A Novel Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Internet of Vehicles Networks

With the rapid development of the Internet of Vehicles (IoV), the cognitive radio-based IoV (CIoV) network is widely used to overcome the lack of spectrum resources. In this paper, a novel joint spectrum sensing and resource allocation (JSS-RA) scheme in the CIoV system is investigated. The JSS-RA process is divided into two phases. In the spectrum sensing phase, our scheme considers the dynamic vehicular environment to adjust the decision threshold individually for each vehicle. In the resource allocation (RA) phase, we first propose a general utility-efficiency function. The various parameters contained in this function enable its transformation into many mainstream objective functions. Subsequently, the RA issue is formulated as a joint orthogonal frequency division multiplexing (OFDM) symbol and power optimization, which is also known as a mixed integer nonlinear programming (MINLP). We solve the original optimization by decomposing it into two subproblems. The theorems prove that the global optimum solution can be obtained by combining the results of two decomposed subproblems. Besides, the convergence rate of the proposed algorithm is discussed. Finally, numerical simulations verify the excellent performance and robustness of our JSS-RA scheme.