Compressive Sensing Based Opportunistic Protocol for Throughput Improvement in Wireless Networks

TL;DR

This paper introduces a compressive sensing-based opportunistic MAC protocol that enhances throughput in wireless networks by efficiently selecting users with high channel gains, especially in fast fading environments.

Contribution

It proposes a novel protocol combining compressive sensing with R-ALOHA to reduce reservation time and improve throughput in wireless networks.

Findings

Requires less reservation time than existing schemes

Outperforms traditional protocols in fast fading environments

Applicable with both analog and digital channel gain reporting

Abstract

A key feature in the design of any MAC protocol is the throughput it can provide. In wireless networks, the channel of a user is not fixed but varies randomly. Thus, in order to maximize the throughput of the MAC protocol at any given time, only users with large channel gains should be allowed to transmit. In this paper, compressive sensing based opportunistic protocol for throughput improvement in wireless networks is proposed. The protocol is based on the traditional protocol of R-ALOHA which allows users to compete for channel access before reserving the channel to the best user. We use compressive sensing to find the best user, and show that the proposed protocol requires less time for reservation and so it outperforms other schemes proposed in literature. This makes the protocol particularly suitable for enhancing R-ALOHA in fast fading environments. We consider both analog and digital versions of the protocol where the channel gains sent by the user are analog and digital, respectively.