Compressive Beam Alignment for Indoor Millimeter-Wave Systems
April Junio, Rafaela Lomboy, Raj Sai Sohel Bandari, and Mohammed E., Eltayeb

TL;DR
This paper introduces a novel compressive sensing-based beam alignment method for indoor millimeter-wave systems that is robust to environmental dynamics and does not require prior knowledge of the user's antenna or channel model.
Contribution
The proposed technique is agnostic to user antenna architecture and channel specifics, using DCT energy compaction to improve beam alignment accuracy with limited measurements.
Findings
Successful recovery of mm-wave power distribution at 60 GHz
Achieves accurate beam alignment with fewer measurements than exhaustive search
Robust performance in dynamic indoor environments
Abstract
The dynamic nature of indoor environments poses unique challenges for next-generation millimeter-wave (mmwave) connectivity. These challenges arise from blockages due to mobile obstacles, mm-wave signal scattering caused by indoor surfaces, and user phased antenna array imperfections. Traditional compressed sensing (CS) based beam alignment techniques enable swift mm-wave connectivity with a limited number of measurements. These techniques, however, rely on prior knowledge of the communication channel model and the user's array manifold to design the sensing matrix and minimize angle quantization errors. This limits their effectiveness in dynamic environments. This paper proposes a novel CS-based beam alignment technique for mm-wave systems operating in indoor environments. Unlike prior work that rely on knowledge of the user's antenna architecture, communication codebook, and channel,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMicrowave Engineering and Waveguides · Millimeter-Wave Propagation and Modeling · Advanced Antenna and Metasurface Technologies
MethodsDiscrete Cosine Transform
