Delay-Aware Energy-Efficient Joint Power Control and Mode Selection in Device-to-Device Communications for FREEDM Systems in Smart Grids

Abstract

Cellular technology with long-term evolution (LTE)-based standards is a promising technology for smart grid communication networks. However, the integration of cellular technology and smart grid communications is a significant challenge due to the transmission of simultaneous and delay-sensitive smart grid data. The Device-to-device (D2D) communications are proposed as critical solutions to enhance the performance of the LTE. In this paper, we study energy efficiency and delay problems in D2D underlaying cellular communications for the future renewable electric energy delivery and management (FREEDM) system in smart grid with different message sizes and varying channel conditions. We adopt a D2D-assisted relaying framework to assist links that meet poor channel conditions in order to increase the data rate of intelligent energy management devices with large size report. We propose a joint power control and mode selection scheme to deal with the problem and develop a brute-force-based algorithm to find the solutions. We conduct simulations to show the effectiveness of the proposed scheme in balancing the tradeoff between energy efficiency and end-to-end delay and show significant energy efficiency improvements when exploiting the proposed scheme compared to direct and relaying schemes in a variety of different conditions.

Spatiotemporal D2D Small Cell Allocation and On-Demand Deployment for Microgrids

“…The k-means clustering proposed SC powering algorithm also performs acceptable convergence with the maximum convergence time for N = 600 as 20.22ms. Therefore, the overall achieved convergence time of TOSPO is as small as 25.08ms, sufficient to support microgrids [44].…”

IoT Underlying Cellular Uplink Through D2D Communication Principle

“…Therefore, transmission power control is crucial for mitigating interference and maximizing network spectral performance. In the literature, there has been considerable interest in power control for mitigating the interference in underlying D2D communication [4], [5] whereas some recent studies [6]- [10] have addressed both delay and power control.…”

“…In all existing D2D performance analysis studies, the delay analysis of the used power control approaches has been discussed independently from the supported individual data rates, with the focus being on the sum spectral efficiency [9], [11] or energy efficiency [8], [10]. Furthermore, none of these studies have addressed individual rates for both CU and D2D pairs.…”

“…In [9], the authors used priority transmission mechanisms to satisfy the requirements of diverse traffic types in a D2D heterogeneous network, and the performance of the D2D underlay cellular network was analyzed in terms of overall average throughput and delay. In [10], a joint power control and mode selection scheme for D2D underlying communication was proposed to maximize energy efficiency while meeting the strict delay requirements of a specific type of smart grid communication. However, to satisfy the delay requirement, the overall scheme must consider two other transmission options rather than relying on only D2D communication.…”

Adaptive Protection Scheme for FREEDM Microgrid Based on Convolutional Neural Network and Gorilla Troops Optimization Technique

“…The control signals are then delivered to these devices and RERs. In the FREEDM system, a communication channel is performed for the data and information transferring among the connected RERs and loads and the control center [3]. There are many advantages of the FREEDM system, including controlling the power flow, reducing the size and weight compared with the traditional transformers, and the plug-and-play capability for the RERs and loads.…”