Name
Title | ||
|---|---|---|
Throughput oriented lightweight near-optimal rendezvous algorithm for cognitive radio networks. |
Abstract | ||
|---|---|---|
In cognitive radio networks, secondary users have to dynamically search and access spectrum unused by primary users. Due to this dynamic spectrum access nature, the rendezvous between secondary users is a great challenge for cognitive radio networks. In this paper, we propose a Throughput oriEnted lightweight Near-Optimal Rendezvous (TENOR) algorithm that does not need a common control channel. TENOR has very lightweight overhead and accomplishes near-optimal performance with regard to both throughput and rendezvous time. With TENOR, secondary users are grouped into node pairs that are spread onto different channels in a decentralized manner. The co-channel interference is minimized and the throughput is near optimal. We develop a mathematical model to analyze the performance of TENOR. Both analytical and simulation results indicate that TENOR achieves near-optimal throughput and rendezvous time, and significantly outperforms the state-of-the-art rendezvous algorithms in the literature. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.comnet.2018.03.009 | Computer Networks |
Keywords | Field | DocType |
Cognitive radio network,Rendezvous,Lightweight rendezvous,Near-optimal rendezvous | Control channel,Computer science,Algorithm,Computer network,Communication channel,Rendezvous,Interference (wave propagation),Throughput,Cognitive radio,Distributed computing | Journal |
Volume | ISSN | Citations |
137 | 1389-1286 | 1 |
PageRank | References | Authors |
0.35 | 20 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunsheng Xin | 1 | 12 | 5.61 |
| Sharif Ullah | 2 | 1 | 0.35 |
| Min Song | 3 | 374 | 45.55 |
| Zhao Wu | 4 | 6 | 1.79 |
| Qiong Gu | 5 | 1 | 0.69 |
| Huanqing Cui | 6 | 3 | 1.05 |