the cost function, an iterative algorithm with guaranteed convergence is developed to solve the joint power allocation problem. As an alternative, an upper bound of the achievable rate is also derived to modify the original cost function in order to obtain a convex optimization solution. This approximation is shown to be asymptotically optimal in the sense of maximizing the achievable rate. It is confirmed throughMonte Carlo simulations that the proposed joint power allocation schemes are superior to the existing schemes in terms of achievable rate and cumulative distribution function (CDF).

Highlights

  • Network coding (NC) was first proposed for wireline systems to improve the network’s achievable rate about ten years ago [1]

  • This paper addresses the joint power allocation issue in physical-layer network coding (PLNC) of multicast systems with two sources and two destinations communicating via a large number of distributed relays

  • Simulation results are demonstrated to show the performances of the two proposed joint power allocation schemes in terms of the achievable rate and cumulative distributed function (CDF)

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Summary

Introduction

Network coding (NC) was first proposed for wireline systems to improve the network’s achievable rate about ten years ago [1]. It was shown in [2, 3] that by coding the data stream, rather than separated symbols, the NC can provide a higher achievable rate than the traditional Shannon information theory does. The PLNC is to jointly process multiple symbols without decoding them considering that the aim of the transmission is to tell the symbols to the destination rather than the relay [7,8,9] It is the data stream, instead of any separate symbol, that is tackled by NC. NC improves the achievable rate from the data stream perspective

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