Subchannel Allocation for Vehicle-to-Vehicle Broadcast Communications in Mode-3

TL;DR

This paper proposes a comprehensive framework for conflict-free, QoS-aware subchannel allocation in V2V mode-3 communications, addressing the unique challenges of decentralized vehicle communication networks.

Contribution

It introduces a unified, holistic approach for subchannel assignment that ensures QoS and conflict prevention in V2V mode-3, including a surrogate relaxation method for optimization.

Findings

Framework effectively prevents subchannel conflicts.

Ensures differentiated QoS for vehicles.

Optimizes subchannel allocation with minimal time dispersion.

Abstract

Conversely to mainstream cellular networks where uplink / downlink data traffic is centrally managed by eNodeBs, in vehicle-to-vehicle (V2V) broadcast communications \textit{mode-3} eNodeBs engage solely in subchannel assignment but ultimately do not intervene in data traffic control. Accordingly, vehicles communicate directly with their counterparts utilizing the allotted subchannels. Due to its loosely controlled one-to-all nature, V2V \textit{mode-3} is advantageous for time-critical applications. Nevertheless, it is imperative that the assignment of subchannels is accomplished without conflicts while at the same time satisfying quality of service (QoS) requirements. To the best of our knowledge, there exists no unified framework for V2V \textit{mode-3} that contemplates both prevention of allocation conflicts and fulfillment of QoS. Thus, four types of conditions that are of forceful character for attaining QoS-aware conflict-free allocations have been identified: $(i)$ assure differentiated QoS per vehicle, $(ii)$ preclude intra-cluster subframe conflicts, $(iii)$ secure minimal time dispersion of allotted subchannels and $(iv)$ forestall one-hop inter-cluster subchannel conflicts. Such conditions have been systematized and merged in an holistic manner allowing non-complex manipulation to perform subchannel allocation optimization. In addition, we propose a surrogate relaxation of the problem that does not affect optimality provided that certain requisites are satisfied.