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Cooperative Intelligent Transportation Systems (C-ITS) will change the modes of road safety and traffic management, especially at intersections without traffic lights, namely unsignalized intersections. Existing researches focus on vehicle control within a small area around an unsignalized intersection. This paper expands the control domain to a large area with multiple intersections. In particular, a Multi-intersection Vehicular Cooperative Control (MiVeCC) is proposed to enable cooperation among vehicles in a large area with multiple unsignalized intersections. Firstly, a vehicular end-edge-cloud computing framework is proposed to facilitate end-edge-cloud vertical cooperation and horizontal cooperation among vehicles. Under the framework, a two-stage reinforcement learning is implemented to obtain the optimal policy for vehicle control. To support RL in the proposed framework, a multi-vehicle state representation method and a safety-oriented value representation method are designed. The former structures the collected vehicle information, and the latter evaluates the traffic condition. A multi-intersection simulation platform is developed to evaluate the proposed scheme. Simulation results show that the proposed MiVeCC can improve travel efficiency at multiple intersections by up to 4.59 times without collision compared with benchmark methods. [ABSTRACT FROM AUTHOR]

Single-input multiple-output non-orthogonal multiple access (SIMO-NOMA) is a promising technology for the uplink (UL) of the Internet of things (IoT). A rate splitting scheme to guarantee max-min fairness (MMF) of SIMO-NOMA is studied. First, the achievable data rate of the minimum mean square error successive interference cancellation (MMSE-SIC) detection is formulated. An upper bound for the minimum data rate of UL users is derived, and it is proved that the upper bound can be achieved by rate splitting with MMSE-SIC detection. Then, an exhaustive-search rate splitting algorithm to maximize the minimum data rate is designed. The existence of a lower bound for the minimum data rate with two-layer SIMO-NOMA is proved. A low-complexity two-layer rate splitting algorithm is designed with suitable detection order to exceed the lower bound. Numerical results verify that rate splitting SIMO-NOMA has higher minimum data rate and lower transmission latency than single-input multiple-output orthogonal multiple access (SIMO-OMA) and un-layered SIMO-NOMA. [ABSTRACT FROM AUTHOR]