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Mohammadmohsen Jadidi

dblp:385/9585 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0001-8246-2521ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › MIMO › massive MIMO
cell-free massive MIMO
0.812024
Performance Analysis and Power Allocation for Uplink Cell-Free Massive MIMO System With Nonlinear Power Amplifier · IEEE Trans. Commun. 2024
Physical-layer communications › hardware impairments
nonlinear power amplifier
0.812024
Performance Analysis and Power Allocation for Uplink Cell-Free Massive MIMO System With Nonlinear Power Amplifier · IEEE Trans. Commun. 2024
Physical-layer communications
power allocation
0.812024
Performance Analysis and Power Allocation for Uplink Cell-Free Massive MIMO System With Nonlinear Power Amplifier · IEEE Trans. Commun. 2024
Physical-layer communications › MIMO › precoder design
channel inversion
0.212024
Performance Analysis and Power Allocation for Uplink Cell-Free Massive MIMO System With Nonlinear Power Amplifier · IEEE Trans. Commun. 2024

Methods — techniques the papers use, named apart from their topics

successive convex approximation · 0.8single condensation method · 0.8geometric programming · 0.8
YearPublicationVenuePosition
2024 Performance Analysis and Power Allocation for Uplink Cell-Free Massive MIMO System With Nonlinear Power Amplifier
abstract
Cell-free Massive multiple-input multiple-output (CF-mMIMO) is one of the most promising technologies. It is crucial to examine the performance of CF-mMIMO systems in real-world scenarios, particularly the hardware impairments caused by nonlinear power amplifiers (PAs). This paper’s main objective is to thoroughly examine CF-mMIMO under PA non-linearity at user equipment (UE), focusing on power allocation performance. We provide closed-form expressions for uplink achievable data rates while accounting for the nonlinear behavior of the PA. We extensively examine power control strategies. Initially, we explore full power transmission and Channel Inversion. Then, we address the non-convex problem of maximizing both the sum rate (MSR) and the minimum rate (MMR) of users using the single condensation method (SCM) and successive convex approximation (SCA) algorithm. We propose iterative algorithms to optimize the ultimate geometric programming (GP) problem and find the optimal power control coefficients. Results confirm that the proposed nonlinearity-aware power control yields substantial enhancements in net throughput compared to conventional algorithms. This underscores the superiority of integrating the nonlinearity of PAs into the power allocation strategy. The proposed MSR algorithm not only enhances the sum throughput but also increases the minimum net throughput and Jain’s fairness index of net throughput.
Mohammadmohsen Jadidi, Amir Mohammad Khoueini, Abbas Mohammadi 0002, Vahid Meghdadi
IEEE Trans. Commun.1