Journal articles: 'Wireless Communications, Energy Efficiency, Green Networks'

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Fettweis, Gerhard P., Kwang-Cheng Chen, and Rahim Tafazoli. "Green radio: Energy efficiency in wireless networks." Journal of Communications and Networks 12, no. 2 (April 2010): 99–102. http://dx.doi.org/10.1109/jcn.2010.6391365.

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Reddy, G. Chenna Kesava, Dr A. A. Ansari, and Dr S. China Venkateswarlu. "Green Communication in Wireless Power Consumption and Energy Efficient Trade-offs." Revista Gestão Inovação e Tecnologias 11, no. 4 (August 4, 2021): 4082–95. http://dx.doi.org/10.47059/revistageintec.v11i4.2433.

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Energy efficiency is a significant issue in portable wireless networks since the battery life of versatile terminals is restricted. Protection of battery power has been tended to utilizing numerous procedures. Wireless sensor networks (WSNs), framed by various little gadgets fit for detecting, processing, and wireless correspondence are arising as a progressive innovation, with applications in different territories. The novel highlights of wireless sensor networks have carried new difficulties and issues to the field of conveyed and communitarian data preparing. In the light of the importance of reducing operating consumpt and maintaining cellular network profitability, energy efficiency in cell networks has received a crucial consideration from both scholars and the business, despite the fact that these networks are “green communication.” Since the base station is the most important energy buyer in the business, efforts have been undertaken to review the use of the base station and to identify ways to energy efficiency improvements. The trade-offs between energy utilization and throughput, under nearby just as under helpful detecting, are portrayed. The Energy efficient tradeoffs have been arranged dependent on every convention layer and examined its effect in the organization energy efficiency.

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Lorincz, Josip, Antonio Capone, and Jinsong Wu. "Greener, Energy-Efficient and Sustainable Networks: State-Of-The-Art and New Trends." Sensors 19, no. 22 (November 8, 2019): 4864. http://dx.doi.org/10.3390/s19224864.

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Although information and communications technologies (ICTs) have the potential of enabling powerful social, economic and environmental benefits, ICT systems give a non-negligible contribution to world electricity consumption and carbon dioxide (CO2) footprint. This contribution will sustain since the increased demand for user′s connectivity and an explosion of traffic volumes necessitate continuous expansion of current ICTs services and deployment of new infrastructures and technologies which must ensure the expected user experiences and performance. In this paper, analyses of costs for the global annual energy consumption of telecommunication networks, estimation of ICT sector CO2 footprint contribution and predictions of energy consumption of all connected user-related devices and equipment in the period 2011–2030 are presented. Since presented estimations of network energy consumption trends for main communication sectors by 2030 shows that highest contribution to global energy consumption will come from wireless access networks and data centres (DCs), the rest of the paper analyses technologies and concepts which can contribute to the energy-efficiency improvements of these two sectors. More specifically, different paradigms for wireless access networks such as millimetre-wave communications, Long-Term Evolution in unlicensed spectrum, ultra-dense heterogeneous networks, device-to-device communications and massive multiple-input multiple-output communications have been analysed as possible technologies for improvement of wireless networks energy efficiency. Additionally, approaches related to the DC resource management, DCs power management, green DC monitoring and thermal management in DCs have been discussed as promising approaches to improvement of DC power usage efficiency. For each of analysed technologies, future research challenges and open issues have been summarised and discussed. Lastly, an overview of the accepted papers in the Special Issue dedicated to the green, energy-efficient and sustainable networks is presented.

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Yadav, Ramnaresh, Keshav Singh, and Ashwani Kumar. "Optimal Power Allocation for Achieving Secure Green Cognitive Radio Networks." Electronics 11, no. 13 (June 22, 2022): 1952. http://dx.doi.org/10.3390/electronics11131952.

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In cognitive radio networks, wireless nodes adapt to the surrounding radio environment and utilize the spectrum of licensed users. The cognitive radio environment is dynamic, and wireless channels are accessible by both legitimate and illegitimate users. Therefore, maintaining the security of cognitive radio networks is a challenging task, which must be addressed thoroughly. Further, with the recent exponential surge in wireless nodes and associated high data rate requirements, energy consumption is also growing at an unprecedented rate. Hence, energy efficiency becomes an important metric that must be considered in the design of future wireless networks. Accordingly, by considering the great ecological and economic benefits of green wireless networks, this work focus on energy-efficient resource allocation in secure cognitive radio networks. Since physical-layer security is an emerging technique that improves the security of communication devices, in this paper, an ergodic secure energy efficiency problem for a cognitive radio network is formulated with a primary user, a secondary user, and an eavesdropper. As the formulated problem is non-convex, a concave lower bound is applied to transform the original non-convex problem into a convex one. Further, by adopting the fractional programming and dual decomposition techniques, optimal power allocation strategies are obtained with the aim of maximizing the ergodic secure energy efficiency of the secondary user with constraints on the average interference power and average transmit power. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm.

