Angle Domain Hybrid Precoding and Channel Tracking for Millimeter Wave Massive MIMO Systems

Zhao, Jianwei; Gao, Feifei; Jia, Weimin; Zhang, Shun; Jin, Shi; Lin, Hai

doi:10.1109/twc.2017.2732405

Cited by 175 publications

(91 citation statements)

References 36 publications

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“…Matching the columns in F RF with the true steering vector a(θ dl p , 0, 0) is named as anglespace beamforming, and the corresponding beams are shown in Fig. 3(a), [85], [131], [132]. Alternatively, if F RF only supports M fixed directions, then the best beamforming vectors should be selected from a predetermined codebook, i.e., beamspace beamforming, [82], [83], [133], [134].…”

Section: A Hybrid Precodingmentioning

confidence: 99%

“…Moreover, due to the limited number of RF chains, we only have part of its spatial (time) domain impulse response depending on how the RF chains are connected to antennas. The problem becomes OFDM sparse frequency domain channel estimation with insufficient impulse response beamforming matrix F RF is obtained, the digital precoder f BB can be derived following minimum mean square error (MMSE) criterion [85], [135], [136] or the zero-forcing (ZF) criterion [132].…”

Section: Channel and Aoa Estimation Ith Imited Rf Chainsmentioning

confidence: 99%

See 1 more Smart Citation

An Overview of Enhanced Massive MIMO With Array Signal Processing Techniques

Wang

Gao

Jin

et al. 2019

IEEE J. Sel. Top. Signal Process.

Self Cite

140

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In the past ten years, there have been tremendous research progresses on massive MIMO systems, most of which stand from the communications viewpoint. A new trend of investigating massive MIMO, especially for the sparse scenario like millimeter wave (mmWave) transmission, is to re-build the transceiver design from array signal processing viewpoint that could deeply exploit the half-wavelength array and provide enhanced performances in many aspects. For example, the high dimensional channel could be decomposed into small amount of physical parameters, e.g., angle of arrival (AoA), angle of departure (AoD), multi-path delay, Doppler shift, etc. As a consequence, transceiver techniques like synchronization, channel estimation, beamforming, precoding, multi-user access, etc., can be re-shaped with these physical parameters, as opposed to those designed directly with channel state information (CSI). Interestingly, parameters like AoA/AoD and multi-path delay are frequency insensitive and thus can be used to guide the downlink transmission from uplink training even for FDD systems. Moreover, some phenomena of massive MIMO that were vaguely revealed previously can be better explained now with array signal processing, e.g., the beam squint effect. In all, the target of this paper is to present an overview of recent progress on merging array signal processing into massive MIMO communications as well as its promising future directions.Index Terms-massive MIMO, array signal processing, mmWave transmission, angle-delay-Doppler reciprocity, beam squint.

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Section: A Hybrid Precodingmentioning

confidence: 99%

Section: Channel and Aoa Estimation Ith Imited Rf Chainsmentioning

confidence: 99%

An Overview of Enhanced Massive MIMO With Array Signal Processing Techniques

Wang

Gao

Jin

et al. 2019

IEEE J. Sel. Top. Signal Process.

Self Cite

140

View full text Add to dashboard Cite

show abstract

“…Most of the existing approaches are based on some iterations (or equivalently a huge number of pilot signals) among transmitters and receivers, which could be very time-consuming given the low transmission rate of the control signals [63]. To reduce the beamforming setup delay, [140] and [141] augmented the beamforming part by a tracking algorithm based on extended Kalman filters, which track the second-order statistics of the channel. However, those approaches need a mobility model.…”

Section: E Transmission Capacity Boosting and Sharing Techniquesmentioning

confidence: 99%

Low-Latency Networking: Where Latency Lurks and How to Tame It

et al. 2019

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While the current generation of mobile and fixed communication networks has been standardized for mobile broadband services, the next generation is driven by the vision of the Internet of Things and mission critical communication services requiring latency in the order of milliseconds or submilliseconds. However, these new stringent requirements have a large technical impact on the design of all layers of the communication protocol stack. The cross layer interactions are complex due to the multiple design principles and technologies that contribute to the layers' design and fundamental performance limitations. We will be able to develop low-latency networks only if we address the problem of these complex interactions from the new point of view of sub-milliseconds latency. In this article, we propose a holistic analysis and classification of the main design principles and enabling technologies that will make it possible to deploy low-latency wireless communication networks. We argue that these design principles and enabling technologies must be carefully orchestrated to meet the stringent requirements and to manage the inherent trade-offs between low latency and traditional performance metrics. We also review currently ongoing standardization activities in prominent standards associations, and discuss open problems for future research.

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“…It is still challenging to handle (P2) due to the complicated structure of its objective function in (17), and therefore we first simplify it into a more tractable form.…”

Section: B Problem Formulationmentioning

confidence: 99%

“…Specifically, the CSI in current channel realization is closely related to that of the previous one, and this relationship can be used to speed up the beam training procedure. This type of priori-aided beam training technique is referred to as channel tracking or beam tracking in the literature [14]- [17]. To date, most existing works that investigate beam tracking techniques for mmWave channels have focused on the assumption that the values of AoA and AoD vary smoothly.…”

Section: Introductionmentioning

confidence: 99%

Beam Allocation for Millimeter-Wave MIMO Tracking Systems

Zhang

Chen

et al. 2020

IEEE Trans. Veh. Technol.

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In this paper, we propose a new beam allocation strategy aiming to maximize the average successful tracking probability (ASTP) of time-varying millimeter-wave MIMO systems. In contrast to most existing works that employ one transmitting-receiving (Tx-Rx) beam pair once only in each training period, we investigate a more general framework, where the Tx-Rx beam pairs are allowed to be used repeatedly to improve the received signal powers in specific directions. In the case of orthogonal Tx-Rx beam pairs, a power-based estimator is employed to track the time-varying AoA and AoD of the channel, and the resulting training beam pair sequence design problem is formulated as an integer nonlinear programming (I-NLP) problem. By dividing the feasible region into a set of subregions, the formulated I-NLP is decomposed into a series of concave sub I-NLPs, which can be solved by recursively invoking a nonlinear branch-and-bound algorithm. To reduce the computational cost, we relax the integer constraints of each sub I-NLP and obtain a low-complexity solution via solving the Karush-Kuhn-Tucker conditions of their relaxed problems. For the case when the Tx-Rx beam pairs are overlapped in the angular space, we estimate the updated AoA and AoD via an orthogonal matching pursuit (OMP) algorithm. Moreover, since no explicit expression for the ASTP exists for the OMP-based estimator, we derive a closed-form lower bound of the ASTP, based on which a favorable beam pair allocation strategy can be obtained. Numerical results demonstrate the superiority of the proposed beam allocation strategy over existing benchmarks. Index TermsMillimeter wave, time-varying channel, beam training, beam tracking, training beam sequence design.

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Angle Domain Hybrid Precoding and Channel Tracking for Millimeter Wave Massive MIMO Systems

Cited by 175 publications

References 36 publications

An Overview of Enhanced Massive MIMO With Array Signal Processing Techniques

An Overview of Enhanced Massive MIMO With Array Signal Processing Techniques

Low-Latency Networking: Where Latency Lurks and How to Tame It

Beam Allocation for Millimeter-Wave MIMO Tracking Systems

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