A Novel Two-Stage Beam Selection Algorithm in mmWave Hybrid Beamforming System

Yu, Hongkang; Qu, Wanyue; Fu, Yusun; Jiang, Chenglong; Zhao, Yuping

doi:10.1109/lcomm.2019.2913385

Cited by 22 publications

(24 citation statements)

References 9 publications

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“…In order to employ beam selection on a snapshot of SV channel model, like [13]- [18], we assume that the channel is time invariant, BS and users both know perfect Channel State Information (CSI). Afterwards, a widely used zero-forcing (ZF) precoder is adopted in baseband.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Nevertheless, these schemes [13]- [16] limit that the number of beams (RF chains) and users must be equal (i.e., N b = K), which leads to degradation of performance and system flexibility. Therefore, maximization of the SINR selection (MSS), maximization of the capacity selection (MCS) [17], and two-stage selection schemes [18] are proposed with variable number of beams.…”

Section: Introductionmentioning

confidence: 99%

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Heuristic Search Inspired Beam Selection Algorithms for mmWave MU-MIMO System With Discrete Lens Array

Wang

Zhang

Zhu³

2021

IEEE Access

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By employing beam selection in beamspace, the costs of hardware and power consumption in millimeter wave (mmWave) massive multiple input multiple output (MIMO) system can be significantly reduced without obvious performance loss. In most existing schemes, there is a limitation that the number of beams (radio frequency (RF) chains) and users must be equal, which leads to degradation of system performance and flexibility. To overcome this limitation, we formulate beam selection as a discrete combinational optimization problem of binary selection vector to maximize the spectral efficiency of multi-user MIMO (MU-MIMO) system. In order to solve this problem, we propose enhanced CE (ECE)based and GA-based algorithms inspired by cross entropy (CE) method and genetic algorithm (GA) in heuristic search. Moreover, we analyze the complexity of proposed algorithms and provide a graphical representation of convergence property for ECE-based algorithm. Simulation results demonstrate that the proposed algorithms are able to achieve good performance with variable number of beams, and verify the validity of graphical representation of convergence property for ECE-based algorithm.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Heuristic Search Inspired Beam Selection Algorithms for mmWave MU-MIMO System With Discrete Lens Array

Wang

Zhang

Zhu³

2021

IEEE Access

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“…Authors in [16] propose a minimum mean square error (MMSE)-based HBF design for massive MIMO pointto-point communications in which a manifold optimizationbased scheme is introduced to deal with the fixed amplitude constraint of RF beamforming directly. In [17], a two-step algorithm is proposed for deriving RF beamforming in an HBF structure. First, by formulating a convex problem, an initial beam set is determined to maximize the lower bound of the sum-rate.…”

Section: Introductionmentioning

confidence: 99%

Transceiver Design in Millimeter Wave Full-Duplex Multi-User Massive MIMO Communication Systems

Darabi

Cırık²,

Lampe

2021

IEEE Access

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We consider hybrid transmit precoding and receive combining in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) multi-user cellular system, where a full-duplex (FD) base station (BS) serves multiple half-duplex (HD) uplink and downlink users simultaneously. Jointly deriving the four matrices of analog precoder, digital precoder, analog combiner, and digital combiner for mmWave FD communications is intractable. Hence, we propose two approaches for either designing joint analog and digital beamformers separately at the transmitters and receivers, or jointly deriving transmit precoders and receive combiners with separate designs of analog and digital beamforming matrices that maximize the sum-rate. In the first proposed method, at the first step, we derive an iterative solution for the fully digital minimum-mean-square-error (MMSE) transmit/receive beamforming. Then, exploiting the spatial structure of mmWave channels, sparse approximation problems are formulated to jointly design radio frequency (RF) and baseband filters approximating the fully digital beamformers via orthogonal-matchingpursuit (OMP) algorithm. To reduce the computational complexity of the first proposed method, which is mainly caused by the iterations between the transmit and receive beamformings, in the second presented scheme, transmit precoding and receive combining matrices are calculated jointly, while RF and digital beamformings are derived separately. More specifically, digital beamforming matrices are derived using the block diagonalization (BD) approach to mitigate the intra-user and inter-users interference, and analog filters are calculated via solving sum-rate maximization problem. In the simulation results, it is shown that our proposed OMP-based hybrid beamforming (HBF) scheme outperforms other HBF approaches for mmWave FD communications in the literature. In addition, it is shown that when the number of RF chains is at least double the number of data streams, the proposed BD-based HBF further improves over the OMPbased HBF in terms of sum-rate. Thus, choosing between OMP-based and BD-based HBF depends on the number of available RF chains.INDEX TERMS Full-duplex (FD), millimeter wave communications, multi-user (MU)-MIMO, transceiver design, hybrid beamforming (HBF), orthogonal-matching-pursuit (OMP), block diagonalization (BD).

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“…Thus to ensure high performance, choosing the suitable BS to user equipment (UE) beam-pair from the set of all the possible directional beams is a crucial task. Beam selection has been conventionally addressed using exhaustive search or multi-level selection approach as in [12,15]. However, with these techniques, large number of beams at mmW BSs leads to large beam training overhead and hence unacceptable latency to access the mmW network.…”

Section: Introductionmentioning

confidence: 99%

DNN Based Beam Selection in mmW Heterogeneous Networks

Jagyasi¹,

Coupechoux²

2021

Preprint

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We consider a heterogeneous cellular network wherein multiple small cell millimeter wave (mmW) base stations (BSs) coexist with legacy sub-6GHz macro BSs. In the mmW band, small cells use multiple narrow beams to ensure sufficient coverage and User Equipments (UEs) have to select the best small cell and the best beam in order to access the network. This process usually based on exhaustive search may introduce unacceptable latency. In order to address this issue, we rely on the sub-6GHz macro BS support and propose a deep neural network (DNN) architecture that utilizes basic components from the Channel State Information (CSI) of sub-6GHz network as input features. The output of the DNN is the mmW BS and beam selection that can provide the best communication performance. In the set of features, we avoid using the UE location, which may not be readily available for every device. We formulate a mmW BS selection and beam selection problem as a classification and regression problem respectively and propose a joint solution using a branched neural network. The numerical comparison with the conventional exhaustive search results shows that the proposed design demonstrate better performance than exhaustive search in terms of latency with at least 85% accuracy.

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A Novel Two-Stage Beam Selection Algorithm in mmWave Hybrid Beamforming System

Cited by 22 publications

References 9 publications

Heuristic Search Inspired Beam Selection Algorithms for mmWave MU-MIMO System With Discrete Lens Array

Heuristic Search Inspired Beam Selection Algorithms for mmWave MU-MIMO System With Discrete Lens Array

Transceiver Design in Millimeter Wave Full-Duplex Multi-User Massive MIMO Communication Systems

DNN Based Beam Selection in mmW Heterogeneous Networks

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