Low-Complexity OTFS-Based Over-the-Air Computation Design for Time-Varying Channels

TL;DR

This paper develops low-complexity OTFS-based over-the-air computation schemes for time-varying channels, improving estimation accuracy and efficiency in high-mobility scenarios with multipath effects.

Contribution

It introduces three novel OTFS-based schemes (S1, S2, S3) for function estimation over time-varying channels, balancing MSE performance and computational complexity.

Findings

S3 achieves the lowest MSE but with higher complexity.

S2 reduces both MSE and complexity compared to benchmarks.

S1 performs best at low SNR with lower complexity.

Abstract

This paper investigates over-the-air computation (AirComp) over multiple-access time-varying channels, where devices with high mobility transmit their sensing data to a fusion center (FC) for averaging. To combat the Doppler shift induced by time-varying channels, each device adopts orthogonal time frequency space (OTFS) modulation. Our objective is minimizing the mean squared error (MSE) for the target function estimation. Due to the multipath time-varying channels, the OTFS-based AirComp not only suffers from noise but also interference. Specifically, we propose three schemes, namely S1, S2, and S3, for the target function estimation. S1 directly estimates the target function under the impacts of noise and interference. S2 mitigates the interference by introducing a zero padding-assisted OTFS. In S3, we propose an iterative algorithm to estimate the function in a matrix form. In the numerical results, we evaluate the performance of S1, S2, and S3 from the perspectives of MSE and computational complexity, and compare them with benchmarks. Specifically, compared to benchmarks, S3 outperforms them with a significantly lower MSE but incurs a higher computational complexity. In contrast, S2 demonstrates a reduction in both MSE and computational complexity. Lastly, S1 shows superior error performance at small SNR and reduced computational complexity.