Energy-Efficient Hybrid Data Computation via Coordinated AirComp and Edge Offloading

TL;DR

This paper proposes an energy-efficient hybrid data computation method combining AirComp and edge offloading, optimizing resource use in 6G networks.

Contribution

It introduces a coordinated framework with a block coordinate descent algorithm to minimize energy consumption in hybrid data processing.

Findings

Significant energy savings over baseline strategies

Effective coordination of AirComp and edge offloading

Improved network sustainability and resource management

Abstract

The development of 6G networks brings an increasing variety of data services, which motivates the hybrid computation paradigm that coordinates the over-the-air computation (AirComp) and edge computing for diverse and effective data processing. In this paper, we address this emerging issue of hybrid data computation from an energy-efficiency perspective, where the coexistence of both types induces resource competition and interference, and thus complicates the network management. Accordingly, we formulate the problem to minimize the overall energy consumption including the data transmission and computation, subject to the offloading capacity and aggregation accuracy. We then propose a block coordinate descent framework that decomposes and solves the subproblems including the user scheduling, power control, and transceiver scaling, which are then iterated towards a coordinated hybrid computation solution. Simulation results confirm that our coordinated approach achieves significant energy savings compared to baseline strategies, demonstrating its effectiveness in creating a well-coordinated and sustainable hybrid computing environment.