Semantic Filtering and Source Coding in Distributed Wireless Monitoring Systems

TL;DR

This paper introduces a goal-oriented semantic filtering and source coding framework for multiuser wireless monitoring systems, optimizing timely status updates based on packet importance and heterogeneous monitor goals.

Contribution

It proposes novel semantic filtering schemes, an error control method, and an optimal source coding strategy to enhance timely information delivery in distributed wireless monitoring.

Findings

Semantic filtering improves packet relevance and system efficiency.

Optimal codeword lengths maximize semantic utility across sensors and monitors.

Proposed schemes outperform traditional methods in delivery timeliness.

Abstract

The problem of goal-oriented semantic filtering and timely source coding in multiuser communication systems is considered here. We study a distributed monitoring system in which multiple information sources, each observing a physical process, provide status update packets to multiple monitors having heterogeneous goals. Two semantic filtering schemes are first proposed as a means to admit or drop arrival packets based on their goal-dependent importance, which is a function of the intrinsic and extrinsic attributes of information and the probability of occurrence of each realization. Admitted packets at each sensor are then encoded and transmitted over block-fading wireless channels so that served monitors can timely fulfill their goals. A truncated error control scheme is derived, which allows transmitters to drop or retransmit undelivered packets based on their significance. Then, we formulate the timely source encoding optimization problem and analytically derive the optimal codeword lengths assigned to the admitted packets which maximize a weighted sum of semantic utility functions for all pairs of communicating sensors and monitors. Our analytical and numerical results provide the optimal design parameters for different arrival rates and highlight the improvement in timely status update delivery using the proposed semantic filtering, source coding, and error control schemes.