Finite Blocklength Analysis of Multiple Access Channels With/Without Cooperation

Motivated by the demand of reliable and finite blocklength communications, we employ tools from information theory, stochastic processes and queueing theory, in order to provide a comprehensive framework regarding the analysis of a Time Division Multiple Access (TDMA) network with bursty traffic, in the finite blocklength regime. Specifically, we reexamine the stability conditions of a non-cooperative TDMA multiple access channel, evaluate the optimal throughput, and identify the optimal data packet size, k, for fixed codeword of blocklength, n. The evaluation is performed both numerically and via the proposed approximations, which result in closed form expressions and provide insight on how the optimal data size, k*, relates to the information metrics of channel capacity and channel dispersion in the finite blocklength regime. Then, we examine the stability conditions and the performance of the Multiple Access Relay Channel with TDMA scheduling, subject to finite blocklength constraints, by applying a cognitive cooperation protocol that assumes relaying is enabled when sources are idle. Finally, we propose the novel Batch-And-Forward (BAF) strategy, a mechanism that allows terminals to send batches of data packets instead on individual data packets, and evaluate the stability conditions and the optimal throughput. Numerical evaluation of the proposed strategy indicates that the performance of the cooperative network in the finite blocklength regime, in terms of throughput, can be significantly enhanced. Moreover, it reduces the requirement in control signals (metadata) [3], since, it avoids the unnecessary repetition of metadata (e.g. address of the source terminal and the destination). The BAF strategy is quite versatile, thus, it can be embedded in existing cooperative protocols, without imposing additional complexity on the overall scheme.

I. Introduction

Information theory paved the way for the development of communication theory, and evolved over the years to include a wide range of communication applications, such as, compression, coding, and statistics. However, it has fallen short of leaving its distinct mark in the field of communication networks [3], [4], and this confinement is mainly attributed to the asymptotic nature of Information theory. Shannon’s definition of channel’s capacity requires infinitely large blocklength in order to guarantee arbitrary small probability of error, for all rates below the channel’s capacity. Thus, classical information measures cannot handle realistic scenarios where the blocklength is finite. Finite blocklength is also inextricably linked with the requirement of Ultra-Reliable Low-Latency Communications (URLLC) [5], which emerged to support a vast family of applications that require the simultaneous consideration of stringent latency and reliability criteria, and is a key factor for many vertical markets, including, autonomous vehicles, remote healthcare and mission critical communications.