Nianzu Li, Peiran Wu, Boyu Ning, Lipeng Zhu, Weidong Mei
{"title":"Over-the-Air Computation via 2D Movable Antenna Array","authors":"Nianzu Li, Peiran Wu, Boyu Ning, Lipeng Zhu, Weidong Mei","doi":"arxiv-2409.10351","DOIUrl":null,"url":null,"abstract":"Movable antenna (MA) has emerged as a promising technology for improving the\nperformance of wireless communication systems, which enables local movement of\nthe antennas to create more favorable channel conditions. In this letter, we\nadvance its application for over-the-air computation (AirComp) network, where\nan access point is equipped with a two-dimensional (2D) MA array to aggregate\nwireless data from massive users. We aim to minimize the computation mean\nsquare error (CMSE) by jointly optimizing the antenna position vector (APV),\nthe receive combining vector at the access point and the transmit coefficients\nfrom all users. To tackle this highly non-convex problem, we propose a two-loop\niterative algorithm, where the particle swarm optimization (PSO) approach is\nleveraged to obtain a suboptimal APV in the outer loop while the receive\ncombining vector and transmit coefficients are alternately optimized in the\ninner loop. Numerical results demonstrate that the proposed MA-enhanced AirComp\nnetwork outperforms the conventional network with fixed-position antennas\n(FPAs).","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10351","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Movable antenna (MA) has emerged as a promising technology for improving the
performance of wireless communication systems, which enables local movement of
the antennas to create more favorable channel conditions. In this letter, we
advance its application for over-the-air computation (AirComp) network, where
an access point is equipped with a two-dimensional (2D) MA array to aggregate
wireless data from massive users. We aim to minimize the computation mean
square error (CMSE) by jointly optimizing the antenna position vector (APV),
the receive combining vector at the access point and the transmit coefficients
from all users. To tackle this highly non-convex problem, we propose a two-loop
iterative algorithm, where the particle swarm optimization (PSO) approach is
leveraged to obtain a suboptimal APV in the outer loop while the receive
combining vector and transmit coefficients are alternately optimized in the
inner loop. Numerical results demonstrate that the proposed MA-enhanced AirComp
network outperforms the conventional network with fixed-position antennas
(FPAs).