NOMA for V2X under similar channel conditions

Abstract

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 rely mainly on conventional orthogonal multiple access (OMA), which utilises the available resources in an orthogonal manner. Consequently, V2X based on OMA may not be able to meet the V2X requirements under dense traffic environments. In this paper, we consider V2X based on non-orthogonal multiple access (NOMA), where several vehicles approach towards a road junction from different directions. Under this scenario, the vehicles at the cross road/junction have very similar channel conditions with the roadside unit (RSU). This poses a challenge to apply NOMA under this scenario because the performance of NOMA is highly dependent upon having significant channel gain difference among users. In order to apply NOMA more effectively under such situation, we propose two channel gain stretching (CGS) strategies inspired by digital image processing to obtain a significant difference among channel gains of the vehicles. In order to evaluate the performance, we derive a closed-form expression of the outage probability. Numerical results are also presented to validate the accuracy of the derived results and also to compare the performance of NOMA with and without both CGS schemes, and OMA.