Exploiting Dynamic Sparsity for Downlink FDD-Massive MIMO Channel Tracking

Lian, Lixiang; Liu, An; Lau, Vincent K. N.

doi:10.1109/tsp.2019.2896179

Cited by 49 publications

(42 citation statements)

References 29 publications

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“…Finally, an MMSE beamformer is used at the AP to cancel the interference that arises in the multi-user setting. The SINR and the achievable rate after MMSE beamforming are computed by using H UL,GMP in (11).…”

Section: B Link Configuration In a Multi-user Settingmentioning

confidence: 99%

“…Our framework allows applying such dynamic CS techniques for channel estimation and beam alignment in short range settings. Dynamic CS-based channel estimation techniques were developed for far field systems in [6], [11]- [13] to exploit structure along time, frequency or spatial dimensions. For example, the far field channel was split into a group of subchannels for compressive subspace estimation [14].…”

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confidence: 99%

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Message Passing-Based Link Configuration in Short Range Millimeter Wave Systems

Myers

Kaleva

Tölli

et al. 2020

IEEE Trans. Commun.

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Millimeter wave (mmWave) communication in typical wearable and data center settings is short range. As the distance between the transmitter and the receiver in short range scenarios can be comparable to the length of the antenna arrays, the common far field approximation for the channel may not be applicable. As a result, dictionaries that result in a sparse channel representation in the far field setting may not be appropriate for short distances. In this paper, we develop a novel framework to exploit the structure in short range mmWave channels. The proposed method splits the channel into several subchannels for which the far field approximation can be applied. Then, the structure within and across different subchannels is leveraged using message passing. We show how information about the antenna array geometry can be used to design message passing factors that incorporate structure across successive subchannels. Simulation results indicate that our framework can be used to achieve better beam alignment with fewer channel measurements when compared to standard compressed sensingbased techniques that do not exploit structure across subchannels. Index TermsShort range communication, mm-Wave, hybrid beamforming, dynamic compressed sensing.

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Section: B Link Configuration In a Multi-user Settingmentioning

confidence: 99%

mentioning

confidence: 99%

Message Passing-Based Link Configuration in Short Range Millimeter Wave Systems

Myers

Kaleva

Tölli

et al. 2020

IEEE Trans. Commun.

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“…Paper [5], [27] considered the hidden joint common and individual sparsity in angle domain among the user channel matrices due to the shared local scatterers in the physical propagation environment. A nonorthogonal downlink pilot design was proposed in [8], [12], [14], [28] by exploiting the spatially common sparsity in angle domain and time correlation of massive MIMO channels. The channel sparsity in angle domain with partial support information was utilized in [29], [30] to acquire compressed CSI.…”

Section: A Related Workmentioning

confidence: 99%

Decoupling Channel Estimation for FDD Massive MIMO Systems Utilizing Joint Sparsity

et al. 2020

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Effective channel estimation for massive multiple-input-multiple-output (MIMO) systems based on frequency division duplex (FDD) protocol is a crucial problem. To reduce pilot overhead, we consider the joint sparsity of the multi-path channel in delay-angle domain. Based on the joint sparsity, we propose a decoupling pilot design scheme. In the proposed scheme, the pilot design is decoupled into two parts. In the first part, a global optimal selection greedy iterative algorithm (GOS-GIA) is proposed to obtain the near-optimal pilot subcarrier pattern. In the second part, a random Rademacher distribution pilot matrix is used as the angle-domain pilot matrix. Accordingly, a two-stage channel estimation strategy is also provided and analyzed. The first stage of the strategy is concerned with retrieving the positions of non-zero dominant taps in the delay domain. The second stage focuses on estimating the channel coefficients at these taps. Algorithm complexity analysis shows that the GOS-GIA can reduce the computational complexity at least one order of magnitude, and the proposed channel estimation strategy reduces the computational complexity by more than two orders of magnitude. Simulation results verify that the proposed pilot design scheme achieves better performance with lower pilot overhead. INDEX TERMS Angle domain, channel estimation, compressive sensing, delay domain, massive multiple-input-multiple-output, pilot design, sparsity.

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“…This sparsity can be formulated as only a limited number of transmit and receive direction pairs with nonzero gains [5]. Based on this observation, one would estimate only the angle of departures/arrivals (AoDs/AoAs) of dominant paths and the corresponding path gains, instead of estimating all the entries of the channel matrix directly [6].…”

Section: Introductionmentioning

confidence: 99%

Channel Estimation for Millimeter Wave Massive MIMO Systems Using Separable Compressive Sensing

et al. 2021

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Channel estimation is a fundamental problem for downlink transmission in millimeter wave (mmWave) multiple input multiple output (MIMO) systems. This paper proposes a channel estimation algorithm by exploiting the separable structured sparsity of mmWave massive MIMO channel. The mmWave downlink channel is firstly formulated as a two dimensional (2D) separable compressive sensing (CS) model according to the sparsity structure of the channel in angle of arrivals (AoAs) and angle of departures (AoDs) domains. Then a separable compressive sampling match pursuit (SCoSaMP) algorithm is proposed to solve the separable CS recovery problem for channel estimation. Based on the separable sparsity structure of the channel, we design the precoding and combining matrices under the metric of mutual information to further improve the performance of channel estimation. Simulations demonstrate the advantages of the proposed algorithm over the traditional CS-based channel estimation methods. INDEX TERMS channel estimation; separable compressive sensing; precoder design; millimeter wave; massive MIMO system

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Exploiting Dynamic Sparsity for Downlink FDD-Massive MIMO Channel Tracking

Cited by 49 publications

References 29 publications

Message Passing-Based Link Configuration in Short Range Millimeter Wave Systems

Message Passing-Based Link Configuration in Short Range Millimeter Wave Systems

Decoupling Channel Estimation for FDD Massive MIMO Systems Utilizing Joint Sparsity

Channel Estimation for Millimeter Wave Massive MIMO Systems Using Separable Compressive Sensing

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