Abstract

We study the fundamental limits of communications over multi-layer wireless networks where each node has only limited knowledge of the channel state information. In particular, we consider the scenario in which each source-destination pair has only enough information to perform optimally when other pairs do not interfere. Beyond that, the only other information available at each node is the global network connectivity. We propose a transmission strategy that solely relies on the available limited knowledge and combines coding with interference avoidance. We show that our proposed strategy goes well beyond the performance of interference avoidance techniques. We present an algebraic framework for the proposed transmission strategy based on which we provide a guarantee of the achievable rate. For several network topologies, we prove the optimality of our proposed strategy by providing information-theoretic outer-bounds.

Highlights

  • In dynamic wireless networks, optimizing system efficiency requires channel state information (CSI) in order to determine what resources are available

  • 6 Conclusions In this paper, we studied the fundamental limits of communications over multi-layer wireless networks where each node has limited channel state information

  • We developed a new transmission strategy for multi-layer wireless networks with partial channel state information (i.e., 1-local view) that combines multiple ideas including interference avoidance and network coding

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Summary

Introduction

In dynamic wireless networks, optimizing system efficiency requires channel state information (CSI) in order to determine what resources are available. To model local views at wireless nodes, we consider the scenario in which each source-destination (S-D) pair has enough. We propose an algebraic framework that defines a transmission scheme that only requires 1-local view at the nodes and combines coding with interference avoidance scheduling. These models range from having no channel state information at the sources [10,11,12,13], delayed channel state information [14,15,16,17,18,19], mismatched delayed channel state knowledge [20,21,22], or analog channel state feedback for fully connected interference channels [23] Most of these works assume fully connected network or a small number of users. If a link between Vi and Vj does not exist, we set nij to be zero

The Gaussian model
Performance metric
Motivating examples
T2 gii i i log i
Gain of coding over interference avoidance: nested folded-chain networks
Conclusions
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