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Oborkhale, L. I., C. C. Nwaogu, and O. A. Amadi. "Achieving energy efficiency for 5G at base stations level." Scientia Africana 20, no. 3 (January 26, 2022): 1–10. http://dx.doi.org/10.4314/sa.v20i3.1.

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As the era of 5th Generation (5G) networks is dawning, several pertinent issues associated with the improvements that have to be achieved in future communications are attracting increasing research attention. This work, considered achieving energy efficiency for 5G at base stations level. Energy efficiency simply means using less energy to perform the same task thereby, eliminating energy waste. The objective of this paper is to examine the ways of deploying energy efficient hardware at the base stations in order to make the base stations more green energy based. Considering the current energy concerns, base stations in emerging wireless networks range from low-energy BSS to high-energy BSS with entirely different constraints in either case. In view of these extremes, this paper examines the major components behind energy-efficient wireless communication network design during the peak and off-peak traffic periods. It was discovered that the Power amplifier consumes up to 59% of the energy at the base stations. Improving a Power amplifier by bringing linearity could improve the efficiency of the BS and hence reduce the energy crunch at the BS level from 59% to 51%.

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Nguyen, Hieu V., Hyeon Min Kim, Gil-Mo Kang, Kha-Hung Nguyen, Van-Phuc Bui, and Oh-Soon Shin. "A Survey on Non-Orthogonal Multiple Access: From the Perspective of Spectral Efficiency and Energy Efficiency." Energies 13, no. 16 (August 8, 2020): 4106. http://dx.doi.org/10.3390/en13164106.

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Non-orthogonal multiple access (NOMA) is a promising technology for next-generation wireless networks with emerging demands on low latency, high throughput, and massive connectivity. Unlike orthogonal multiple access, NOMA allows multiple users to share the same radio resources, which significantly improves spectral efficiency (SE). To achieve green wireless communications for numerous networked devices, NOMA helps reduce energy consumption while satisfying rate fairness and quality-of-experience requirements. The goal of this paper is to introduce the innovative approaches for NOMA in terms of the SE and energy efficiency, and discuss emerging technologies involved with NOMA. Further, its challenges and future research directions are highlighted.

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Huang, Tangsen, Xiangdong Yin, and Xiaowu Li. "Energy-efficient and intelligent cooperative spectrum sensing algorithm in cognitive radio networks." International Journal of Distributed Sensor Networks 18, no. 9 (September 2022): 155013292211251. http://dx.doi.org/10.1177/15501329221125119.

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Green communication is the demand of current and future wireless communication. As the next-generation communication network, cognitive radio network also needs to meet the requirements of green communication. Therefore, improving energy efficiency is an inevitable requirement for the development of cognitive radio networks. However, there is a need to compromise sensing performance while improving energy efficiency. To take into account the two important indicators of sensing performance and energy efficiency, a grouping algorithm is proposed in this article, which can effectively improve the energy efficiency while improving the spectrum sensing performance. The algorithm obtains the initial value of the reliability of the nodes through training, and sorts them according to the highest reliability value, then selects an even number of nodes with the highest reliability value, and divides the selected nodes into two groups, and the two groups of nodes take turns in Alternate work. At this time, other nodes not participating in cooperative spectrum sensing are in a silent state, waiting for the instruction of the fusion center. The experimental results show that compared with the traditional algorithm, the proposed algorithm has a great improvement in the two indicators of sensing performance and energy efficiency.

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Gao, Jing, Xin Guan, Shuyue Zhang, and Xiao Meng. "Resource Allocation Optimization Based on Energy Efficiency in Green Cloud Radio Access Network." Wireless Communications and Mobile Computing 2022 (May 11, 2022): 1–18. http://dx.doi.org/10.1155/2022/8932961.

