2016/12/23 by Francisco J. Martín-Vega, Martin-Vega, Francisco J., Beatriz Soret +7
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Technologies #FOS: Computer and information sciences #Information Theory (cs.IT) #Mobile Ad Hoc Networks #Opportunistic and Delay-Tolerant Networks #Vehicular Ad Hoc Networks (VANETs)
paper · pdf · doi:10.48550/arxiv.1612.07999
openalex publication_date 2016/12/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Delivery of broadcast messages among vehicles for safety purposes, which is\nknown as one of the key ingredients of Intelligent Transportation Systems\n(ITS), requires an efficient Medium Access Control (MAC) that provides low\naverage delay and high reliability. To this end, a Geo-Location Based Access\n(GLOC) for vehicles has been proposed for Vehicle-to-Vehicle (V2V)\ncommunications, aiming at maximizing the distance of co-channel transmitters\nwhile preserving a low latency when accessing the resources. In this paper we\nanalyze, with the aid of stochastic geometry, the delivery of periodic and\nnon-periodic broadcast messages with GLOC, taking into account path loss and\nfading as well as the random locations of transmitting vehicles. Analytical\nresults include the average interference, average Binary Rate (BR), capture\nprobability, i.e., the probability of successful message transmission, and\nEnergy Efficiency (EE). Mathematical analysis reveals interesting insights\nabout the system performance, which are validated thought extensive Monte Carlo\nsimulations. In particular, it is shown that the capture probability is an\nincreasing function with exponential dependence with respect to the transmit\npower and it is demonstrated that an arbitrary high capture probability can be\nachieved, as long as the number of access resources is high enough. Finally, to\nfacilitate the system-level design of GLOC, the optimum transmit power is\nderived, which leads to a maximal EE subject to a given constraint in the\ncapture probability.\n