A D2D user pairing algorithm based on motion prediction and power control

User pairing plays an important role in device-to-device (D2D) relay communication, contributing significantly to maintaining low energy consumption, high throughput, and overall energy efficiency in the communication system. To achieve these purposes, an attention-based long short-term memory motion prediction model (AT-LSTM) and propose a joint power control algorithm. Leveraging these techniques, we also propose a D2D user pairing algorithm, distance–power–SINR pairing algorithm (DPSPA), which comprehensively considers factors such as D2D communication distances, transmit power, and signal-to-interference-plus-noise ratio. Initially, the AT-LSTM model is utilized to predict the location of users. Subsequently, the distance between the user terminal device and each communication point and the base station, filtering cache points, and non-cache points within the D2D communication radius are calculated. Then, based on the distance, required transmission power, and signal-to-interference-plus-noise ratio of each point, the evaluation index (the best matching product) is obtained. Finally, the point with the maximum best matching product is selected for D2D direct communication mode, D2D relay communication mode, or cellular communication mode. Simulation results demonstrate that DPSPA effectively reduces system energy consumption, enhances system throughput, and improves overall energy efficiency.