High-Mobility Wideband Massive MIMO Communications: Doppler Compensation, Analysis and Scaling Laws

Wei, Guo; Zhang, Weile; Mu, Pengcheng; Gao, Feifei; Lin, Hai

doi:10.1109/twc.2019.2911508

Cited by 74 publications

(56 citation statements)

References 36 publications

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“…By exploiting the angle information of users, the carrier frequency offset (CFO) was estimated for each user individually through a joint spatial-frequency alignment procedure. Moreover, the authors in [121] and [122] addressed the joint estimation issue of Doppler shifts and CFO in high-mobility downlink massive MIMO systems, where a high-resolution beamforming network was designed to separate different Doppler and CFOs in the angle domain.…”

Section: Synchronizationmentioning

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.

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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: Synchronizationmentioning

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

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“…Hence, they all attain the maximum atω = 0. Apart from this, the following observations (22), (24) and (26) (26)).…”

Section: B Impact Of Beamforming Directions and Antenna Spacing On Cmentioning

confidence: 83%

“…• Explicit PSD expression with wider applicability and clearer insights: Unlike [23], [24] where the channel PSD is approximatively derived, we demonstrate that the channel PSD can be exactly expressed as the product of a pattern function and a beam-distortion function. The former can be uniquely determined by the antenna spacing and in fact corresponds to the radiation pattern of ULA, while the latter depends on how the beamforming directions are configured.…”

Section: Introductionmentioning

confidence: 94%

“…The derivation of Doppler spread requires the channel PSD, which is the Fourier Transform of channel autocorrelation. Since different channel taps are independent and have identical statistical properties [11], [24], we only consider one tap for simplicity, i.e., L = 1, d 1 = 0. By ignoring the noise item, the signal at the BS obtained after Doppler shifts compensation and multi-branch beamforming can be expressed as…”

Section: System Modelmentioning

confidence: 99%

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Beamforming Network Optimization for Reducing Channel Time Variation in High-Mobility Massive MIMO

Zhang

Gao

et al. 2019

IEEE Trans. Commun.

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Communications in high-mobility environments have caught a lot of attentions recently. In this paper, fast time-varying channels for massive multiple-input multiple-output (MIMO) systems are addressed. We derive the exact channel power spectrum density (PSD) for the uplink from a high-speed railway (HSR) to a base station (BS) and propose to further reduce the channel time variation via beamforming network optimization. A large-scale uniform linear array (ULA) is equipped at the HSR to separate multiple Doppler shifts in angle domain through high-resolution transmit beamforming. Each branch comprises a dominant Doppler shift, which can be compensated to suppress the channel time variation, and we derive the channel PSD and the Doppler spread to assess the residual channel time variation. Interestingly, the channel PSD can be exactly expressed as the product of a pattern function and a beam-distortion function. The former reflects the impact of array aperture and is the converted radiation pattern of ULA, while the latter depends on the configuration of beamforming directions. Inspired by the PSD analysis, we introduce a common configurable amplitudes and phases (CCAP) parameter to optimize the beamforming network, by partly removing the constant modulus quantized phase constraints of matched filter (MF) beamformers. In this way, the residual Doppler shifts can be ulteriorly suppressed, further reducing the residual channel time variation. The optimal CCAP parameter minimizing the Doppler spread is derived in a closed form. Numerical results are provided to corroborate both the channel PSD analysis and the superiority of beamforming network optimization technique.Index Terms-High-mobility communication, time-varying channel, power spectrum density (PSD), Doppler spread, angledomain massive MIMO, beamforming network optimization.

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“…time-varying channel estimation. On the other hand, for uplink high-mobility transmission, it has been demonstrated that the harmful effect of Doppler shift can be mitigated by massive MIMO technique [10]. Owing to the angle-domain Doppler shifts compensation technique, the asymptotic scaling law in [10] showed that, the Doppler spread decreases approximately as 1/…”

Section: Introductionmentioning

confidence: 99%

High-Mobility CoMP Massive MIMO Uplink Transmissions: Channel PSD Analysis and Doppler Spread Suppression

Zhang

2020

IEEE Access

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Coordinated Multi-Point transmission/reception (CoMP) is one of the promising techniques for high-mobility wireless communications systems to increase cell edge user throughput in both uplink and downlink transmission. In this paper, we consider the high-mobility CoMP uplink transmission, where a high-speed terminal (HST) simultaneously transmits signals to multiple base stations (BSs) with angledomain Doppler shifts compensation. We derive the exact channel power spectrum density (PSD) for uplink CoMP transmissions. The antenna weighting technique is then proposed to suppress the Doppler spread, where an optimization problem is formulated to minimize the maximum Doppler spread among all the BSs. Numerical results are provided to corroborate both the PSD analysis and the superiority of antenna weighting technique. INDEX TERMS High-mobility communication, coordinated multi-point transmission/reception (CoMP), power spectrum density (PSD), Doppler spread.

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High-Mobility Wideband Massive MIMO Communications: Doppler Compensation, Analysis and Scaling Laws

Cited by 74 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

Beamforming Network Optimization for Reducing Channel Time Variation in High-Mobility Massive MIMO

High-Mobility CoMP Massive MIMO Uplink Transmissions: Channel PSD Analysis and Doppler Spread Suppression

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