Optimal Age of Information and Throughput Scheduling in Heterogeneous Traffic Wireless Physical-Layer Security Communications

A wireless multiuser uplink heterogeneous network is investigated in this article, which comprises an access point and two distinct user groups including throughput-oriented users and Age-of-Information (AoI)-oriented users, in which throughput-oriented users prioritize achieving as high throughput as possible, while AoI-oriented users emphasize timely transmission of information. It is assumed that the transmitted information needs to be kept strictly confidential to unintended users, and the time-division multiple access (TDMA) approach is adopted to transmit confidential information of each user. For such a network, all users who are not scheduled for transmission will be treated as potential eavesdroppers. The objective of our work is to maximize the average achievable secrecy rate of throughput-oriented users while minimizing the average AoI of AoI-oriented users subject to the data queue causality and stability constraints, the sampling rate requirements of AoI-oriented users, the time-averaged and peak transmission power constraints, and the user scheduling constraint. We propose using Lyapunov optimization to convert the original time-averaged optimization problem into a sequence of real-time ones associated with both queue sizes and AoI involved in the current time slot. On this basis, an adaptive heterogeneous traffic security transmission (AHTST) strategy is proposed to determine the optimal strategies for the flow control of throughput-oriented users, the sampling rate control of AoI-oriented users, the power allocation, as well as the user scheduling. Numerical results demonstrate that the AHTST strategy surpasses the considered benchmark schemes in both achievable average secrecy rate and average AoI.

I. Introduction

The advancementof Internet of Things (IoT) is connecting more aspects of our daily lives within the computer network, which makes more applications need to meet the requirements of information timeliness [1]. For example, a large amount of freshness information is required in autonomous driving to calculate road conditions and console scheduling [2]. Outdated information could result in faulty control decisions and potentially lead to catastrophic disasters. As a result, it is crucial to prioritize the timely receipt of data in status information updating systems. In general, the transmission latency is a common metric used to measure whether a system can meet the requirements of delay-sensitive services. However, the transmission latency only takes into account the time elapsed from sending to receiving data packets, and the freshness of information cannot be accurately assessed based on transmission latency solely. For example, it is common for data queue in the system to remain empty in the case of a low information arrival rate, leading to a small delay for packet transmission. Nonetheless, in the absence of new packets arriving, the information received at the recipient may become outdated and potentially lose its relevance. Consequently, the concept of Age of Information (AoI) is introduced as a novel metric that has been developed to measure the freshness of information from the receiver’s viewpoint [3].