Economics of Semantic Communication System in Wireless Powered Internet of Things

TL;DR

This paper explores the economic aspects of energy allocation in semantic communication systems for wireless powered IoT, proposing a deep learning auction mechanism to optimize revenue while ensuring fairness.

Contribution

It introduces a semantic-based energy valuation model and employs deep learning for optimal auction design in energy-constrained wireless IoT systems.

Findings

Maximized wireless power transmitter revenue.

Ensured individual rationality and incentive compatibility.

Improved energy allocation efficiency.

Abstract

The semantic communication system enables wireless devices to communicate effectively with the semantic meaning of the data. Wireless powered Internet of Things (IoT) that adopts the semantic communication system relies on harvested energy to transmit semantic information. However, the issue of energy constraint in the semantic communication system is not well studied. In this paper, we propose a semantic-based energy valuation and take an economic approach to solve the energy allocation problem as an incentive mechanism design. In our model, IoT devices (bidders) place their bids for the energy and power transmitter (auctioneer) decides the winner and payment by using deep learning based optimal auction. Results show that the revenue of wireless power transmitter is maximized while satisfying Individual Rationality (IR) and Incentive Compatibility (IC).