UAV-Enabled Hardware-Impaired Spatially Correlated Cell-Free Massive MIMO Systems: Analysis and Energy Efficiency Optimization

Tentu, Venkatesh; Sharma, Ekant; Amudala, Dheeraj Naidu; Budhiraja, Rohit

doi:10.1109/tcomm.2022.3144470

Cited by 25 publications

(17 citation statements)

References 39 publications

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“…The longterm channel statistics i.e., hmk , β mk and R mk , remain constant over a resource block and, similar to [4], are assumed to be perfectly known at the AP. Most of the Rician CF works e.g., [19], [31], [32], assume that the LoS phase-shift φ λ mk is static. A slight change in UEs position, however, can radically modify the phase.…”

Section: A Channel Modelmentioning

confidence: 99%

“…Tentu et. al in [19] investigated the SE of an unmanned aerial vehicle enabled CF mMIMO system with RF impairments and spatially-correlated Rician channels. All these works considered only local SLD schemes, and also ignored channel aging in their analysis.…”

Section: Introductionmentioning

confidence: 99%

“…These works ignored RF impairments and channel aging. Also, the existing works [19], [23], [26] modeled the Rician fading channel with a static line-of-sight phase. A small change in the UE location induces significant phase-shift in the LoS path.…”

Section: Introductionmentioning

confidence: 99%

“…are also independent of the time instant n. Further, the term c (∈) kin,mm in the second summation of(19), contains ρ 2 i [n − λ]. As a result, the interference term IUI ki,n can be expressed as e 1 ρ 2 i…”

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confidence: 99%

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UAV-Enabled Hardware-Impaired Cell-free Massive MIMO With Spatially-Correlated Rician Fading

Tentu

Amudala

Sharma

et al. 2021

ICC 2021 - IEEE International Conference on Communications

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We study the impact of channel aging on the uplink of a cell-free (CF) massive multiple-input multiple-output (mMIMO) system by considering i) spatially-correlated Rician-faded channels; ii) hardware impairments at the access points and user equipments (UEs); and iii) two-layer large-scale fading decoding (LSFD). We first derive a closed-form spectral efficiency (SE) expression for this system, and later propose two novel optimization techniques to optimize the non-convex SE metric by exploiting the minorization-maximization (MM) method. The first one requires a numerical optimization solver, and has a high computation complexity. The second one with closed-form transmit power updates, has a trivial computation complexity. We numerically show that i) the two-layer LSFD scheme effectively mitigates the interference due to channel aging for both low-and high-velocity UEs; and ii) increasing the number of AP antennas does not mitigate the SE deterioration due to channel aging. We numerically characterize the optimal pilot length required to maximize the SE for various UE speeds. We also numerically show that the proposed closed-form MM optimization yields the same SE as that of the first technique, which requires numerical solver, and that too with a much reduced time-complexity.

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Section: A Channel Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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UAV-Enabled Hardware-Impaired Cell-free Massive MIMO With Spatially-Correlated Rician Fading

Tentu

Amudala

Sharma

et al. 2021

ICC 2021 - IEEE International Conference on Communications

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“…For instance, a novel non-orthogonal multiple-access (NOMA) aided cell-free massive MIMO system was investigated in [8]- [10] to meet the conflicting demands of high SE/EE/reliability and massive connectivity with low latency. Furthermore, as it can provide an outstanding capability of agilely moving in three-dimensional space, in [11] and [12] an unmanned aerial vehicle (UAV) enabled cell-free massive MIMO systems were considered for a wide-range of applications, which is able to remarkably relieve spatial limitations. Unlike traditional secrecy through cryptographic encryption, the authors in [13] and [14] use the trajectory design to tackle the physical layer security from an information-theoretic standpoint.…”

Section: Introductionmentioning

confidence: 99%

Downlink Analysis for the D2D Underlaid Multigroup Multicast Cell-Free Massive MIMO With Low-Resolution ADCs/DACs

Wan

Zhou

et al. 2022

IEEE Access

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To fully utilize the scarce spectrum resources, the downlink device-to-device (D2D) underlaid multigroup multicast cell-free massive multi-input multi-output (MIMO) systems is proposed, where the geographically distributed access points (APs) serving both multi-antenna cell-free users (CFUEs) and D2D users (DUEs) pair over the same time/frequency resource blocks. Specially, the low-resolution analog-todigital converters/digital-to-analog converters (ADCs/DACs) are adopted at the AP to effectively reduce hardware damage and energy costs. The imperfect channel state information (CSI) is obtained firstly by the standard minimum mean square error (MMSE), then the lower bounds of the closed-form achievable downlink rates for both CFUEs and DUEs are derived. Aside from that, the sum energy efficiency (EE) is also explored using the established power consumption model. Finally, numerical simulations are assessed to verify the analytical results and provide insights into the effects of the key system parameters. It demonstrates that increasing the number of APs can improve the sum SE, however, the sum EE decreases with the number of the APs sharply. Furthermore, increasing the density of DUEs can significantly improve the system capacity. The findings highlight the significance of the collaborative deployment of D2D and multigroup multicast cell-free massive MIMO technology, which can serve as a valuable reference and guide for the actual deployment of future communication systems.INDEX TERMS Cell-free massive MIMO, D2D, energy efficiency, low-resolution ADCs/DACs, multigroup multicast, spectral efficiency.

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Mathematical Analysis and Performance Evaluation of the Cell-Free mMIMO Networks Based on Cognitive Relays

Shalaby

Shahein

Shokair

2022

Wireless Pers Commun

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The Cell-Free mMIMO networks can provide a satisfied performance for 5G networks and beyond even there are shadowed users or indoor ones. The performance of cell-Free mMIMO networks was mathematically analyzed and simulated. This work aims to apply the cognitive relays in cell-Free mMIMO networks. The cell-Free mMIMO system, based on cognitive relays, is mathematically analyzed and simulated. The proposed work depends on two axes. Firstly, the relays can improve the performance of cell-Free mMIMO networks especially at shadowed users and cell-edge ones. Secondly, the cognitive radio can mitigate the interference in a cell-Free mMIMO network. The Cell-Free mMIMO network, based on cognitive relays, is proposed. The system is mathematically analyzed and simulated. The spectral efficiency SE and signal to interference plus noise ratio SINR is deduced and given in a closed form formula. It can be concluded that the cognitive relays can improve; SINR, SE, and Energy Efficiency EE of a cell-Free mMIMO network.

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UAV-Enabled Hardware-Impaired Spatially Correlated Cell-Free Massive MIMO Systems: Analysis and Energy Efficiency Optimization

Cited by 25 publications

References 39 publications

UAV-Enabled Hardware-Impaired Cell-free Massive MIMO With Spatially-Correlated Rician Fading

UAV-Enabled Hardware-Impaired Cell-free Massive MIMO With Spatially-Correlated Rician Fading

Downlink Analysis for the D2D Underlaid Multigroup Multicast Cell-Free Massive MIMO With Low-Resolution ADCs/DACs

Mathematical Analysis and Performance Evaluation of the Cell-Free mMIMO Networks Based on Cognitive Relays

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