Antenna Selection in Switch-Based MIMO Arrays via DOA Threshold Region Approximation

Hui Chen, Tarig Ballal, Mohammed E. Eltayeb, Tareq Y. Al-Naffouri

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Direction-of-arrival (DOA) information is vital for multiple-input-multiple-output (MIMO) systems to complete localization and beamforming tasks. Switched antenna arrays have recently emerged as an effective solution to reduce the cost and power consumption of MIMO systems. Switch-based array architectures connect a limited number of radio frequency chains to a subset of the antenna elements forming a subarray. This paper addresses the problem of antenna selection to optimize DOA estimation performance. We first perform a subarray layout alignment process to remove subarrays with identical beampatterns and create a unique subarray set. By using this set, and based on a DOA threshold region performance approximation, we propose two antenna selection algorithms; a greedy algorithm and a deep-learning-based algorithm. The performance of the proposed algorithms is evaluated numerically. The results show a significant performance improvement over selected benchmark approaches in terms of DOA estimation in the threshold region and computational complexity.
Original languageEnglish (US)
Pages (from-to)1-6
Number of pages6
JournalIEEE Transactions on Vehicular Technology
StatePublished - Jul 19 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-09-14
Acknowledged KAUST grant number(s): ORA-CRG2021-4695
Acknowledgements: This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. ORA-CRG2021-4695.


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