Linear Receivers in Non-Stationary Massive MIMO Channels With Visibility Regions

Ali, Anum; Carvalho, Elisabeth de; Heath, Robert W.

doi:10.1109/lwc.2019.2898572

Cited by 71 publications

(112 citation statements)

References 10 publications

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“…For example, it is shown in [63] that the uplink minimum data rate does not scale with L when using MR processing. Scaling laws should also be investigated for realworld channels, such as with mixed line-of-sight (LoS) and non-LoS propagation, and other non-stationary channels [79], [80]. For LoS channels, approaches used in [81], [82] for cellular networks can be adapted for cell-free networks [83].…”

Section: E Open Research Problemsmentioning

confidence: 99%

Prospective Multiple Antenna Technologies for Beyond 5G

Zhang

Björnson

Matthaiou

et al. 2020

IEEE J. Select. Areas Commun.

716

370

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Multiple antenna technologies have attracted much research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are adopted. Since multiple antenna technology has become a key component of the fifth-generation (5G) networks, it is time for the research community to look for new multiple antenna technologies to meet the immensely higher data rate, reliability, and traffic demands in the beyond 5G era. Radically new approaches are required to achieve orders-of-magnitude improvements in these metrics. There will be large technical challenges, many of which are yet to be identified. In this paper, we survey three new multiple antenna technologies that can play key roles in beyond 5G networks: cellfree massive MIMO, beamspace massive MIMO, and intelligent reflecting surfaces. For each of these technologies, we present the fundamental motivation, key characteristics, recent technical progresses, and provide our perspectives for future research directions. The paper is not meant to be a survey/tutorial of a mature subject, but rather serve as a catalyst to encourage more research and experiments in these multiple antenna technologies. Index Terms-Beyond 5G, cell-free massive MIMO, beamspace, intelligent reflecting surface. I. INTRODUCTION T HE demand for higher data rates and traffic volumes seems to be never-ending, thus the quest for delivering The work of J.

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Section: E Open Research Problemsmentioning

confidence: 99%

Prospective Multiple Antenna Technologies for Beyond 5G

Zhang

Björnson

Matthaiou

et al. 2020

IEEE J. Select. Areas Commun.

716

370

View full text Add to dashboard Cite

show abstract

“…The work of [15] presented an ergodic capacity analysis of extra-large scale massive MIMO by introducing a tractable non-stationary channel model which divides the scattering clusters into two categories, i.e., wholly visible clusters and partially visible clusters, and regards these clusters as an array with virtual antennas. A simple non-stationary channel model, which has connections with the stationary massive MIMO channel model, was proposed in [16]. The downlink analysis of extra-large scale massive MIMO systems with linear precoders was also provided by deriving an approximate deterministic equivalent of the instantaneous signal-to-interference-plus-noise ratio (SINR).…”

Section: Introductionmentioning

confidence: 99%

“…The downlink analysis of extra-large scale massive MIMO systems with linear precoders was also provided by deriving an approximate deterministic equivalent of the instantaneous signal-to-interference-plus-noise ratio (SINR). The numerical results in [16] indicated that the VR significantly impacts the performance of linear precoders. Despite that, there is less of work that investigates the uplink performance of extra-large scale massive MIMO systems when taking the spatial nonstationarities into account.…”

Section: Introductionmentioning

confidence: 99%

On the Uplink Transmission of Extra-Large Scale Massive MIMO Systems

Yang

Cao

Matthaiou

et al. 2020

IEEE Trans. Veh. Technol.

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With the inherent benefits, such as, better cell coverage and higher area throughput, extra-large scale massive multiple-input multiple-output (MIMO) has great potential to be one of the key technologies for the next generation wireless communication systems. However, in practice, when the antenna dimensions grow large, spatial non-stationarities occur and users will only see a portion of the base station antenna array, which we call visibility region (VR). To assess the impact of spatial non-stationarities, in this paper, we investigate the uplink transmission of extra-large scale massive MIMO systems by considering VRs. In particular, we first propose a subarraybased system architecture for extra-large scale massive MIMO systems. Then, tight closed-form uplink spectral efficiency (SE) approximations with linear receivers are derived. With the objective of maximizing the achievable SE, we also propose schemes for the subarray phase coefficient design. In addition, based on the obtained ergodic achievable SE approximations, two statistical channel state information (CSI)-based greedy user scheduling algorithms are developed. Our results indicate that the statistical CSI-based greedy joint user and subarray scheduling algorithm collaborating with the on-off switch-based subarray architecture is a promising practical solution for extra-large scale massive MIMO systems.

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“…Very recent researches on the nonstationarities channel modeling include 12‐16 . In Reference 13 a channel model was proposed for vehicle‐to‐vehicle communication environments, in which the spherical wave‐front is assumed.…”

Section: Introductionmentioning

confidence: 99%

“…In References 12,14, the spherical wave‐front and the spatial nonstationarity property were evaluated, considering the nonstationarity properties on the array for M‐MIMO channel modeling. For XL‐MIMO systems, in Reference 15, linear receivers are evaluated, where the nonstationarities are included in the correlation matrix from each user. In Reference 16, the near‐field propagation considering the spherical wave‐front was considered, including the spatial nonstationarity properties for XL‐MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

Stochastic channel models for massive and extreme large multiple‐input multiple‐output systems

Taniguchi

Abrão

2020

Trans Emerging Tel Tech

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In this article, stochastic channel models for massive multiple‐input multiple‐output (M‐MIMO) and extreme large MIMO (XL‐MIMO) system applications are described, evaluated, and systematically compared. This work aims to cover new aspects of M‐MIMO stochastic channel models in a comprehensive and systematic way. For that, we compare different models, presenting graphically and intuitively the behavior of each model. Each M‐MIMO channel model emulates the environment using different methodologies and properties. Using metrics such as capacity, SINR, singular values decomposition, and condition number, one can understand the influence of each characteristic on the modeling and how it differentiates from other models. Moreover, in new XL‐MIMO scenarios, where the near‐field and visibility region effects arise, our finding demonstrate that for the two assumed schemes of clusters distribution, the clusters location influences the performance of the conjugate beamforming and zero‐forcing precoding due to the correlation effect, which have been analyzed from the geometric M‐MIMO channel models.

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Linear Receivers in Non-Stationary Massive MIMO Channels With Visibility Regions

Cited by 71 publications

References 10 publications

Prospective Multiple Antenna Technologies for Beyond 5G

Prospective Multiple Antenna Technologies for Beyond 5G

On the Uplink Transmission of Extra-Large Scale Massive MIMO Systems

Stochastic channel models for massive and extreme large multiple‐input multiple‐output systems

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