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Nuerxiati Nuermaimaiti

dblp:246/2368 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

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

Computer networks · 1

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 · 81% Wireless networking · 19%

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

TopicWeightPapersLastEvidence papers
Cellular and mobile networks › device-to-device communication
d2d caching
0.412020
Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy · IEEE Trans. Commun. 2020
Cellular and mobile networks
device-to-device communication
0.412020
Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy · IEEE Trans. Commun. 2020
Cellular and mobile networks › mobile networks › mobile network architecture › cellular network architecture
cache-enabled networks
0.112020
Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy · IEEE Trans. Commun. 2020
Cellular and mobile networks
heterogeneous networks
0.112020
Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy · IEEE Trans. Commun. 2020
Wireless networking › stochastic geometry
poisson cluster process
0.112020
Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy · IEEE Trans. Commun. 2020
Wireless networking
stochastic geometry
0.112020
Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy · IEEE Trans. Commun. 2020

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

poisson cluster process · 0.4laplace transform · 0.4
YearPublicationVenuePosition
2020 Deployment Model and Performance Analysis of Clustered D2D Caching Networks Under Cluster-Centric Caching Strategy
abstract
Device-to-Device (D2D) communication has become a promising candidate in future cellular networks to improve spectrum efficiency and energy efficiency, while reducing the latency. As the capacity of D2D user equipments (DUEs) increases, it makes DUEs caching possible, and it can offload traffic from macro base stations, perform computation-intensive and latency-critical tasks. In this paper, in-band communication is considered, and the Poisson cluster process is utilized to model and analyze the clustered D2D networks under cluster-centric caching strategy. Firstly, we use the Thomas cluster process to model cellular user equipments (CUEs) and DUEs, and give a deployment scheme of clustered D2D caching networks. Secondly, the aggregated interference of the typical D2D receiver is analyzed in the clustered D2D networks. Then the Laplace transform of the aggregated interference is analyzed, and the expressions of coverage probability, average achievable rate and cache hit probability of the typical D2D receiver are deduced. The simulation results show that we can adjust the path loss exponent, densities of DUEs and CUEs, transmitting power of CUEs, mean of simultaneously active transmitters in each cluster and Zipf exponent to improve the performance of clustered D2D caching networks.
Zhonggui Ma, Nuerxiati Nuermaimaiti, Haijun Zhang 0001, Huan Zhou 0002, Arumugam Nallanathan
IEEE Trans. Commun.2