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Yan Zhang 0110

dblp:04/3348-110 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-2131-3626ORCID · verified

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 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
channel state information
0.612022
Reconfigurable Intelligent Surfaces With Outdated Channel State Information: Centralized vs. Distributed Deployments · IEEE Trans. Commun. 2022
Physical-layer communications › channel state information
outdated CSI
0.612022
Reconfigurable Intelligent Surfaces With Outdated Channel State Information: Centralized vs. Distributed Deployments · IEEE Trans. Commun. 2022
Physical-layer communications
reconfigurable intelligent surface
0.612022
Reconfigurable Intelligent Surfaces With Outdated Channel State Information: Centralized vs. Distributed Deployments · IEEE Trans. Commun. 2022
Physical-layer communications › information theory › capacity analysis
ergodic capacity
0.212022
Reconfigurable Intelligent Surfaces With Outdated Channel State Information: Centralized vs. Distributed Deployments · IEEE Trans. Commun. 2022
Physical-layer communications › radio propagation
near-field and far-field propagation
0.212022
Reconfigurable Intelligent Surfaces With Outdated Channel State Information: Centralized vs. Distributed Deployments · IEEE Trans. Commun. 2022

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

monte carlo simulation · 0.6
YearPublicationVenuePosition
2022 Reconfigurable Intelligent Surfaces With Outdated Channel State Information: Centralized vs. Distributed Deployments
abstract
In this paper, we investigate the performance of an RIS-aided wireless communication system subject to outdated channel state information that may operate in both the near- and far-field regions. In particular, we take two RIS deployment strategies into consideration: (i) the centralized deployment, where all the reflecting elements are installed on a single RIS and (ii) the distributed deployment, where the same number of reflecting elements are placed on multiple RISs. For both deployment strategies, we derive accurate closed-form approximations for the ergodic capacity, and we introduce tight upper and lower bounds for the ergodic capacity to obtain useful design insights. From this analysis, we unveil that an increase of the transmit power, the Rician-$K$factor, the accuracy of the channel state information and the number of reflecting elements help improve the system performance. Moreover, we prove that the centralized RIS-aided deployment may achieve a higher ergodic capacity as compared with the distributed RIS-aided deployment when the RIS is located near the base station or near the user. In different setups, on the other hand, we prove that the distributed deployment outperforms the centralized deployment. Finally, the analytical results are verified by using Monte Carlo simulations.
Yan Zhang 0110, Jiayi Zhang 0001, Marco Di Renzo, Huahua Xiao, Bo Ai 0001
IEEE Trans. Commun.1