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Compared with traditional cellular networks, cloud wireless access network (C-RAN) can save more energy consumption because it centrally processes the signals in the baseband unit (BBU) pool served by the cloud platform. Aiming at the limited fronthaul capacity of the fronthaul link caused by massive data and the huge energy consumption caused by the explosive growth of mobile traffic, an energy-saving resource management scheme that is powered by a mixture of on-grid and green energy is proposed in this paper. Specifically, a new network energy efficiency (EE) model is constructed. The RRH with hybrid energy to supply power of the model in response to green communication and the model can also realize two functions: information decoding and wireless charging at the same time. The total power consumption including remote radio head (RRH), fronthaul link, BBU pool, and wireless charging equipment of user equipment is considered. Based on network energy efficiency model, in addition to considering the user’s quality of service (QoS), data rate requirements, transmission power of RRHs, and maximum battery capacity constraints, the constraints of fronthaul link capacity constraints also are considered in this paper. In order to solve the proposed optimization problem, a joint strategy of power allocation, resource block (RB) allocation, and power allocation ratio adjustment is proposed in this paper. However, the objective function of energy efficiency optimization problem is nonconvex and cannot be solved directly. Therefore, an equivalent convex feasibility problem is reconstructed, and the optimal solution is obtained by Lagrange dual decomposition method. Simulation results show that the proposed resource allocation scheme can provide higher energy efficiency for the network.

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Ram, Mahendra, Sushil Kumar, Vinod Kumar, Ajay Sikandar, and Rupak Kharel. "Enabling Green Wireless Sensor Networks: Energy Efficient T-MAC Using Markov Chain Based Optimization." Electronics 8, no. 5 (May 13, 2019): 534. http://dx.doi.org/10.3390/electronics8050534.

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Due to the rapidly growing sensor-enabled connected world around us, with the continuously decreasing size of sensors from smaller to tiny, energy efficiency in wireless sensor networks has drawn ample consideration in both academia as well as in industries’ R&D. The literature of energy efficiency in wireless sensor networks (WSNs) is focused on the three layers of wireless communication, namely the physical, Medium Access Control (MAC) and network layers. Physical layer-centric energy efficiency techniques have limited capabilities due to hardware designs and size considerations. Network layer-centric energy efficiency approaches have been constrained, in view of network dynamics and available network infrastructures. However, energy efficiency at the MAC layer requires a traffic cooperative transmission control. In this context, this paper presents a one-dimensional discrete-time Markov chain analytical model of the Timeout Medium Access Control (T-MAC) protocol. Specifically, an analytical model is derived for T-MAC focusing on an analysis of service delay, throughput, energy consumption and power efficiency under unsaturated traffic conditions. The service delay model calculates the average service delay using the adaptive sleep wakeup schedules. The component models include a queuing theory-based throughput analysis model, a cycle probability-based analytical model for computing the probabilities of a successful transmission, collision, and the idle state of a sensor, as well as an energy consumption model for the sensor’s life cycle. A fair performance assessment of the proposed T-MAC analytical model attests to the energy efficiency of the model when compared to that of state-of-the-art techniques, in terms of better power saving, a higher throughput and a lower energy consumption under various traffic loads.

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Anwar, Muhammad, Abdul Abdullah, Ayman Altameem, Kashif Qureshi, Farhan Masud, Muhammad Faheem, Yue Cao, and Rupak Kharel. "Green Communication for Wireless Body Area Networks: Energy Aware Link Efficient Routing Approach." Sensors 18, no. 10 (September 26, 2018): 3237. http://dx.doi.org/10.3390/s18103237.

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Recent technological advancement in wireless communication has led to the invention of wireless body area networks (WBANs), a cutting-edge technology in healthcare applications. WBANs interconnect with intelligent and miniaturized biomedical sensor nodes placed on human body to an unattended monitoring of physiological parameters of the patient. These sensors are equipped with limited resources in terms of computation, storage, and battery power. The data communication in WBANs is a resource hungry process, especially in terms of energy. One of the most significant challenges in this network is to design energy efficient next-hop node selection framework. Therefore, this paper presents a green communication framework focusing on an energy aware link efficient routing approach for WBANs (ELR-W). Firstly, a link efficiency-oriented network model is presented considering beaconing information and network initialization process. Secondly, a path cost calculation model is derived focusing on energy aware link efficiency. A complete operational framework ELR-W is developed considering energy aware next-hop link selection by utilizing the network and path cost model. The comparative performance evaluation attests the energy-oriented benefit of the proposed framework as compared to the state-of-the-art techniques. It reveals a significant enhancement in body area networking in terms of various energy-oriented metrics under medical environments.

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Darus, Muhamad Firdaus, Fakrulradzi Idris, and Norlezah Hashim. "Energy-efficient non-orthogonal multiple access for wireless communication system." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (April 1, 2023): 1654. http://dx.doi.org/10.11591/ijece.v13i2.pp1654-1668.

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<p>Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed.</p>

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Basnayake, Vishaka, Dushantha Nalin K. Jayakody, Vishal Sharma, Nikhil Sharma, P. Muthuchidambaranathan, and Hakim Mabed. "A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G." Information 11, no. 2 (February 7, 2020): 89. http://dx.doi.org/10.3390/info11020089.

