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Somayeh Aghashahi

dblp:342/4562 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0002-7391-4386ORCID · 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
Cellular and mobile networks · 80% Vehicular, aerial and satellite networks · 20%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cellular and mobile networks
beam management
0.712023
Stochastic Modeling of Beam Management in mmWave Vehicular Networks · IEEE Trans. Mob. Comput. 2023
Cellular and mobile networks › beam management
beam switching
0.712023
Stochastic Modeling of Beam Management in mmWave Vehicular Networks · IEEE Trans. Mob. Comput. 2023
Cellular and mobile networks › mobility management
handover
0.712023
Stochastic Modeling of Beam Management in mmWave Vehicular Networks · IEEE Trans. Mob. Comput. 2023
Cellular and mobile networks
millimeter-wave communication
0.712023
Stochastic Modeling of Beam Management in mmWave Vehicular Networks · IEEE Trans. Mob. Comput. 2023
Vehicular, aerial and satellite networks
vehicular networks
0.712023
Stochastic Modeling of Beam Management in mmWave Vehicular Networks · IEEE Trans. Mob. Comput. 2023
Performance modeling and evaluation
stochastic modeling
0.212023
Stochastic Modeling of Beam Management in mmWave Vehicular Networks · IEEE Trans. Mob. Comput. 2023

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

stochastic geometry · 1.3analytical modeling · 1.3
YearPublicationVenuePosition
2023 Stochastic Modeling of Beam Management in mmWave Vehicular Networks
abstract
Mobility management is a major challenge for millimeter-wave (mmWave) cellular networks. In particular, directional beamforming in mmWave devices renders high-speed mobility support very complex. This complexity, however, is not limited to system design but also the performance estimation and evaluation. Hence, some have turned their attention to stochastic modeling of mmWave vehicular communication to derive closed-form expressions that can characterize the coverage and rate behavior of the network. In this article, we model and analyze the beam management for mmWave vehicular networks. To the best of our knowledge, this is the first work that goes beyond coverage and rate analysis. Specifically, we focus on a multi-lane divided highway scenario in which base stations and vehicles are present on both sides of the highway. In addition to providing analytical expressions for the average number of beam switching and handover events, we provide design insights for the operators to fine-tune their network through more informed choice of system parameters, including the number of resources dedicated to channel feedback and beam alignment operations.
Somayeh Aghashahi, Samaneh Aghashahi, Zolfa Zeinalpour-Yazdi, AliAkbar Tadaion, Arash Asadi
IEEE Trans. Mob. Comput.1