Pareto-Optimal Hybrid Beamforming for Finite-Blocklength Millimeter Wave Systems

Short-packet communication (SPC) is essentially synonymous with ultra-reliable low-latency communication (uRLLC), which must meet stringent latency and reliability requirements. However, achieving efficient hybrid beamforming (HBF) in SPC-based millimeter wave (mmWave) systems is challenging due to the constraints of finite block lengths, limited number of radio frequency chains (RFCs), and owing to the complex optimization of transmit precoders (TPCs). In this work, we investigate the achievable rate region of an SPC-based mmWave downlink system. We harness the HBF for finite block lengths low-latency communication, relying on a low number of RFCs. We formulate a Pareto optimization problem for characterizing the achievable rate region, while considering the transmit power, mmWave hardware, and block length constraints. To solve this highly non-convex problem, we propose a bisection search-based block coordinate descent (Bi-BCD) algorithm, in which we optimize the RF TPC, the baseband (BB) TPC, and the block length. Specifically, we jointly optimize the RF and BB TPCs for a fixed block length, which involves both Remanian conjugate gradient (RCG) and second-order cone programming (SOCP) techniques, and then we optimize the block length by the mixed integer programming method. Subsequently, we update the achievable rate via the bisection search method. Finally, we present simulation results and quantify the efficiency of the proposed scheme.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-01-27
DOI
https://doi.org/10.1109/tvt.2025.3534021
Citations
7
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
5.11

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article

Pareto-Optimal Hybrid Beamforming for Finite-Blocklength Millimeter Wave Systems

Banda Naveen, Aditya K. Jagannatham, Jitendra Singh, Suraj Srivastava et al.
7 citations
IEEE Transactions on Vehicular Technology
Millimeter-Wave Propagation and Modeling
5.11
article

Pareto-Optimal Hybrid Beamforming for Finite-Blocklength Millimeter Wave Systems

Banda Naveen, Aditya K. Jagannatham, Jitendra Singh, Suraj Srivastava, Lajos Hanzo
article en
7 citations

Abstract

Short-packet communication (SPC) is essentially synonymous with ultra-reliable low-latency communication (uRLLC), which must meet stringent latency and reliability requirements. However, achieving efficient hybrid beamforming (HBF) in SPC-based millimeter wave (mmWave) systems is challenging due to the constraints of finite block lengths, limited number of radio frequency chains (RFCs), and owing to the complex optimization of transmit precoders (TPCs). In this work, we investigate the achievable rate region of an SPC-based mmWave downlink system. We harness the HBF for finite block lengths low-latency communication, relying on a low number of RFCs. We formulate a Pareto optimization problem for characterizing the achievable rate region, while considering the transmit power, mmWave hardware, and block length constraints. To solve this highly non-convex problem, we propose a bisection search-based block coordinate descent (Bi-BCD) algorithm, in which we optimize the RF TPC, the baseband (BB) TPC, and the block length. Specifically, we jointly optimize the RF and BB TPCs for a fixed block length, which involves both Remanian conjugate gradient (RCG) and second-order cone programming (SOCP) techniques, and then we optimize the block length by the mixed integer programming method. Subsequently, we update the achievable rate via the bisection search method. Finally, we present simulation results and quantify the efficiency of the proposed scheme.

IEEE Transactions on Vehicular TechnologyVol. 74(6)
Indian Institute of Technology Jodhpur (IN), University of Southampton (GB), Indian Institute of Technology Kanpur (IN)
Indian Institute of Technology Jodhpur, Engineering and Physical Sciences Research Council
Affordable and clean energy
Openalex Percentile: Top 5%
Millimeter-Wave Propagation and Modeling
5.11
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