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Energy efficiency is a major concern in the emerging mobile cellular wireless networks since massive connectivity is to be expected with high energy requirements from the network operators. Non-orthogonal multiple access (NOMA) being the frontier multiple access scheme for 5G, there exists numerous research attempts on enhancing the energy efficiency of NOMA enabled wireless networks while maintaining its outstanding performance metrics such as high throughput, data rates and capacity maximized optimally.The concept of green NOMA is introduced in a generalized manner to identify the energy efficient NOMA schemes. These schemes will result in an optimal scenario in which the energy generated for communication is managed sustainably. Hence, the effect on the environment, economy, living beings, etc is minimized. The recent research developments are classified for a better understanding of areas which are lacking attention and needs further improvement. Also, the performance comparison of energy efficient, NOMA schemes against conventional NOMA is presented. Finally, challenges and emerging research trends, for energy efficient NOMA are discussed.

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Huang, Huifeng, Zhihong Wu, and Shaoju Tang. "Energy-saving route optimizationin a software-defined wireless sensor network." International Journal of Distributed Sensor Networks 14, no. 10 (October 2018): 155014771880765. http://dx.doi.org/10.1177/1550147718807655.

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Energy efficiency in wireless sensor networks is an important concern of ‘green’ Internet of Things. The existing energy-saving routing protocols usually compute the route in isolation, which is disadvantageous to globally optimize the energy consumption. In this article, we propose a novel energy-saving route optimization solution based on the software-defined wireless sensor network. In our proposed solution, the controller obtains the overall information about the network topology and the existing routes. Based on the above information, this solution centrally optimizes the routes in a global manner. In contrast to the existing energy-saving routing protocols, the central route optimization better reduces the energy consumption from an overall perspective. The global route optimization tends to reduce the overall energy consumption using a small number of sensors, which can improve the effectiveness of the used sensors. However, using a small number of sensors leads to high energy consumption of related sensors. To solve the above problem, our proposed solution uses a routing evasion mechanism to balance the energy consumption between sensors.

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Miličević, Zoran, and Zoran Bojković. "Military green technology: Present and future." Vojnotehnicki glasnik 71, no. 1 (2023): 136–52. http://dx.doi.org/10.5937/vojtehg71-40544.

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Introduction/purpose: This paper aims to present military green technology through present concepts, solutions and challenges, as well as through future trends, particularly in wireless communication. Methods: Analyses and syntheses were used to consider various aspects, challenges and developments of military green technology. Results: Important aspects of organization, challenges and strategies in military green technologies are presented. Next, the role of a green energy action plan is emphasized. Furthermore, green defence solutions and security challenges are considered. Besides presenting green technologies of today, primarily focused on wireless networks, especially 5G, the paper also considers the impact of biofuels, methanol-based fuel cells, hydrogen fuel cells, hybrid electrical vehicles and photovoltaic energy. Finally, green technologies for the future are presented through some of the most important technologies: next generation wireless networks, pulse detonation engines, piezoelectricity, and biodegradable platforms. Conclusion: Military green technology is now necessary for approaching wireless networking in order to meet challenges of high demands of wireless traffic and energy consumption. Also, military green technology will require further constant considerations in the field of efficiency and sustainability of application as well as research to provide different acceptable solutions, not only in technical, but also in the organizational domain, in order to be applied in military environment.

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Hossain, Md Sanwar, Khondoker Ziaul Islam, Abu Jahid, Khondokar Mizanur Rahman, Sarwar Ahmed, and Mohammed H. Alsharif. "Renewable Energy-Aware Sustainable Cellular Networks with Load Balancing and Energy-Sharing Technique." Sustainability 12, no. 22 (November 10, 2020): 9340. http://dx.doi.org/10.3390/su12229340.

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With the proliferation of cellular networks, the ubiquitous availability of new-generation multimedia devices, and their wide-ranging data applications, telecom network operators are increasingly deploying the number of cellular base stations (BSs) to deal with unprecedented service demand. The rapid and radical deployment of the cellular network significantly exerts energy consumption and carbon footprints to the atmosphere. The ultimate objective of this work is to develop a sustainable and environmentally-friendly cellular infrastructure through compelling utilization of the locally available renewable energy sources (RES) namely solar photovoltaic (PV), wind turbine (WT), and biomass generator (BG). This article addresses the key challenges of envisioning the hybrid solar PV/WT/BG powered macro BSs in Bangladesh considering the dynamic profile of the RES and traffic intensity in the tempo-spatial domain. The optimal system architecture and technical criteria of the proposed system are critically evaluated with the help of HOMER optimization software for both on-grid and off-grid conditions to downsize the electricity generation cost and waste outflows while ensuring the desired quality of experience (QoE) over 20 years duration. Besides, the green energy-sharing mechanism under the off-grid condition and the grid-tied condition has been critically analyzed for optimal use of green energy. Moreover, the heuristic algorithm of the load balancing technique among collocated BSs has been incorporated for elevating the throughput and energy efficiency (EE) as well. The spectral efficiency (SE), energy efficiency, and outage probability performance of the contemplated wireless network are substantially examined using Matlab based Monte–Carlo simulation under a wide range of network configurations. Simulation results reveal that the proper load balancing technique pledges zero outage probability with expected system performance whereas energy cooperation policy offers an attractive solution for developing green mobile communications employing better utilization of renewable energy under the proposed hybrid solar PV/WT/BG scheme.

