Interference-Robust Non-Coherent Over-the-Air Computation for Decentralized Optimization

Explainable & Ethical AI

Published: arXiv: 2602.12426v1

Authors

Nicolò Michelusi

Abstract

Non-coherent over-the-air (NCOTA) computation enables low-latency and bandwidth-efficient decentralized optimization by exploiting the average energy superposition property of wireless channels. It has recently been proposed as a powerful tool for executing consensus-based optimization algorithms in fully decentralized systems. A key advantage of NCOTA is that it enables unbiased consensus estimation without channel state information at either transmitters or receivers, requires no transmission scheduling, and scales efficiently to dense network deployments. However, NCOTA is inherently susceptible to external interference, which can bias the consensus estimate and deteriorate the convergence of the underlying decentralized optimization algorithm. In this paper, we propose a novel interference-robust (IR-)NCOTA scheme. The core idea is to apply a coordinated random rotation of the frame of reference across all nodes, and transmit a pseudo-random pilot signal, allowing to transform external interference into a circularly symmetric distribution with zero mean relative to the rotated frame. This ensures that the consensus estimates remain unbiased, preserving the convergence guarantees of the underlying optimization algorithm. Through numerical results on a classification task, it is demonstrated that IR-NCOTA exhibits superior performance over the baseline NCOTA algorithm in the presence of external interference.

Paper Summary

Problem

In many real-world scenarios, such as search and rescue operations or remote rural regions, traditional centralized learning frameworks are impractical due to limited infrastructure or unreliable connections. This paper addresses the challenge of decentralized optimization and learning in wireless networks, where nodes communicate with each other and rely on peer-to-peer connections.

Key Innovation

The researchers propose a novel Interference-Robust Non-Coherent Over-the-Air (IR-NCOTA) computation scheme that enables decentralized optimization in wireless networks affected by external interference. This innovation extends the applicability of the NCOTA framework, which enables decentralized consensus without channel state information or transmission scheduling.

Practical Impact

The proposed IR-NCOTA scheme has significant practical implications for decentralized learning and optimization in various domains, such as remote sensing, distributed inference, multi-agent coordination, and machine learning. By enabling unbiased consensus estimation and preserving the convergence guarantees of the underlying optimization algorithm, IR-NCOTA can be applied in environments where traditional NCOTA fails due to external interference.

Analogy / Intuitive Explanation

Imagine a group of nodes trying to reach a consensus on a solution, but with a noisy and interfering signal that distorts their communication. The IR-NCOTA scheme is like a clever way to "scramble" the interference signal, making it appear zero-mean and allowing the nodes to converge on a solution despite the noise. This is achieved through a coordinated random rotation of the frame of reference and a pseudo-random pilot transmission, which jointly render the distortion introduced by the interfering signal zero-mean in expectation.

Paper Information

Categories:

eess.SP cs.LG cs.MA

Published Date:

arXiv ID:

2602.12426v1

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