Cross-Layer Stream Allocation of mMIMO-OFDM Hybrid Beamforming Video Communications

This paper proposes a source encoding rate control and cross-layer data stream allocation scheme for uplink millimeter-wave (mmWave) multi-user massive MIMO (MU-mMIMO) orthogonal frequency division multiplexing (OFDM) hybrid beamforming video communication systems. Unlike most previous studies that focus on the downlink scenario, our proposed scheme optimizes the uplink transmission while also addressing the limitation of prior works that only consider single-data-stream users. A key distinction of our approach is the integration of cross-layer resource allocation, which jointly considers both the physical layer channel state information (CSI) and the application layer video rate-distortion (RD) function. While traditional methods optimize for spectral efficiency (SE), our proposed method directly maximizes the peak signal-to-noise ratio (PSNR) to enhance video quality, aligning with the growing demand for high-quality video communication. We introduce a novel iterative cross-layer dynamic data stream allocation scheme, where the initial allocation is based on conventional physical-layer data stream allocation, followed by iterative refinement. Through multiple iterations, users with lower PSNR can dynamically contend for data streams, leading to a more balanced and optimized resource allocation. Our approach is a general framework that can incorporate any existing physical-layer data stream allocation as an initialization step before iteration. Simulation results demonstrate that the proposed cross-layer scheme outperforms three conventional physical-layer schemes by 0.4 to 1.14 dB in PSNR for 4-6 users, at the cost of a 1.8 to 2.3× increase in computational complexity (requiring 3.6-5.8 iterations).

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Publication Details

Journal
Sensors
Published
2025-04-17
DOI
https://doi.org/10.3390/s25082554
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
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article

Cross-Layer Stream Allocation of mMIMO-OFDM Hybrid Beamforming Video Communications

Shu‐Ming Tseng, Chao Fang, Yujian Chen, Yung‐Fang Chen
Sensors
Millimeter-Wave Propagation and Modeling
article

Cross-Layer Stream Allocation of mMIMO-OFDM Hybrid Beamforming Video Communications

Shu‐Ming Tseng, Chao Fang, Yujian Chen, Yung‐Fang Chen
article en

Abstract

This paper proposes a source encoding rate control and cross-layer data stream allocation scheme for uplink millimeter-wave (mmWave) multi-user massive MIMO (MU-mMIMO) orthogonal frequency division multiplexing (OFDM) hybrid beamforming video communication systems. Unlike most previous studies that focus on the downlink scenario, our proposed scheme optimizes the uplink transmission while also addressing the limitation of prior works that only consider single-data-stream users. A key distinction of our approach is the integration of cross-layer resource allocation, which jointly considers both the physical layer channel state information (CSI) and the application layer video rate-distortion (RD) function. While traditional methods optimize for spectral efficiency (SE), our proposed method directly maximizes the peak signal-to-noise ratio (PSNR) to enhance video quality, aligning with the growing demand for high-quality video communication. We introduce a novel iterative cross-layer dynamic data stream allocation scheme, where the initial allocation is based on conventional physical-layer data stream allocation, followed by iterative refinement. Through multiple iterations, users with lower PSNR can dynamically contend for data streams, leading to a more balanced and optimized resource allocation. Our approach is a general framework that can incorporate any existing physical-layer data stream allocation as an initialization step before iteration. Simulation results demonstrate that the proposed cross-layer scheme outperforms three conventional physical-layer schemes by 0.4 to 1.14 dB in PSNR for 4-6 users, at the cost of a 1.8 to 2.3× increase in computational complexity (requiring 3.6-5.8 iterations).

SensorsVol. 25(8)
National Taipei University of Technology (TW), National Central University (TW), Beijing University of Technology (CN)
Openalex Percentile: Top 94%
Millimeter-Wave Propagation and Modeling
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