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PTMAC: A Prediction-Based TDMA MAC Protocol for Reducing Packet Collisions in VANET | IEEE Journals & Magazine | IEEE Xplore

PTMAC: A Prediction-Based TDMA MAC Protocol for Reducing Packet Collisions in VANET


Abstract:

With the rapid development of wireless communications, vehicular ad hoc networks (VANETs) have recently attracted great attention. Although IEEE 802.11p has been approved...Show More

Abstract:

With the rapid development of wireless communications, vehicular ad hoc networks (VANETs) have recently attracted great attention. Although IEEE 802.11p has been approved as the standard medium access control (MAC) protocol for vehicle-to-vehicle communications, its contention-based nature and inability to handle hidden-terminal problems may incur high packet collision probability under high-traffic-density situations. To overcome the shortcoming of IEEE 802.11p, time-division multiple-access (TDMA)-based protocols are proposed. However, packet collisions can still occur due to contention or multiple vehicles using the same slot while approaching each other, i.e., encounter collisions, particularly in two-way traffic roads. Some proposed remedying the encounter collisions for two-way traffic by partitioning a frame into two sets: one for the traffic in each direction. However, these proposed protocols are harder to adapt to the uneven traffic loads on both directions and cannot solve the problem of four-way intersections. In this paper, we propose a new TDMA protocol called prediction-based TDMA MAC (PTMAC) based on a novel way of predicting encounter collisions and effectively reducing the number of collisions. To the best of our knowledge, PTMAC is the first protocol that is designed for both two-way traffic and four-way intersections. It has shown that, based on this predictability, the encounter collisions can be greatly reduced in both two-way traffic and four-way intersections, regardless of the traffic loads on different road segments.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 65, Issue: 11, November 2016)
Page(s): 9209 - 9223
Date of Publication: 19 January 2016

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