NOMA for V2X under similar channel conditions

The research on connected vehicles is undergoing a paradigm shift from vehicle-to-vehicle(V2V) to vehicle-to-everything (V2X) communication. However, the existing proposals for V2X relymainly on conventional orthogonal multiple access (OMA), which utilises the available resources in anorthogonal manner. Consequently, V2X based on OMA may not be able to meet the V2X requirementsunder dense tra c environments. In this paper, we consider V2X based on non-orthogonal multipleaccess (NOMA), where several vehicles approach towards a road junction from di erent directions.Under this scenario, the vehicles at the cross road/junction have very similar channel conditions withthe roadside unit (RSU). This poses a challenge to apply NOMA under this scenario because theperformance of NOMA is highly dependent upon having significant channel gain di erence amongusers. In order to apply NOMA more e ectively under such situation, we propose two channelgain stretching (CGS) strategies inspired by digital image processing to obtain a significant di erenceamong channel gains of the vehicles. In order to evaluate the performance, we derive a closed-formexpression of the outage probability. Numerical results are also presented to validate the accuracyof the derived results and also to compare the performance of NOMA with and without both CGSschemes, and OMA