Network Slicing Based Joint Optimization of Beamforming and Resource Selection Scheme for Energy Efficient D2D Networks

被引:1
作者
Papachary, Biroju [1 ]
Arya, Rajeev [1 ]
Dappuri, Bhasker [2 ]
机构
[1] National Institute of Technology Patna, Wireless Sensor Networks Lab, Department of Electronics & Communication Engineering, Patna
[2] CMR Engineering College, Department of Electronics and Communication Engineering, Hyderabad
来源
Intelligent and Converged Networks | 2024年 / 5卷 / 03期
关键词
device-to-device communication; Enhanced Mobile Broadband (eMBB); heterogeneous cellular network; network slicing; Ultra Reliable Low Latency Communication (URLLC);
D O I
10.23919/ICN.2024.0018
中图分类号
学科分类号
摘要
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 £1-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. © 2020 Tsinghua University Press.
引用
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页码:248 / 264
页数:16
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