Hybrid secure beamforming and vehicle selection using hierarchical agglomerative clustering for C-RAN-based vehicle-to-infrastructure communications in vehicular cyber-physical systems

The architecture of C-RAN-based soft-defined vehicular networks can support increasing demands of various applications in the future vehicular cyber-physical systems, but lacks strong and practical security–enhancing mechanisms in the physical layer. In this article, we propose a hybrid beamforming and vehicle-selection framework for vehicle-to-infrastructure communications to broadcast high-speed confidential messages. A one-dimensional roadway scenario having multiple lanes is considered, and the concept of secure region and interference-selection region is, respectively, developed for each roadside unit. We formulate an optimization problem of maximizing secrecy sumrate with the constraint of orthogonality-based vehicle selection. The original problem is then divided into two subproblems subtly. In terms of the first subproblem, we, by exploiting the orthogonality assumption, obtain a corresponding secure beamformer for each vehicle located in the secure region to reduce the interference and confidential information leakage. Based on secure beamformers, the second subproblem is changed to be a vehicle-selection problem, which is then solved by adopting hierarchical agglomerative clustering method and implemented by two proposed novel algorithms blending vehicle selection with beamformer generation. Simulation results verify the effectiveness of the proposed algorithms in the respect of secrecy sumrate compared with the conventional zero-forcing beamforming using semi-orthogonal user selection algorithms. Furthermore, simulations show how our proposed algorithms resist against eavesdropping from collusive vehicles located in the same secure region by flexibly altering the size of secure region and interference-selection according to the traffic density.