Graph-based resource allocation with conflict avoidance for V2V broadcast communications

Abstract

In this paper we present a graph-based resource allocation scheme for sidelink broadcast vehicleto-vehicle (V2V) communications. Harnessing available information on the geographical position of vehicles and spectrum resources utilization, eNodeBs are capable of allotting the same set of sidelink resources to several different vehicles in order for them to broadcast their signals. Hence, vehicles sharing the same resources would ideally be in different communications clusters for the interference level-generated due to resource repurposing-to be maintained under control. Within a communications cluster, it is crucial that vehicles transmit in orthogonal time resources to prevent conflicts as vehicleswith half-duplex radio interfaces-cannot transmit and receive simultaneously. In this research, we have envisaged a solution based on a bipartite graph, where vehicles and spectrum resources are represented by vertices whereas the edges represent the achievable rate in each resource based on the signal-to-interference-plus-noise ratio (SINR) that vehicles perceive. The aforementioned constraint on time orthogonality of allocated resources can be approached by aggregating conflicting vertices into macro-vertices which, in addition, narrows the search space yielding a solution with computational complexity equivalent to the conventional graph matching problem. We show mathematically and through simulations that the proposed approach yields an optimal solution. In addition, we provide simulations arXiv:1805.06550v1 [eess.SP]

Impact of Quantized Side Information on Subchannel Scheduling for Cellular V2X

“…We can observe that as the number of vehicles increases, an efficient distribution of subchannels becomes more challenging. This is particularly true for the 4 The smaller the value is, the fairer the scheme behaves. Thus, a small value depicts quality homogeneity among the alloted subchannels.…”

“…It was mentioned that time-orthogonality of subchannels is an important requirement within each communication cluster as it prevents conflicts due to half-duplex PHY. Enforcing orthogonality of subchannels in time domain is equivalent to aggregating vertices into macro-vertices [4]. Thus, (1) can be reduced as follows.…”

“…It has been proved that the time orthogonality constraint mentioned earlier can be enforced by aggregating conflicting vertices into macro-vertices [4]. The approach discussed herein requires side information such as signal-to-interference-plus-noise ratio (SINR) measurements sensed by vehicles across the subchannels.…”

Subchannel allocation for vehicle-to-vehicle broadcast communications in mode-3

“…In mode-3, eNodeBs participate limitedly only assigning subchannels to vehicles in coverage. The assignment of subchannels is accomplished taking into consideration that (i) vehicles are dispersed over several communications clusters and that (ii) some subchannels can be reused provided that the interference generated due to repurposing is controlled [2] [5]. Subsequently, the allocation of subchannels is notified via downlink to all vehicles in coverage, which will engage in direct communications with their counterparts.…”

Enhanced C-V2X Mode-4 Subchannel Selection

“…For instance, [3] considers a single sub-band setting where a sequential heuristic approach is proposed in order to maximize the reuse distance among vehicles broadcasting in the same subchannel, and thus leading to co-channel interference (CCI) reduction. On the other hand, [4] describes a multiple sub-band setting where maximization of the system sum-capacity is sought based on the subchannels signal-to-interference-plus-noise ratio (SINR) that vehicles report to eNodeBs. Furthermore, [5] extends the previous work including additional constraints where differentiated QoS requirements per vehicle are considered.…”