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Filippini, Ilario, Alessandro Enrico Cesare Redondi, and Antonio Capone. "Beyond Cellular Green Generation: Potential and Challenges of the Network Separation." Mobile Information Systems 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/7149643.

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This article introduces the ideas investigated in the BCG2 project of the GreenTouch consortium. The basic concept is to separate signaling and data in the wireless access network. Transmitting the signaling information separately maintains coverage even when the whole data network is adapted to the current load situation. Such network-wide adaptation can power down base stations when no data transmission is needed and, thus, promises a tremendous increase in energy efficiency. We highlight the advantages of the separation approach and discuss technical challenges opening new research directions. Moreover, we propose two analytical models to assess the potential energy efficiency improvement of the BCG2 approach.

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Wang, Qiang, and Hai-Lin Liu. "Optimized Base Station Sleeping and Renewable Energy Procurement Scheme Using PSO." International Journal of Swarm Intelligence Research 8, no. 1 (January 2017): 54–73. http://dx.doi.org/10.4018/ijsir.2017010103.

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Energy efficiency of the wireless networks has drawn more and more attentions due to the requirement of the green communication. The base station sleeping strategy and resource allocation can effectively improve the energy efficiency for the wireless networks. Meanwhile, renewable energy is important to decrease the carbon emission. In this paper, the authors propose a joint BS sleeping strategy, resource allocation and renewable energy procurement scheme to maximize the profit of the network operators and minimize the carbon emission. Then, a joint optimization problem is formulated, which is a mixed integer programming problem. To solve it, they adopt the bi-velocity discrete particle swarm optimization (BVDPSO) algorithm to optimize the BS sleeping strategy. When the BS sleeping strategy is fixed, the authors propose an optimal algorithm based on Lagrange dual domain method to optimize the power allocation, subcarrier assignment and energy procurement. Numerical results illustrate the effectiveness of their proposed scheme and algorithm.

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Wang, Jiaze, Chunhua Hu, and Anfeng Liu. "Comprehensive Optimization of Energy Consumption and Delay Performance for Green Communication in Internet of Things." Mobile Information Systems 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/3206160.

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Energy efficiency as well as fast data transmission is vital to green communications-based applications for Internet of Things (IoT). Wireless sensors, which constitute one of the important parts of IoT, adopt duty cycle operating mode to save energy. Although duty cycle operating mode will decrease the energy consumption of sensor nodes, it leads to a larger communication delay. In this paper, a utility-based adaptive duty cycle (UADC) routing algorithm is proposed to increase energy efficiency, reduce transmission delay, and keep long lifetime at the same time. First, UADC routing algorithm adopts a comprehensive performance evaluation function to evaluate the utility of choosing different relay nodes. Then it selects the node which maximizes the utility of the system to perform data relay. The utility function synthesizes comprehensive indexes like the reliability, energy consumption, and delay of the node. UADC routing algorithm adopts a high-duty cycle operating mode in the areas which have more remaining energy to decrease the delay. And a low-duty cycle operating mode in the energy-strained areas is adopted to ensure a long lifetime. The simulation results also prove the significant performances of our proposed algorithms.

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Ayedi, Mariem, Esraa Eldesouky, and Jabeen Nazeer. "Energy-Spectral Efficiency Optimization in Wireless Underground Sensor Networks Using Salp Swarm Algorithm." Journal of Sensors 2021 (January 15, 2021): 1–16. http://dx.doi.org/10.1155/2021/6683988.

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Achieving high data rate transmission is critically constrained by green communication metrics in Wireless Sensor Networks (WSNs). A unified metric ensuring a successful compromise between the energy efficiency (EE) and the spectral efficiency (SE) is, then, an interesting design criterion in such systems. In this paper, we focus on EE-SE tradeoff optimization in Wireless Underground Sensor Networks (WUSNs) where signals penetrate through a challenging lossy soil medium and nodes’ power supply is critical. Underground sensor nodes gather and send sensory information to underground relay nodes which amplify-and-retransmit received signals to an aboveground sink node. We propose to optimize source and relay powers used for each packet transmission using an efficient recent metaheuristic optimization algorithm called Salp Swarm Algorithm (SSA). Thus, the optimal source and relay transmission powers, which maximize the EE-SE tradeoff under the maximum allowed transmission powers and the initial battery capacity constraints, are obtained. Further, we study the case where the underground medium properties are dynamic and change from a transmission to another. For this situation, we propose to allocate different maximum node powers according to the soil medium conditions. Simulation results prove that our proposed optimization achieves a significant EE-SE tradeoff and prolongs the network’s lifetime compared to the fixed allocation node power scheme. Additional gain is obtained in case of dynamic medium conditions.

