Deep-Learning Based High-Precision Localization with Massive MIMO

Tian, Guoda (author): Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,LTH profilområde: AI och digitalisering,LTH profilområden,Lunds Tekniska Högskola,Communications Engineering,Lund University Research Groups,LTH Profile Area: AI and Digitalization,LTH Profile areas,Faculty of Engineering, LTH

Yaman, Ilayda (author): Lund University,Lunds universitet,Integrerade elektroniksystem,Forskargrupper vid Lunds universitet,Integrated Electronic Systems,Lund University Research Groups

Sandra, Michiel (author): Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups

Cai, Xuesong (author): Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,Communications Engineering,Lund University Research Groups

Liu, Liang (author): Lund University,Lunds universitet,System på chips (master),Utbildningsprogram, LTH,Lunds Tekniska Högskola,Integrerade elektroniksystem,Forskargrupper vid Lunds universitet,LTH profilområde: Nanovetenskap och halvledarteknologi,LTH profilområden,LTH profilområde: AI och digitalisering,Embedded Electronics Engineering (M.Sc.),Educational programmes, LTH,Faculty of Engineering, LTH,Integrated Electronic Systems,Lund University Research Groups,LTH Profile Area: Nanoscience and Semiconductor Technology,LTH Profile areas,Faculty of Engineering, LTH,LTH Profile Area: AI and Digitalization,Faculty of Engineering, LTH

Tufvesson, Fredrik (author): Lund University,Lunds universitet,Kommunikationsteknologi,Forskargrupper vid Lunds universitet,LTH profilområde: AI och digitalisering,LTH profilområden,Lunds Tekniska Högskola,LU profilområde: Naturlig och artificiell kognition,Lunds universitets profilområden,Communications Engineering,Lund University Research Groups,LTH Profile Area: AI and Digitalization,LTH Profile areas,Faculty of Engineering, LTH,LU Profile Area: Natural and Artificial Cognition,Lund University Profile areas

(creator_code:org_t)

2023
2023
English.
In: IEEE Transactions on Machine Learning in Communications and Networking. - 2831-316X.

Related links:: https://portal.resea... (primary) (free); show more...; https://lup.lub.lu.s...; show less...

Abstract Subject headings

High-precision localization and machine learning (ML) are envisioned to be key technologies in future wireless systems. This paper presents an ML pipeline to solve localization tasks. It consists of multiple parallel processing chains, each trained using a different fingerprint to estimate the position of the user equipment. In this way, ensemble learning can be utilized to fuse all chains to improve localization performance. Nevertheless, a common problem of ML-based techniques is that network training and fine-tuning can be challenging due to the increase in network sizes when applied to (massive) multiple-input multiple-output (MIMO) systems. To address this issue, we utilize a subarray-based approach. We divide the large antenna array into several subarrays, feeding the fingerprints of the subarrays into the pipeline. In our case, such an approach eases the training process while maintaining or even enhancing the performance. We also use the Nyquist sampling theorem to gain insight on how to appropriately sample and average training data. Finally, an indoor measurement campaign is conducted at 3.7 GHz using the Lund University massive MIMO testbed to evaluate the approaches. Localization accuracy at a centimeter level has been reached in this particular measurement campaign.

By the author/editor: Tian, Guoda; Yaman, Ilayda; Sandra, Michiel; Cai, Xuesong; Liu, Liang; Tufvesson, Fredr ...

About the subject

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Electrical Engin ...; and Signal Processin ...

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.