Nested Grassmannian Codebooks for Quantizing MIMO Precoders on the Flag Manifold

In MIMO systems, the channel can be decomposed using Singular Value Decomposition (SVD). The resulting unitary matrices, used as precoders, are fed back to the transmitter to enhance rates. Their non-uniqueness enables efficient quantization on Flag manifolds. While previous studies have investigated manifold-based precoder feedback approaches, an incremental subspace-based quantization approach remains unexplored. We propose a nested Grassmannian quantizer for Flag elements, which incrementally builds codebook dimensions. Simulations show the proposed method effectively captures Flag elements and outperforms existing approaches, with significant gains.

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Publication Details

Journal
IEEE Communications Letters
Published
2025-04-04
DOI
https://doi.org/10.1109/lcomm.2025.3557002
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Nested Grassmannian Codebooks for Quantizing MIMO Precoders on the Flag Manifold

Naresh Kolla, Debasattam Pal, Kumar Appaiah, Parth Mehta
IEEE Communications Letters
Advanced MIMO Systems Optimization
article

Nested Grassmannian Codebooks for Quantizing MIMO Precoders on the Flag Manifold

Naresh Kolla, Debasattam Pal, Kumar Appaiah, Parth Mehta
article en

Abstract

In MIMO systems, the channel can be decomposed using Singular Value Decomposition (SVD). The resulting unitary matrices, used as precoders, are fed back to the transmitter to enhance rates. Their non-uniqueness enables efficient quantization on Flag manifolds. While previous studies have investigated manifold-based precoder feedback approaches, an incremental subspace-based quantization approach remains unexplored. We propose a nested Grassmannian quantizer for Flag elements, which incrementally builds codebook dimensions. Simulations show the proposed method effectively captures Flag elements and outperforms existing approaches, with significant gains.

IEEE Communications LettersVol. 29(6)
Indian Institute of Technology Bombay (IN)
Qualcomm
Openalex Percentile: Top 95%
Advanced MIMO Systems Optimization
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Nested Grassmannian Codebooks for Quantizing MIMO Precoders on the Flag Manifold — Naresh Kolla, Debasattam Pal, et al. · IEEE Communications Letters (2025) | TGRS Research Map | TGRS