Towards Optimal Constellation Design for Digital Over-the-Air Computation

TL;DR

This paper introduces a novel digital modulation framework for over-the-air computation that optimizes constellation design to minimize error over noisy channels, with analytical solutions and extensions for various scenarios.

Contribution

It formulates the optimal constellation design as a nonlinear system, derives conditions for uniqueness, and provides closed-form solutions in high SNR regimes, advancing digital OAC methods.

Findings

Optimal constellation minimizes MSE under power constraints.

Closed-form solutions derived using Lambert function in high SNR.

Framework extends to higher dimensions and non-Gaussian noise.

Abstract

Over-the-air computation (OAC) has emerged as a key technique for efficient function computation over multiple-access channels (MACs) by exploiting the waveform superposition property of the wireless domain. While conventional OAC methods rely on analog amplitude modulation, their performance is often limited by noise sensitivity and hardware constraints, motivating the use of digital modulation schemes. This paper proposes a novel digital modulation framework optimized for computation over additive white Gaussian noise (AWGN) channels. The design is formulated as an additive mapping problem to determine the optimal constellation that minimizes the mean-squared error (MSE) under a transmit power constraint. We express the optimal constellation design as a system of nonlinear equations and establish the conditions guaranteeing the uniqueness of its solution. In the high signal-to-noise-ratio (SNR) regime, we derive closed-form expressions for the optimal modulation parameters using the generalized Lambert function, providing analytical insight into the system's behavior. Furthermore, we discuss extensions of the framework to higher-dimensional grids corresponding to multiple channel uses, to non-Gaussian noise models, and to computation over real-valued domains via hybrid digital-analog modulation.