A Cellular Network Resource Allocation Strategy Based on D2D Communication

Abstract

To address the problems of system capacity reduction due to high system interference in highway vehicular communication scenarios, a resource allocation strategy for cellular vehicular communication based on device-to-device (D2D) communication is proposed. A mathematical model is constructed with CUE user channel capacity as the optimization objective, considering resource sharing between device-to-device users (DUE) and cellular users (CUE), and the model is solved through three stages. Firstly, it is proposed to calculate the user channel gain to construct the DUE user channel gain matrix and compare the total channel gain after user multiplexing to manage the user clustering to reduce the interference between users. Secondly, the elite reverse learning strategy and Lévy flight strategy were introduced to improve the sparrow search algorithm, which increased the convergence speed and the ability to escape from the local optimal solution and optimized the channel matching problem. Finally, the water injection algorithm is invoked to solve the power allocation problem to maximize the channel capacity of CUE. Simulation experimental results show that the strategy achieves a system capacity of 340 bps/Hz while ensuring that the system communication is basically stable.