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Shang, Xiaohui, Hao Yin, Aijun Liu, Mu Li, Yida Wang, and Yong Wang. "Secure Green-Oriented Multiuser Scheduling for Wireless-Powered Internet of Things." Wireless Communications and Mobile Computing 2020 (January 7, 2020): 1–11. http://dx.doi.org/10.1155/2020/7845107.

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In this paper, we consider the secure green-oriented multiuser scheduling for the wireless-powered Internet of Things (IoT) scenario, in which multiple source sensors communicate with a controller assisted by an intermediate sensor with the existence of a passive tapping device. Due to the limited energy, all sensors must acquire energy from external power beacons (PBs). Specifically, for the security improvement, we introduce two multiuser scheduling schemes possessing the optimal PB chosen by the relay, i.e., the best source sensor is scheduled in a random way (BSR), while the best source sensor is decided by the best PB (BSBP). Furthermore, for every scheme, we derive the analytical expressions for the secrecy outage probability (SOP) and investigate the secure energy efficiency (SEE) optimization problem with constricted transmission power in PBs. Simulation results reveal that the BSBP scheme provides better secrecy performance, and elevating the PBs quantity or reducing both the ratio of distance from PBs to source users and the total communication distance to some extent is helpful for improving SEE. In addition, the time-switching factor shows an important effect upon secrecy performance of the considered system.

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Du, Xiu Juan, Ke Jun Huang, Fan Liu, Zhen Xing Feng, and Sheng Lin Lan. "Micro-ANP：A Novel Network Protocol Architecture for Underwater Sensor Network." Applied Mechanics and Materials 303-306 (February 2013): 223–30. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.223.

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Underwater sensor network (UWSN) adopts acoustic communication and is characterized by high delay, low bandwidth, high error rate, low energy-consumption requirement and sparse topology, which lead to conventional network protocols for terrestrial WSN or other wireless multi-hop networks are unable to satisfy the performance of UWSN. On the other hand, the limited resources of energy, CPU and memory cause that the protocol stack running on the sensor node shouldn’t be much complicated. The paper proposes a novel, green network protocol architecture model tailored for UWSN, referred to as Micro-ANP, which is three layered structure including application, network transport, and physical layer. Furthermore, basing on Micro-ANP we realize the packet size optimization of UWSN through Matlab simulation. Micro-ANP protocol architecture and packet size optimization improve the energy efficiency of UWSN, prolong the network lifetime and achieve green network while meeting the requirement of QoS with the constraints of limited resource.

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Imoize, Agbotiname Lucky, Hope Ikoghene Obakhena, Francis Ifeanyi Anyasi, and Samarendra Nath Sur. "A Review of Energy Efficiency and Power Control Schemes in Ultra-Dense Cell-Free Massive MIMO Systems for Sustainable 6G Wireless Communication." Sustainability 14, no. 17 (September 5, 2022): 11100. http://dx.doi.org/10.3390/su141711100.

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The traditional multiple input multiple output (MIMO) systems cannot provide very high Spectral Efficiency (SE), Energy Efficiency (EE), and link reliability, which are critical to guaranteeing the desired Quality of Experience (QoE) in 5G and beyond 5G wireless networks. To bridge this gap, ultra-dense cell-free massive MIMO (UD CF-mMIMO) systems are exploited to boost cell-edge performance and provide ultra-low latency in emerging wireless communication systems. This paper attempts to provide critical insights on high EE operation and power control schemes for maximizing the performance of UD CF-mMIMO systems. First, the recent advances in UD CF-mMIMO systems and the associated models are elaborated. The power consumption model, power consumption parts, and energy maximization techniques are discussed extensively. Further, the various power control optimization techniques are discussed comprehensively. Key findings from this study indicate an unprecedented growth in high-rate demands, leading to a significant increase in energy consumption. Additionally, substantial gains in EE require efficient utilization of optimal energy maximization techniques, green design, and dense deployment of massive antenna arrays. Overall, this review provides an elaborate discussion of the research gaps and proposes several research directions, critical challenges, and useful recommendations for future works in wireless communication systems.

