Efficient Receiver Design for Uplink Cell-Free Massive MIMO With Hardware Impairments

Zheng, Jiakang; Zhang, Jiayi; Zhang, Luming; Zhang, Xiaodan; Ai, Bo

doi:10.1109/tvt.2020.2975354

Cited by 81 publications

(38 citation statements)

References 14 publications

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“…These effects lead to signal distortion which in some cases can be modeled as a signal power loss plus an uncorrelated additive distortion term, using the Bussgang decomposition [39], [58]. The impact of such distortion on cell-free networks has been analyzed in [116], [211], [216] for general hardware impairments, while the special case of quantization distortion in each analog-to-digital converter (ADC) was considered in [78]. The obtained SE expressions can be utilized to get a better sense of the practically achievable SE and to optimize the transmit power based on these expressions.…”

Section: Low-cost Componentsmentioning

confidence: 99%

Foundations of User-Centric Cell-Free Massive MIMO

Demir

Björnson

Sanguinetti

2021

FNT in Signal Processing

379

279

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Imagine a coverage area where each mobile device is communicating with a preferred set of wireless access points (among many) that are selected based on its needs and cooperate to jointly serve it, instead of creating autonomous cells. This effectively leads to a user-centric post-cellular network architecture, which can resolve many of the interference issues and service-quality variations that appear in cellular networks. This concept is called User-centric Cellfree Massive MIMO (multiple-input multiple-output) and has its roots in the intersection between three technology components: Massive MIMO, coordinated multipoint processing, and ultra-dense networks. The main challenge is to achieve the benefits of cell-free operation in a practically feasible way, with computational complexity and fronthaul requirements that are scalable to enable massively large networks with many mobile devices. This monograph covers the foundations of User-centric Cell-free Massive MIMO, starting from the motivation and mathematical definition. It continues by describing the state-of-the-art signal processing algorithms for channel estimation, uplink data reception,

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Section: Low-cost Componentsmentioning

confidence: 99%

Foundations of User-Centric Cell-Free Massive MIMO

Demir

Björnson

Sanguinetti

2021

FNT in Signal Processing

379

279

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show abstract

“…The classical i.i.d. Rayleigh fading propagation model used in most previous research works on CF massive MIMO networks (see, for instance [4], [5], [8], [27]- [30]) will be replaced by a simplified version of the third generation partnership project (3GPP) Urban Microcell model described in [31]. This model takes into account the possibility of the channel to toggle between non-line-of-sight (NLOS) and LOS and the existence of spatial correlation at the AP arrays.…”

Section: A Channel Modelmentioning

confidence: 99%

Channel Hardening in Cell-Free and User-Centric Massive MIMO Networks With Spatially Correlated Ricean Fading

et al. 2020

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The irruption of the cell-free (CF) massive multiple-input multiple-output (MIMO) network topology has meant taking one step further the concept of massive MIMO as a means to provide uniform service in large coverage areas. A key property of massive MIMO networks is channel hardening, by which the channel becomes deterministic when the number of antennas grows large enough relative to the number of serviced users, easing the signal processing and boosting the performance of simple precoders. However, in CF massive MIMO, the fulfillment of this condition depends on several aspects that are not considered in classical massive MIMO systems. In this work, we address the presence of channel hardening in both CF massive MIMO and the recently appeared user-centric (UC) approach, under a spatially correlated Ricean fading channel using distributed and cooperative precoding and combining schemes and different power control strategies for both the downlink (DL) and uplink (UL) segments. We show that the lineof-sight (LOS) component, spatially correlated antennas and UC schemes have an impact on how the channel hardens. In addition, we examine the existent gap between the estimated achievable rate and the true network performance when channel hardening is compromised. Exact closed-form expressions for both the hardening metric and achievable DL/UL rates are given as well. INDEX TERMS Cell-Free, Massive MIMO, User-Centric, Correlated Ricean Fading, Channel Hardening.

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“…The original papers [37], [38] considered singleantenna APs, single-antenna UEs, Rayleigh fading channels, and infinite capacity error-free fronthaul connections. Later works have studied more realistic setups, such as singleantenna APs with Rician fading channels [41], [42], multiantenna APs with uncorrelated [43], [44] or correlated [45], [46] fading, multi-antenna UEs [47], [48], and hardware impairments [49], [50]. The impact of finite-resolution fronthaul connections (i.e., when both CSI and the received signal must be quantized) was considered in [44].…”

Section: B Basics Of Cell-free Massive Mimomentioning

confidence: 99%

Prospective Multiple Antenna Technologies for Beyond 5G

Zhang

Björnson

Matthaiou

et al. 2020

IEEE J. Select. Areas Commun.

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718

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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Efficient Receiver Design for Uplink Cell-Free Massive MIMO With Hardware Impairments

Cited by 81 publications

References 14 publications

Foundations of User-Centric Cell-Free Massive MIMO

Foundations of User-Centric Cell-Free Massive MIMO

Channel Hardening in Cell-Free and User-Centric Massive MIMO Networks With Spatially Correlated Ricean Fading

Prospective Multiple Antenna Technologies for Beyond 5G

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