Age of Semantic Information-Aware Wireless Transmission for Remote Monitoring Systems

TL;DR

This paper introduces a new semantic-aware transmission metric called AoIS for remote monitoring, optimizing video data delivery over MIMO channels by balancing information freshness and semantic importance.

Contribution

It proposes the Age of Incorrect Semantics (AoIS) metric and develops low-complexity algorithms for joint optimization in semantic communication systems.

Findings

Preserves over 50% more original information at the same AoIS compared to baselines.

Develops efficient algorithms like SCA and ZF for beamformer optimization.

Transforms complex optimization into manageable subproblems with Lyapunov and AO methods.

Abstract

Semantic communication is emerging as an effective means of facilitating intelligent and context-aware communication for next-generation communication systems. In this paper, we propose a novel metric called Age of Incorrect Semantics (AoIS) for the transmission of video frames over multiple-input multiple-output (MIMO) channels in a monitoring system. Different from the conventional age-based approaches, we jointly consider the information freshness and the semantic importance, and then formulate a time-averaged AoIS minimization problem by jointly optimizing the semantic actuation indicator, transceiver beamformer, and the semantic symbol design. We first transform the original problem into a low-complexity problem via the Lyapunov optimization. Then, we decompose the transformed problem into multiple subproblems and adopt the alternative optimization (AO) method to solve each subproblem. Specifically, we propose two efficient algorithms, i.e., the successive convex approximation (SCA) algorithm and the low-complexity zero-forcing (ZF) algorithm for optimizing transceiver beamformer. We adopt exhaustive search methods to solve the semantic actuation policy indicator optimization problem and the transmitted semantic symbol design problem. Experimental results demonstrate that our scheme can preserve more than 50\% of the original information under the same AoIS compared to the constrained baselines.