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Haseeb, Khalid, Fahad A. Alzahrani, Mohammad Siraj, Zahid Ullah, and Jaime Lloret. "Energy-Aware Next-Generation Mobile Routing Chains with Fog Computing for Emerging Applications." Electronics 12, no. 3 (January 23, 2023): 574. http://dx.doi.org/10.3390/electronics12030574.

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The Internet of Things (IoT) provides robust services to connected sensors in a distributed manner, and maintains real-time communication using wireless standards. The smart network has offered many autonomous smart systems to collect information from remote nodes, and share it by exploring the network layer. Researchers have recently offered a variety of ways to increase the effectiveness of emerging applications using trustworthy relaying systems. However, there are still many issues with route reformulation due to frequent disconnections of mobile devices and resource limitations. Furthermore, most of the existing methods for IoT systems are unable to utilize network resources, which lowers the performance of green networks. Thus, providing a foolproof solution for the autonomous system with energy efficiency is a challenging task. Therefore, this paper presents an algorithm for the mobile network using fog computing to reduce network disconnectivity. Furthermore, using security services, the proposed algorithm efficiently explores the characteristics of the device, and avoids malicious traffic to drain the additional energy consumption of the network. The main aspects of the proposed algorithm are as follows: (i) using the adjustable transmission power, the proposed algorithm offers a fault-tolerant solution to transmit the aggregated data over the unpredictable wireless system; (ii) with the support of fog nodes, the data load is reduced among devices with the offering of a secured authentication scheme. Using simulations, the proposed algorithm is tested, and its significance is demonstrated against other related studies.

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Su, Jinglei, Xue Chu, Seifedine Kadry, and Rajkumar S. "Internet-of-Things-Assisted Smart System 4.0 Framework Using Simulated Routing Procedures." Sustainability 12, no. 15 (July 29, 2020): 6119. http://dx.doi.org/10.3390/su12156119.

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The environment and energy are two important issues in the current century. The development of modern society is closely linked to energy and the environment. Internet of Things (IoT) and Wireless Sensor Networks (WSNs) have recently been developed substantially to contribute to the fourth transformation of the power grid, namely the smart grid. WSNs have the potential to improve power grid reliability via cable replacements, fault-tolerance features, large-scale protection, versatility to deploy, and cost savings in the smart grid environment. Moreover, because of equipment noise, dust heat, electromagnetic interference, multipath effects, and fading, current WSNs are making it very difficult to provide effective communication for the smart grid (SG) environment, in which WSN work is more difficult. For the smart system 4.0 framework, a highly reliable communication network based on the WSN is critically important for the successful operation of electricity grids in the next decade. To solve the above problem, a Robust Bio-Dynamic Stimulated Routing Procedure (RDSRP) has been proposed based on the real-time behavior of a new Hybrid Bird Optimizer (HBO) model. The presented innovative research and development is a small yet important aspect of continuous critical activities that address one of our society’s major challenges and that reverse the dangerous trends of environmental destruction. This study explores some of the most recent advances in this area, including energy efficiency and energy harvesting, which are expected to have a significant impact on green topics under smart systems in the Internet of things. The experimental results show that the proposed distributed system suggestively enhances network efficiency and reduces the transmission of excess packets for wireless sensor network-based smart grid applications.

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Zheng, Xin, Yu Nan, Fangsu Wang, Ruiqing Song, Gang Zheng, Gaocai Wang, Yuting Lu, and Qifei Zhao. "A Data Transmission Strategy with Energy Minimization Based on Optimal Stopping Theory in Mobile Cloud Computing." Wireless Communications and Mobile Computing 2019 (November 21, 2019): 1–11. http://dx.doi.org/10.1155/2019/1257150.

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Considering the widespread use of mobile devices and the increased performance requirements of mobile users, shifting the complex computing and storage requirements of mobile terminals to the cloud is an effective way to solve the limitation of mobile terminals, which has led to the rapid development of mobile cloud computing. How to reduce and balance the energy consumption of mobile terminals and clouds in data transmission, as well as improve energy efficiency and user experience, is one of the problems that green cloud computing needs to solve. This paper focuses on energy optimization in the data transmission process of mobile cloud computing. Considering that the data generation rate is variable, because of the instability of the wireless connection, combined with the transmission delay requirement, a strategy based on the optimal stopping theory to minimize the average transmission energy of the unit data is proposed. By constructing a data transmission queue model with multiple applications, an admission rule that is superior to the top candidates is proposed by using secretary problem of selecting candidates with the lowest average absolute ranking. Then, it is proved that the rule has the best candidate. Finally, experimental results show that the proposed optimization strategy has lower average energy per unit of data, higher energy efficiency, and better average scheduling period.

