Millimeter Wave V2V Communications: Distributed Association and Beam Alignment
Cristina Perfecto, Javier Del Ser, Mehdi Bennis

TL;DR
This paper introduces a novel framework combining Matching Theory and Swarm Intelligence to optimize vehicle pairing and beam alignment in millimeter-wave V2V communications, enhancing reliability and reducing latency.
Contribution
It presents a new resource allocation framework for mmWave V2V that jointly considers CSI and QSI, improving pairing efficiency and beam management in high-mobility scenarios.
Findings
Up to 25% improvement in reliability and delay in dense scenarios
50% more vehicle pairs compared to baseline methods
Demonstrates practical feasibility of mmWave for high-rate V2V communications
Abstract
Recently millimeter-wave bands have been postulated as a means to accommodate the foreseen extreme bandwidth demands in vehicular communications, which result from the dissemination of sensory data to nearby vehicles for enhanced environmental awareness and improved safety level. However, the literature is particularly scarce in regards to principled resource allocation schemes that deal with the challenging radio conditions posed by the high mobility of vehicular scenarios. In this work we propose a novel framework that blends together Matching Theory and Swarm Intelligence to dynamically and efficiently pair vehicles and optimize both transmission and reception beamwidths. This is done by jointly considering Channel State Information (CSI) and Queue State Information (QSI) when establishing vehicle-to-vehicle (V2V) links. To validate the proposed framework, simulation results are…
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