Beam alignment for mmWave and THz: systematic review

Sundire Madhekwana (), Muhammad Arslan Usman (), Ahtisham Ayyub () and Christos Politis ()
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Sundire Madhekwana: Kingston University London
Muhammad Arslan Usman: Kingston University London
Ahtisham Ayyub: Kingston University London
Christos Politis: Kingston University London

Telecommunication Systems: Modelling, Analysis, Design and Management, 2025, vol. 88, issue 3, No 7, 53 pages

Abstract: Abstract This compact study investigates published research on beam management frameworks for large antenna arrays in mmWave and terahertz (THz) systems. The systematic literature review (SLR) focused on beam alignment and initial access frameworks for mmWave and THz. The investigation uncovered 596 relevant articles, including journals and conference papers from different sources using defined criteria, leading to 73 final studies post-filtering, following our SLR-defined 3-stage screening process. We explained the taxonomy of mmWave and THz beam alignment frameworks by classifying them into beam sweeping-based, context information-based, compressive sensing-based, and Machine Learning/Artificial Intelligence (ML/AI)-based frameworks, as well as Integrated Sensing and Communication (ISAC)-based frameworks, which combine ISAC with other frameworks. In addition, we presented research gaps by identifying and analyzing the limitations of the current frameworks. Lastly, challenges and possible opportunities for future research were highlighted.

Keywords: Beam alignment; MmWave; THz; Compressive sensing; Beam sweeping; ML/AI; Context information; Beam management (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11235-025-01318-7

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