Distributed Association and Relaying with Fairness in Millimeter Wave Networks
August 11, 2016 Β· Declared Dead Β· π IEEE Transactions on Wireless Communications
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yuzhe Xu, Hossein Shokri-Ghadikolaei, Carlo Fischione
arXiv ID
1608.03380
Category
cs.NI: Networking & Internet
Citations
39
Venue
IEEE Transactions on Wireless Communications
Last Checked
6 months ago
Abstract
Millimeter wave (mmWave) systems are emerging as an essential technology to enable extremely high data rate wireless communications. The main limiting factors of mmWave systems are blockage (high penetration loss) and deafness (misalignment between the beams of the transmitter and receiver). To alleviate these problems, it is imperative to incorporate efficient association and relaying between terminals and access points. Unfortunately, the existing association techniques are designed for the traditional interference-limited networks, and thus are highly suboptimal for mmWave communications due to narrow-beam operations and the resulting non-negligible interference-free behavior. This paper introduces a distributed approach that solves the joint association and relaying problem in mmWave networks considering the load balancing at access points. The problem is posed as a novel stochastic optimization problem, which is solved by distributed auction algorithms where the clients and relays act asynchronously to achieve optimal client-relay-access point association. It is shown that the algorithms provably converge to a solution that maximizes the aggregate logarithmic utility within a desired bound. Numerical results allow to quantify the performance enhancements introduced by the relays, and the substantial improvements of the network throughput and fairness among the clients by the proposed association method as compared to standard approaches. It is concluded that mmWave communications with proper association and relaying mechanisms can support extremely high data rates, connection reliability, and fairness among the clients.
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