6533b853fe1ef96bd12ac389

RESEARCH PRODUCT

Network-Assisted Resource Allocation with Quality and Conflict Constraints for V2V Communications

Arie KoppelaarLuis F. Abanto-leonSonia Heemstra De Groot

subject

Signal Processing (eess.SP)Linear programmingComputer scienceReliability (computer networking)media_common.quotation_subject050801 communication & media studies02 engineering and technology0508 media and communications0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringResource managementQuality (business)Electrical Engineering and Systems Science - Signal Processingmedia_commonbusiness.industryQuality of service05 social sciences020206 networking & telecommunicationsMaximizationKnapsack problemquality of serviceResource allocationbroadcast vehicular communicationssubchannel allocationbusinessComputer network

description

The 3rd Generation Partnership Project (3GPP) has recently established in Rel. 14 a network-assisted resource allocation scheme for vehicular broadcast communications. Such novel paradigm is known as vehicle--to--vehicle (V2V) \textit{mode-3} and consists in eNodeBs engaging only in the distribution of sidelink subchannels among vehicles in coverage. Thereupon, without further intervention of the former, vehicles will broadcast their respective signals directly to their counterparts. Because the allotment of subchannels takes place intermittently to reduce signaling, it must primarily be conflict-free in order not to jeopardize the reception of signals. We have identified four pivotal types of allocation requirements that must be guaranteed: one quality of service (QoS) requirement and three conflict conditions which must be precluded in order to preserve reception reliability. The underlying problem is formulated as a maximization of the system sum-capacity with four types of constraints that must be enforced. In addition, we propose a three-stage suboptimal approach that is cast as multiple independent knapsack problems (MIKPs). We compare the two approaches through simulations and show that the latter formulation can attain acceptable performance at lesser complexity.

https://dx.doi.org/10.48550/arxiv.1807.04829