Massive MIMO Forward Link Analysis for Cellular Networks

George, Geordie; Lozano, Angel; Haenggi, Martin

doi:10.1109/twc.2019.2907584

Cited by 33 publications

(15 citation statements)

References 39 publications

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“…This convergence, moreover, is very evident for practical strengths of the shadowing. In hexagonal lattice networks, for instance, PPP-based analyses are highly representative for shadowing standard deviations on the order of 10 dB [6]- [8], well in line with the typical values encountered in macrocellular deployments.…”

Section: Motivationsupporting

confidence: 66%

Distribution of the Number of Users per Base Station in Cellular Networks

George

Lozano

Haenggi

2019

IEEE Wireless Commun. Lett.

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We consider the number of users associating with each base station in a cellular network. Extending and unifying the characterizations for certain settings available in the literature, we derive a result that is asymptotic in the strength of the shadowing, yet otherwise universally valid: it holds for every network geometry and shadowing distribution. We then illustrate how this result provides excellent representations in various classes of networks and with realistic shadowing strengths, evidencing broad applicability.

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Section: Motivationsupporting

confidence: 66%

Distribution of the Number of Users per Base Station in Cellular Networks

George

Lozano

Haenggi

2019

IEEE Wireless Commun. Lett.

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“…Proposition 3. Considering the channel hardening scenario, without full-duplexing (and hence no co-channel interference between users) and with full-resolution ADC/DAC, we retrieve the results derived for downlink users in multicell massive MIMO systems in [6].…”

Section: B Matched Filter Precodermentioning

confidence: 99%

“…A massive number of antennas can provide enough degrees of freedom (DoF) not only to improve the spatial multiplexing gain but also substantially mitigate the SI. Thanks to these benefits, massive MIMO FD has been considered for cellular networks, millimeter wave applications such as IEEE 802.11ad and 802.11ay Wi-Fi standards, and 5G New Radio (NR) in 3GPP Release 15 [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

Full-Duplex Massive MIMO Cellular Networks with Low Resolution ADC/DAC

Balti¹,

Evans²

2021

Preprint

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In this paper, we provide an analytical framework for full-duplex (FD) massive multiple-input multiple-output (MIMO) cellular networks with low resolution analog-to-digital and digital-to-analog converters (ADCs and DACs). Matched filters are employed at the FD base stations (BSs) at the transmit and receive sides. For both reverse and forward links, we derive the expressions of the signal-to-quantization-plus-interference-and-noise ratio (SQINR) for general and special cases. We further evaluate the outage probability and spectral efficiency for reverse and forward links, and quantify the effects of the quantization error, loopback self-interference and inter-user interference for cells arranged in a hexagonal lattice and Poisson Point Process (PPP) tessellations. Finally, we derive analytical expressions for spectral efficiency for asymptotic cases as well as for power scaling laws.

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“…Under the premise of AP positions that are agnostic to the radio propagation, shadow fading renders the network approximately Poisson-like from the vantage of any user [53]- [55]. This approximation sharpens as the shadowing strengthens, being precise for values of interest [54]- [57]. Relying on this result, we draw the AP positions uniformly; these positions thus conform to a binomial point process, which, as the network grows, converges to a Poisson point process, avoiding the explicit modeling of shadowing as it is then already captured by the network geometry.…”

Section: A Large-scale Modelingmentioning

confidence: 99%

Subset MMSE Receivers for Cell-Free Networks

Attarifar

Abbasfar

Lozano

2020

IEEE Trans. Wireless Commun.

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This paper formulates linear MMSE receivers that are both network-and user-centric for the uplink of cell-free wireless networks with centralized processing. Precisely, every user's reception involves a distinct subset of access points (APs) while every AP participates in the reception of a distinct subset of users, hence the moniker subset MMSE receivers. These subsets, defined on the basis of the large-scale channel gains between users and APs, capture the most relevant signal and interference contributions while disregarding those whose processing is costineffective and whose associated channel estimations would incur unnecessary overheads. With that, subset reception approaches the performance of network-wide MMSE reception, offering a multiple-fold improvement over cellular and matched-filtering counterparts, while being scalable in terms of cost and channel estimation. Moreover, because the subsets overlap considerably, they can sometimes be advantageously combined and the computation of the corresponding receivers can share a hefty amount of processing.

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Massive MIMO Forward Link Analysis for Cellular Networks

Cited by 33 publications

References 39 publications

Distribution of the Number of Users per Base Station in Cellular Networks

Distribution of the Number of Users per Base Station in Cellular Networks

Full-Duplex Massive MIMO Cellular Networks with Low Resolution ADC/DAC

Subset MMSE Receivers for Cell-Free Networks

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