Cooperative Interference Management for Over-the-Air Computation Networks

TL;DR

This paper develops centralized and distributed power control algorithms for multi-cell AirComp networks to optimize inter-cell interference management, significantly reducing the overall mean squared error in data aggregation.

Contribution

It introduces a novel approach to jointly optimize power control in multi-cell AirComp networks, including a convex optimization-based centralized method and a decentralized iterative algorithm.

Findings

Centralized power control minimizes sum MSE via convex optimization.

Distributed IT-based method achieves Pareto-optimal MSE with local control.

Simulations show substantial MSE reduction with proposed algorithms.

Abstract

This paper considers a multi-cell AirComp network and investigates the optimal power control policies over multiple cells to regulate the effect of inter-cell interference. First, we consider the scenario of centralized multi-cell power control, where we characterize the Pareto boundary of the multi-cell MSE region by minimizing the sum MSE subject to a set of constraints on individual MSEs. Though the sum-MSE minimization problem is non-convex and its direct solution intractable, we optimally solve this problem via equivalently solving a sequence of convex second-order cone program feasibility problems together with a bisection search. Next, we consider distributed power control in the other scenario without a centralized controller, for which an alternative IT-based method is proposed to characterize the same MSE Pareto boundary, and enable a decentralized power control algorithm. Accordingly, each AP only needs to individually control the power of its associated devices, but subject to a set of IT constraints on their interference to neighboring cells, while different APs can cooperate in iteratively updating the IT levels by pairwise information exchange, to achieve a Pareto-optimal MSE tuple. Last, simulation results demonstrate that cooperative power control using the proposed algorithms can substantially reduce the sum MSE of AirComp networks.