Explore-Before-Talk: Multichannel Selection Diversity for Uplink Transmissions in Machine-Type Communication

TL;DR

This paper introduces Explore-Before-Talk (EBT), a multichannel selection diversity method for uplink MTC that improves data rates by exploring multiple channels before data transmission, optimizing resource allocation.

Contribution

The paper proposes a novel EBT approach that exploits multichannel diversity and derives analytical expressions for data rate and outage probability, enhancing uplink MTC performance.

Findings

EBT achieves higher mean data rates than conventional protocols.

EBT maintains outage constraints while improving throughput.

Numerical results validate the effectiveness of the proposed method.

Abstract

Improving the data rate of machine-type communication (MTC) is essential in supporting emerging Internet of things (IoT) applications ranging from real-time surveillance to edge machine learning. To this end, in this paper we propose a resource allocation approach for uplink transmissions within a random access procedure in MTC by exploiting multichannel selection diversity, coined explore-before-talk (EBT). Each user in EBT first sends pilot signals through multiple channels that are initially allocated by a base station (BS) for exploration, and then the BS informs a subset of initially allocated channels that are associated with high signal-to-noise ratios (SNRs) for data packet transmission by the user while releasing the rest of the channels for other users. Consequently, EBT exploits a multichannel selection diversity gain during data packet transmission, at the cost of exploration during pilot transmission. We optimize this exploration-exploitation trade-off, by deriving closed-form mean data rate and resource outage probability expressions. Numerical results corroborate that EBT achieves a higher mean data rate while satisfying the same outage constraint, compared to a conventional MTC protocol without exploration.