| Title | SINR and Reliability Based Hidden Terminal Estimation for Next Generation Vehicular Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | Bozkaya, Elif, Chowdhury, Kaushik, Canberk, Berk |
| Conference Name | Proceedings of the 12th ACM Symposium on QoS and Security for Wireless and Mobile Networks |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-4504-0 |
| Keywords | broadcast vehicular communication, hidden terminal problem, predictability, pubcrawl, reliability, Resiliency, Scalability, Security Heuristics, sinr estimation |
| Abstract | Safety applications are currently being developed in next generation vehicular networks to provide road safety. Broadcasting of safety messages unveils the need of reliability assessment since there are no request-to-send (RTS)/clear-to-send (CTS) handshaking and acknowledgment packets in broadcast vehicular communications. Therefore, the reliability of broadcast messages suffer from hidden terminal problem, interference and high mobility. To overcome these challenges, Signal-to-Interference-and-Noise Ratio (SINR) estimation is a key solution so that we can foresee the transmission collisions caused by hidden terminals and prevent its transmissions. Then, we can build a model to improve reliability of broadcast messages. Towards this aim, in this paper, we propose a SINR based hidden terminal estimation model. First, we introduce a method to specify hidden terminals and their transmissions, then we estimate accurate SINR level at the receiver in the near future. Second, we formulate the successfully received packets with a heuristic algorithm and, calculate throughput and hidden terminal radius. Our approach enables significant improvement in the reliability of broadcast vehicular communications. |
| URL | http://doi.acm.org/10.1145/2988272.2988283 |
| DOI | 10.1145/2988272.2988283 |
| Citation Key | bozkaya_sinr_2016 |
SINR and Reliability Based Hidden Terminal Estimation for Next Generation Vehicular Networks