Network slicing based joint optimization of beamforming and resource selection scheme for energy efficient D2D networks

The integration of network slicing into a Device-to-Device (D2D) network is a promising technological approach for efficiently accommodating Enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communication (URLLC) services. In this work, we aim to optimize energy efficiency and resource allocation in a D2D underlay cellular network by jointly optimizing beamforming and Resource Sharing Unit (RSU) selection. The problem of our investigation involves a Mixed-Integer Nonlinear Program (MINLP). To solve the problem effectively, we utilize the concept of the Dinkelbach method, the iterative weighted ℓ1-norm technique, and the principles of Difference of Convex (DC) programming. To simplify the solution, we merge these methods into a two-step process using Semi-Definite Relaxation (SDR) and Successive Convex Approximation (SCA). The integration of network slicing and the optimization of short packet transmission are the proposed strategies to enhance spectral efficiency and satisfy the demand for low-latency and high-data-rate requirement applications. The Simulation results validate that the proposed method outperforms the benchmark schemes, demonstrating higher throughput ranging from 11.79% to 28.67% for URLLC users, and 13.67% to 35.89% for eMBB users, respectively.