A Partial Reciprocity-Based Channel Prediction Framework for FDD Massive MIMO With High Mobility

Qin, Ziao; Yin, Haifan; Cao, Yandi; Li, Weidong; Gesbert, David

doi:10.1109/twc.2022.3178499

Cited by 11 publications

(11 citation statements)

References 56 publications

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“…where C L h and C Lv are the horizontal and vertical-domain codebooks with L h and L v dimensions, respectively. In (8), [33].…”

Section: A Analysis Of Average Beamforming Gainmentioning

confidence: 99%

“…In [6], Bayesian learning-based channel estimation that enables the estimation of the downlink channel at the base station (BS) was proposed for the FDD multiuser MIMO system. In addition, partial reciprocity-based CSI acquisition was recently studied [7], [8]. The authors of [7] concluded that the downlink channel can be reconstructed accurately with the aid of an uplink pilot.…”

Section: Introductionmentioning

confidence: 99%

“…The authors of [7] concluded that the downlink channel can be reconstructed accurately with the aid of an uplink pilot. Furthermore, the authors of [8] proposed a channel prediction framework by tracking timevarying partial CSI, such as angle, delay, and Doppler information.…”

Section: Introductionmentioning

confidence: 99%

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Limited Feedback Design Based on Kronecker Product Codebook for Massive MIMO Systems

Min

Kim

2023

IEEE Access

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To realize massive multiple-input multiple-output (MIMO) systems, the uniform planar array (UPA) structure has been adopted to deploy a large number of antennas in a limited area of a radio unit at a base station. Subsequently, the Kronecker product (KP) codebook, consisting of horizontal and verticaldomain codebooks, was introduced to enable efficient quantization and feedback for the channel state information (CSI) under the UPA structure. In this paper, we propose advanced limited feedback schemes based on the KP codebook for massive MIMO systems. First, we propose one feedback bit allocation scheme to maximize the beamforming gain. Eigenvalues of spatial correlation channels are used to determine the numbers of feedback bits for horizontal and vertical-domain CSI, and the numbers of feedback bits to maximize the beamforming gain are derived as a closed-form expression. Moreover, we propose a novel feedback and pilot transmission scheme to reduce both the feedback and pilot overhead. The proposed feedback and pilot transmission scheme utilizes the property that the small-scale fading information can be compressed only to the horizontal-domain CSI when the spatial correlation of the vertical-domain channel is high. Simulation results show that, with the use of the proposed feedback bit allocation, the beamforming gain increases by up to 65% compared with the fixed feedback bit allocation when the horizontal and vertical-domain spatial correlation coefficients are equal to 0.57, and the numbers of horizontal and verticaldomain antennas are 8 and 12, respectively. In addition, it is also shown that the proposed feedback and pilot transmission scheme improves the ergodic rate by up to 48% compared with conventional feedback schemes.

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“…where C L h and C Lv are the horizontal and vertical-domain codebooks with L h and L v dimensions, respectively. In (8), [33].…”

Section: A Analysis Of Average Beamforming Gainmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Limited Feedback Design Based on Kronecker Product Codebook for Massive MIMO Systems

Min

Kim

2023

IEEE Access

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“…Third, the compatibility with the existing codebooks is also vital and will facilitate the implementation. The mobility enhanced codebook proposed in [20] is a candidate, which provides an effective approach to obtain the CSI in high mobility scenarios by applying a joint-angle-delay-Doppler (JADD) channel prediction scheme. The core idea is to track the multipath Doppler frequency shifts with a few channel samples.…”

Section: A Enhanced Codebook For Mobile Scenariosmentioning

confidence: 99%

A Review of Codebooks for CSI Feedback in 5G New Radio and Beyond

Qin¹,

Yin²

2023

Preprint

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Codebooks have been indispensable for wireless communication standard since the first release of the Long-Term Evolution in 2009. They offer an efficient way to acquire the channel state information (CSI) for multiple antenna systems. Nowadays, a codebook is not limited to a set of pre-defined precoders, it refers to a CSI feedback framework, which is more and more sophisticated. In this paper, we review the codebooks in 5G New Radio (NR) standards. The codebook timeline and the evolution trend are shown. Each codebook is elaborated with its motivation, the corresponding feedback mechanism, and the format of the precoding matrix indicator. Some insights are given to help grasp the underlying reasons and intuitions of these codebooks. Finally, we point out some unresolved challenges of the codebooks for future evolution of the standards. In general, this paper provides a comprehensive review of the codebooks in 5G NR and aims to help researchers understand the CSI feedback schemes from a standard and industrial perspective.

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“…These performance gains depend on accurate and timely channel state information (CSI) at the transmitter. Since full channel reciprocity is not available in the frequency division duplex (FDD) system, the downlink CSI has to be estimated from pilots at the user equipment (UE) side and then fed back to the BS [5] [6]. Unfortunately, the dimension of the channel matrix scales with the number Y. Cao, H. Yin, Z. Qin, W. Li and W. Wu are with School of Electronic Information and Communications, Huazhong University of Science and Technology, 430074 Wuhan, China (e-mail: ydcao@hust.edu.cn, yin@hust.edu.cn, ziao qin@hust.edu.cn, weidongli@hust.edu.cn, wuwm@hust.edu.cn).…”

Section: Introductionmentioning

confidence: 99%

Manifold Learning-Based CSI Feedback in Massive MIMO Systems

Cao

Yin

et al. 2022

ICC 2022 - IEEE International Conference on Communications

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Massive multi-input multi-output (MIMO) in Frequency Division Duplex (FDD) mode suffers from heavy feedback overhead for Channel State Information (CSI). In this paper, a novel manifold learning-based CSI feedback framework (MLCF) is proposed to reduce the feedback and improve the spectral efficiency of FDD massive MIMO. Manifold learning (ML) is an effective method for dimensionality reduction. However, most ML algorithms focus only on data compression, and lack the corresponding recovery methods. Moreover, the computational complexity is high when dealing with incremental data. To solve these problems, we propose a landmark selection algorithm to characterize the topological skeleton of the manifold where the CSI sample resides. Based on the learned skeleton, the local patch of the incremental CSI on the manifold can be easily determined by its nearest landmarks. This motivates us to propose a lowcomplexity compression and reconstruction scheme by keeping the local geometric relationships with landmarks unchanged. We theoretically prove the convergence of the proposed algorithm. Meanwhile, the upper bound on the error of approximating the CSI samples using landmarks is derived. Simulation results under an industrial channel model of 3GPP demonstrate that the proposed MLCF method outperforms existing algorithms based on compressed sensing and deep learning.

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A Partial Reciprocity-Based Channel Prediction Framework for FDD Massive MIMO With High Mobility

Cited by 11 publications

References 56 publications

Limited Feedback Design Based on Kronecker Product Codebook for Massive MIMO Systems

Limited Feedback Design Based on Kronecker Product Codebook for Massive MIMO Systems

A Review of Codebooks for CSI Feedback in 5G New Radio and Beyond

Manifold Learning-Based CSI Feedback in Massive MIMO Systems

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