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A Scalable Platform for Single-Snapshot Direction Of Arrival (DOA) Estimation in Massive MIMO Systems

Authors:

Adou Sangbone Assoa,

Arijit RaychowdhuryAuthors Info & Claims

GLSVLSI '23: Proceedings of the Great Lakes Symposium on VLSI 2023

Pages 631 - 637

https://doi.org/10.1145/3583781.3590212

Published: 05 June 2023 Publication History

Abstract

With the development of Radio Frequency (RF) massive Multiple Inputs-Multiple Outputs (MIMO) array systems for Beyond 5G (B5G) applications, real-time DOA estimation has become challenging due to large antenna architectures producing a staggering amount of data. Traditional DOA estimation techniques are not scalable since they either require multiple snapshots of data or computationally expensive matrix operations hindering fast processing. To address these challenges, we propose a single-snapshot DOA processor based on the Alternating Direction Method of Multipliers (ADMM). The algorithm is modified to handle complex-valued measurements. We develop a High-Level Synthesis (HLS) based scalable FPGA design to handle multiple array sizes ranging from 8 to 512 elements. Our system implemented on a Xilinx Ultra96-V2 FPGA, operates at a frequency of 100 MHz with a sub-200μs processing time for a 512-antenna array, thereby meeting the millisecond-level processing time specifications of B5G applications.

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Cited By

Sangbone Assoa ABhat ARyu SRaychowdhury A(2025)MDS-DOA: Fusing Model-Based and Data-Driven Approaches for Modular, Distributed, and Scalable Direction-of-Arrival EstimationIEEE Transactions on Circuits and Systems I: Regular Papers10.1109/TCSI.2024.346992872:2(941-952)Online publication date: Feb-2025
https://doi.org/10.1109/TCSI.2024.3469928
Bhattacharjya RSarkar AMaity BDutt N(2024)MUSIC-Lite: Efficient MUSIC Using Approximate Computing: An OFDM Radar Case StudyIEEE Embedded Systems Letters10.1109/LES.2024.344020816:4(329-332)Online publication date: Dec-2024
https://doi.org/10.1109/LES.2024.3440208
Hussain ATayem NSoliman A(2024)Low Complexity DOA Estimation of Multiple Coherent Sources Using a Single Direct Data SnapshotIEEE Access10.1109/ACCESS.2023.334841412(2371-2388)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2023.3348414

Index Terms

A Scalable Platform for Single-Snapshot Direction Of Arrival (DOA) Estimation in Massive MIMO Systems
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems
      1. Digital signal processing

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Published In

cover image ACM Conferences

GLSVLSI '23: Proceedings of the Great Lakes Symposium on VLSI 2023

June 2023

731 pages

ISBN:9798400701252

DOI:10.1145/3583781

General Chairs:
Himanshu Thapliyal
University of Tennessee, Knoxville, USA
,
Ronald DeMara
University of Central Florida, USA
,
Program Chairs:
Inna Partin-Vaisband
University of Illinois Chicago, USA
,
Srinivas Katkoori
University of South Florida, USA

Copyright © 2023 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 05 June 2023

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GLSVLSI '23: Great Lakes Symposium on VLSI 2023

June 5 - 7, 2023

TN, Knoxville, USA

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Overall Acceptance Rate 312 of 1,156 submissions, 27%

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Cited By

Sangbone Assoa ABhat ARyu SRaychowdhury A(2025)MDS-DOA: Fusing Model-Based and Data-Driven Approaches for Modular, Distributed, and Scalable Direction-of-Arrival EstimationIEEE Transactions on Circuits and Systems I: Regular Papers10.1109/TCSI.2024.346992872:2(941-952)Online publication date: Feb-2025
https://doi.org/10.1109/TCSI.2024.3469928
Bhattacharjya RSarkar AMaity BDutt N(2024)MUSIC-Lite: Efficient MUSIC Using Approximate Computing: An OFDM Radar Case StudyIEEE Embedded Systems Letters10.1109/LES.2024.344020816:4(329-332)Online publication date: Dec-2024
https://doi.org/10.1109/LES.2024.3440208
Hussain ATayem NSoliman A(2024)Low Complexity DOA Estimation of Multiple Coherent Sources Using a Single Direct Data SnapshotIEEE Access10.1109/ACCESS.2023.334841412(2371-2388)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2023.3348414

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