A Base Station DTX Scheme for OFDMA Cellular Networks Powered by the Smart Grid

Wang, Qiang; Zhao, Feng; Chen, Tiejun

doi:10.1109/access.2018.2876395

Cited by 10 publications

(3 citation statements)

References 22 publications

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“…This offers efficient infrastructure for information transmission, interoperability, and allowing real-time communication. Discontinuous transmission is also identified as an essential technology to improve energy efficiency, particularly in wireless cellular networks [68]. This is achieved by incorporating the sleep/active mode technique on particular components embedded in the network, which further minimizes the power consumption and improves the reliability of the grids.…”

Section: Distribution Domainmentioning

confidence: 99%

A Review of Cognitive Radio Smart Grid Communication Infrastructure Systems

2020

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The cognitive smart grid (SG) communication paradigm aims to mitigate quality of service (QoS) issues in obsolete communication architecture associated with the conventional electrical grid. This paradigm entails the integration of advanced information and communication technologies (ICTs) into power grids, enabling a two-way flow of information. However, due to the exponential increase in wireless applications and services, also driven by the deployment of the Internet of Things (IoT) smart devices, SG communication systems are expected to handle large volumes of data. As a result, the operation of SG networks is confronted with the major challenge of managing and processing data in a reliable and secure manner. The existing works in the literature proposed architectures with the objective to mitigate the underlying QoS issues such as latency, bandwidth, data congestion, energy efficiency, etc. In addition, a variety of communication technologies have been analyzed for their capacity to support stringent QoS requirements for diverse SGs environments. This notwithstanding, a standard architecture designed to mitigate the aforementioned issues for SG networks remains a work-in-progress. The main objective of this paper is to investigate the emerging technologies such as cognitive radio networks (CRNs) as part of the Fifth-Generation (5G) mobile technology for reliable communication in SG networks. Furthermore, a hybrid architecture based on the combination of fog computing and cloud computing is proposed. In this architecture, real-time latency-sensitive information is given high priority, with fog edge based servers deployed in close proximity to home area networks (HANs) for preprocessing and analyzing of information collected from smart IoT devices. In comparison to the recent works in the literature, which are mainly based on CRNs and 5G separately, the proposed architecture in this paper incorporates the combination of CRNs and 5G for reliable and efficient communication in SG networks.

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Section: Distribution Domainmentioning

confidence: 99%

A Review of Cognitive Radio Smart Grid Communication Infrastructure Systems

2020

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“…Moreover, the energy exchange between the grids and the SPBSs would require a large number of financial transactions. For such a large number of transactions, the traditional method of storing every single energy transaction on a centralized database is not plausible [19]. Another significant issue with centralized frameworks is their lack of transparency and vulnerability to several kinds of malicious attacks.…”

Section: Introductionmentioning

confidence: 99%

A blockchain-based framework for energy trading between solar powered base stations and grid

Hassija

Gupta

Chamola

et al. 2020

Proceedings of the Twenty-First International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Netw

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The rapidly increasing mobile traffic across the globe has proliferated the deployment of cellular base stations, which has, in turn, led to an increase in the power consumption and carbon footprint of the telecommunications industry. In recent times, solar-powered base stations (SPBSs) have gained much popularity in the telecom sector due to their ability to make operations more sustainable. However, some potential energy benefits rendered by the SPBSs have not yet been realized. In areas with dense base station deployment or low mobile traffic, SPBSs store surplus energy, which, in most instances, gets lost due to limited charge storage capacity of the batteries. To limit the wastage of energy, an appropriate mechanism enabling the utilization of excess energy produced by these base stations can be adopted. To this end, we model a Base Station-to-Grid (BS2G) network in which the grid can utilize surplus energy spared by the SPBSs. To overcome challenges in regards to scalability, robustness, and cost-optimization, we propose using the blockchain technology to create the BS2G network. Blockchain is a distributed ledger designed to record transactions in a transparent, lightweight, and tamper-proof manner. To make energy trade between base stations and the grid cost-effective, a game-theoretical approach has also been adopted in this paper. The proposed model simplifies the process of energy trading while also making it cost-optimal. CCS CONCEPTS • Networks → Peer-to-peer networks; • Hardware → Energy generation and storage; Smart grid.

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“…Empirical research on global warming and climate change identifies the CO 2 emission as the key factor for increasing the atmospheric GHG emissions [1]. Climate change threatens the quality of life and the habitability of planet earth for many species, which significantly reduce the prospect of ensuring energy, environmental sustainability, and economic effectiveness (3E) of energy supply.…”

Section: Introductionmentioning

confidence: 99%

Binary Particle Swarm Optimization for Scheduling MG Integrated Virtual Power Plant Toward Energy Saving

et al. 2019

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This paper introduces a novel optimal schedule controller to manage renewable energy resources (RESs) in virtual power plant (VPP) using binary particle swarm optimization (BPSO) algorithm. It is crucial to minimize the costs giving priority for sustainable resources use instead of purchasing from the national grid. The effectiveness of the proposed approach is examined by the IEEE 14 bus system containing microgrids (MGs) integrated with RESs in the form of VPP. Real load demand recorded is used to model and simulate the test case studies of the system for 24 h in Perlis, Malaysia. Moreover, weather data collected from the Malaysian Meteorological Department such as wind, solar, fuel, and battery status data are used in the BPSO to find the best ON and OFF schedules. The results found that the developed BPSO algorithm is robust in reducing energy consumption and emissions of the VPP. This study contributes to the development of an optimization algorithm for an optimal scheduling controller of MG integrated VPP in order to reduce carbon emissions and manage sustainable energy. Finally, a comparative analysis of the optimal algorithms over conventional justifies the use of RESs integration and validates the developed BPSO for sustainable energy management and emissions reduction. INDEX TERMS Virtual power plant, microgrid, energy management, carbon reduction, scheduling controller, optimization.

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A Base Station DTX Scheme for OFDMA Cellular Networks Powered by the Smart Grid

Cited by 10 publications

References 22 publications

A Review of Cognitive Radio Smart Grid Communication Infrastructure Systems

A Review of Cognitive Radio Smart Grid Communication Infrastructure Systems

A blockchain-based framework for energy trading between solar powered base stations and grid

Binary Particle Swarm Optimization for Scheduling MG Integrated Virtual Power Plant Toward Energy Saving

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