Estimation of collision probability in a saturated vehicular Ad-Hoc networks

It is envisioned that WAVE standard, the technology for future DSRC communication in vehicular environments will support vehicular communication networks in order to provide safety and infotainment services as part of ITS. However, the defined parameter set for the EDCA used in 802.11p is capable of prioritizing messages, and when number of vehicles sending AC3 increases, packet collision probability will undeniably increase significantly. Since transmission collisions can only be detected after a transmission if at all, high percentage of packet collision probability will lead to many dead channel access times with no useful data exchange. We proposed CODER scheme which uses network coding to increase packet content and mitigate the problem of high collision probability which is inherent in WAVE standard by minimizing contention. Results of the theoretical analysis and simulation experiments show that CODER scheme has a performance gain over WAVE in terms of reduced collision rate.

[1]  Andreas Terzis,et al.  Wireless ACK Collisions Not Considered Harmful , 2008, HotNets.

[2]  Yunhao Liu,et al.  Exploiting Constructive Interference for Scalable Flooding in Wireless Networks , 2013, IEEE/ACM Transactions on Networking.

[3]  Jens B. Schmitt,et al.  On the Reception of Concurrent Transmissions in Wireless Sensor Networks , 2014, IEEE Transactions on Wireless Communications.

[4]  Rudolf Ahlswede,et al.  Network information flow , 2000, IEEE Trans. Inf. Theory.

[5]  James A. Roberts.  Packet error rates for DPSK and differentially encoded coherent BPSK , 1994, IEEE Trans. Commun..

[6]  Ashok K. Agrawala,et al.  Sniffing out the correct physical layer capture model in 802.11b , 2004, Proceedings of the 12th IEEE International Conference on Network Protocols, 2004. ICNP 2004..

[7]  Yanghee Choi,et al.  An experimental study on the capture effect in 802.11a networks , 2007, WinTECH '07.

[8]  Jon W. Mark,et al.  Wireless Communications and Networking , 2002 .

[9]  Chiara Buratti,et al.  Capture effect in IEEE 802.15.4 networks: Modelling and experimentation , 2010, IEEE 5th International Symposium on Wireless Pervasive Computing 2010.

[10]  Fulvio Babich,et al.  Capture analysis of mobile multi-packet networks adopting spatial reuse: An alternative study , 2014, 2014 IEEE Global Communications Conference.

[11]  Elmar Gerhards-Padilla,et al.  BonnMotion: a mobility scenario generation and analysis tool , 2010, SimuTools.

[12]  Lian Zhao,et al.  Performance Analysis of Broadcast Messages in VANETs Safety Applications , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[13]  D. Davis,et al.  Performance of Slotted ALOHA Random Access with Delay Capture and Randomized Time of Arrival , 1980, IEEE Trans. Commun..

[14]  Hari Balakrishnan,et al.  Harnessing Exposed Terminals in Wireless Networks , 2008, NSDI.

[15]  Kamin Whitehouse,et al.  Flash Flooding: Exploiting the Capture Effect for Rapid Flooding in Wireless Sensor Networks , 2009, IEEE INFOCOM 2009.

[16]  Mun Choon Chan,et al.  Splash : Fast Data Dissemination with Constructive Interference in Wireless Sensor Networks , 2013 .

[17]  Lothar Thiele,et al.  Efficient network flooding and time synchronization with Glossy , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[18]  Yunhao Liu,et al.  Disco: Improving Packet Delivery via Deliberate Synchronized Constructive Interference , 2015, IEEE Transactions on Parallel and Distributed Systems.

[19]  Bhaskar Krishnamachari,et al.  Experimental study of concurrent transmission in wireless sensor networks , 2006, SenSys '06.

[20]  John G. Proakis,et al.  Digital Communications , 1983 .

[21]  Sijing Zhang,et al.  Vehicular ad hoc networks (VANETs): Current state, challenges, potentials and way forward , 2014, 2014 20th International Conference on Automation and Computing.

[22]  Shaojie Tang,et al.  Fast and fine-grained counting and identification via constructive interference in WSNs , 2014, IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks.

[23]  Guoliang Xing,et al.  C-MAC: Model-Driven Concurrent Medium Access Control for Wireless Sensor Networks , 2009, IEEE INFOCOM 2009.

[24]  Srihari Nelakuditi,et al.  On Spatial Reuse and Capture in Ad Hoc Networks , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[25]  Li Li,et al.  Cross-Layer Design and Performance Analysis of Tactical Radio Networks , 2015, IEEE Transactions on Vehicular Technology.

[26]  Rahim Tafazolli,et al.  Analytical Study of the IEEE 802.11p MAC Sublayer in Vehicular Networks , 2012, IEEE Transactions on Intelligent Transportation Systems.

[27]  Srinivasan Seshan,et al.  Understanding and mitigating the impact of RF interference on 802.11 networks , 2007, SIGCOMM 2007.

[28]  Samir Ranjan Das,et al.  A measurement study of interference modeling and scheduling in low-power wireless networks , 2008, SenSys '08.

[29]  Andreas Terzis,et al.  Design and evaluation of a versatile and efficient receiver-initiated link layer for low-power wireless , 2010, SenSys '10.

[30]  Mustafa Ergen,et al.  Multichannel Medium Access Control for Dedicated Short-Range Communications , 2006, IEEE Transactions on Vehicular Technology.

[31]  Defeng Huang,et al.  Multiuser diversity with capture for wireless networks: protocol and performance analysis , 2008, IEEE Journal on Selected Areas in Communications.

[32]  e EDCA,et al.  Contention Window Analysis and Proposed Algorithm for Collision Minimization of IEEE 802 . 11 , .