Reliable and Secure Short-Packet Communications

TL;DR

This paper develops an analytical framework to evaluate and optimize the reliability and security of short-packet communications, crucial for applications like mMTC and uRLLC, considering outage probability and effective throughput.

Contribution

It introduces a comprehensive analytical approach to approximate outage probability and throughput in short-packet systems, including closed-form expressions for high SNR regimes, and optimizes blocklength for reliability and security.

Findings

The framework accurately predicts outage probability and throughput.

Optimal blocklength maximizes throughput under outage constraints.

Numerical results confirm the framework's effectiveness and parameter influence.

Abstract

Exploiting short packets for communications is one of the key technologies for realizing emerging application scenarios such as massive machine type communications (mMTC) and ultra-reliable low-latency communications (uRLLC). In this paper, we investigate short-packet communications to provide both reliability and security guarantees simultaneously with an eavesdropper. In particular, an outage probability considering both reliability and secrecy is defined according to the characteristics of short-packet transmission, while the effective throughput in the sense of outage is established as the performance metric. Specifically, a general analytical framework is proposed to approximate the outage probability and effective throughput. Furthermore, closed-form expressions for these quantities are derived for the high signal-to-noise ratio (SNR) regime. Both effective throughput obtained via a general analytical framework and a high-SNR approximation are maximized under an outage-probability constraint by searching for the optimal blocklength. Numerical results verify the feasibility and accuracy of the proposed analytical framework, and illustrate the influence of the main system parameters on the blocklength and system performance under the outage-probability constraint.