Non-Saturated Throughput Analysis of Coexistence of Wi-Fi and Cellular With Listen-Before-Talk in Unlicensed Spectrum
July 25, 2017 Β· Declared Dead Β· π IEEE Transactions on Vehicular Technology
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yongjae Kim, Yujae Song, Yonghoon Choi, Youngnam Han
arXiv ID
1707.07843
Category
cs.NI: Networking & Internet
Citations
75
Venue
IEEE Transactions on Vehicular Technology
Last Checked
5 months ago
Abstract
This paper analyzes the coexistence performance of Wi-Fi and cellular networks conditioned on non-saturated traffic in the unlicensed spectrum. Under the condition, the time-domain behavior of a cellular small-cell base station (SCBS) with a listen-before-talk (LBT) procedure is modeled as a Markov chain, and it is combined with a Markov chain which describes the time-domain behavior of a Wi-Fi access point. Using the proposed model, this study finds the optimal contention window size of cellular SCBSs in which total throughput of both networks is maximized while satisfying the required throughput of each network, under the given traffic densities of both networks. This will serve as a guideline for cellular operators with respect to performing LBT at cellular SCBSs according to the changes of traffic volumes of both networks over time.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Networking & Internet
R.I.P.
π»
Ghosted
π
π
The Cartographer
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
π
π
The Cartographer
A Survey of Indoor Localization Systems and Technologies
R.I.P.
π»
Ghosted
Survey of Important Issues in UAV Communication Networks
π
π
The Cartographer
Network Function Virtualization: State-of-the-art and Research Challenges
π
π
The Cartographer
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted