Optimal Discrete Spatial Compression for Beamspace Massive MIMO Signals
Zhiyuan Jiang, Sheng Zhou, Zhisheng Niu

TL;DR
This paper proposes a novel beam combination method using low-resolution digital phase shifters to reduce RF chain count in beamspace massive MIMO systems, addressing power leakage and channel estimation issues.
Contribution
Introduction of a discrete beam combination scheme with a branch-and-bound approach for optimal weights, reducing RF chains beyond traditional beamspace methods.
Findings
RF chains reduced by up to 25% with one-bit phase shifters
Closed-form solution for sub-problem in beam combination
Sequential greedy scheme with linear complexity
Abstract
Deploying massive number of antennas at the base station side can boost the cellular system performance dramatically. Meanwhile, it however involves significant additional radio-frequency (RF) front-end complexity, hardware cost and power consumption. To address this issue, the beamspace-multiple-input-multiple-output (beamspace-MIMO) based approach is considered as a promising solution. In this paper, we first show that the traditional beamspace-MIMO suffers from spatial power leakage and imperfect channel statistics estimation. A beam combination module is hence proposed, which consists of a small number (compared with the number of antenna elements) of low-resolution (possibly one-bit) digital (discrete) phase shifters after the beamspace transformation to further compress the beamspace signal dimensionality, such that the number of RF chains can be reduced beyond beamspace…
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.
