Research on cluster overlap and non-overlap region for 5G-IoV networks with NOMA

Abstract As a multi hop self-organizing network, wireless sensor network has the ability to cooperatively sense, collect and process information of sensed objects. The applications WCN in 5G-based Internet Vehicles (5G-IoV), using fusion intelligent processing technologies, can obtain more reliable accurate detection parameters, which been widely concerned. However, massive connectivity exchange 5G-IoV pose great challenges bandwidth efficiency. In order overcome these issues networks, performance enhanced scheme based on non-orthogonal multiple access (NOMA) is proposed. proposed scheme, different vehicle locations are respectively discussed, i.e., whether overlap region cluster head vehicles (CHVs). particular, conventional works, each receiving node only decodes desired signal avoid loss provided from poor channel quality limitation. On other hand, all CHVs decode-and-forward new superposition coded signals with power allocation factors, while that maximum ratio combining utilized at receivers further improve ergodic sum-rate (SR) probability conflict. closed-form expressions SR for our analyzed under independent Rayleigh fading channels. Numerical results corroborating theoretical analysis show transmission applied NOMA-IoV improves significantly compared existing especially high signal-to-noise region.