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Bao, Jingjing, Qiang Mai, Zhangwen Fang, and Xiaowen Mao. "ARM-Based Indoor RGB-LED Visible Light Communication System." Scientific Programming 2022 (June 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/8290106.

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As a new green solid-state light source, semiconductor light-emitting diodes (LEDs) have the advantages of low power consumption, small size, long life, short response time, and good modulation performance. At the same time, the frequency band to which LED light sources belong does not require regulatory registration, thus alleviating the current problem of spectrum scarcity for wireless communications. However, white LED-based visible light communication (VLC) systems suffer from limited bandwidth and low energy efficiency. Therefore, an ARM-based indoor RGB-LED VLC system is proposed. Firstly, the three RGB colours are mixed into white light, thus obtaining a larger modulation bandwidth than normal white LEDs while illuminating normally. Secondly, the S3C6410 processor is used to modulate and demodulate the RGB-LEDs with biased light OFDM, thus obtaining a high spectrum utilisation while ensuring system transmission stability. Then, according to the characteristics of the light source of the VLC system, the leading and window functions used in the optical network transceiver module are designed to improve the communication energy efficiency of the system. Finally, functional tests were carried out on an ARM development board. The experimental results show that with a single RGB-LED light source, the maximum transmission distance is 5 cm, the maximum average delay is 68 ms, the maximum throughput is 25 Mbps, and the BER is controlled below 3.2 × 10−3, which meets the basic communication requirements.

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Waseem, Athar, Aqdas Naveed, Sardar Ali, Muhammad Arshad, Haris Anis, and Ijaz Mansoor Qureshi. "Compressive Sensing Based Channel Estimation for Massive MIMO Communication Systems." Wireless Communications and Mobile Computing 2019 (May 27, 2019): 1–15. http://dx.doi.org/10.1155/2019/6374764.

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Massive multiple-input multiple-output (MIMO) is believed to be a key technology to get 1000x data rates in wireless communication systems. Massive MIMO occupies a large number of antennas at the base station (BS) to serve multiple users at the same time. It has appeared as a promising technique to realize high-throughput green wireless communications. Massive MIMO exploits the higher degree of spatial freedom, to extensively improve the capacity and energy efficiency of the system. Thus, massive MIMO systems have been broadly accepted as an important enabling technology for 5th Generation (5G) systems. In massive MIMO systems, a precise acquisition of the channel state information (CSI) is needed for beamforming, signal detection, resource allocation, etc. Yet, having large antennas at the BS, users have to estimate channels linked with hundreds of transmit antennas. Consequently, pilot overhead gets prohibitively high. Hence, realizing the correct channel estimation with the reasonable pilot overhead has become a challenging issue, particularly for frequency division duplex (FDD) in massive MIMO systems. In this paper, by taking advantage of spatial and temporal common sparsity of massive MIMO channels in delay domain, nonorthogonal pilot design and channel estimation schemes are proposed under the frame work of structured compressive sensing (SCS) theory that considerably reduces the pilot overheads for massive MIMO FDD systems. The proposed pilot design is fundamentally different from conventional orthogonal pilot designs based on Nyquist sampling theorem. Finally, simulations have been performed to verify the performance of the proposed schemes. Compared to its conventional counterparts with fewer pilots overhead, the proposed schemes improve the performance of the system.

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De Sanctis, Mauro, Ernestina Cianca, and Viraj Joshi. "Energy Efficient Wireless Networks Towards Green Communications." Wireless Personal Communications 59, no. 3 (February 22, 2011): 537–52. http://dx.doi.org/10.1007/s11277-011-0244-4.

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Diputra, Muhammad Ihsan, Ahmad Akbar Megantara, Pima Hani Safitri, and Didik Purwanto. "GECOM: GREEN COMMUNICATION CONCEPTS FOR ENERGY EFFICIENCY IN WIRELESS MULTIMEDIA SENSOR NETWORK." JUTI: Jurnal Ilmiah Teknologi Informasi 18, no. 2 (July 31, 2020): 85. http://dx.doi.org/10.12962/j24068535.v18i2.a942.

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SONG, XIAO-OU, and ZONG-QIANG LI. "A Green Geographic Routing in Wireless Sensor Network." Journal of Interconnection Networks 15, no. 03n04 (September 2015): 1540003. http://dx.doi.org/10.1142/s0219265915400034.

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The routing information is hard to maintain and the energy is limited in highly dynamic wireless sensor network. To solve these problems, energy-saving geographic routing (ESGR) is proposed, which does not maintain the network topology and can save energy. A node broadcast its position information to its neighboring nodes before transmitting data. The neighboring nodes compute the position of the virtual relay node using the data transmitter position, the base station position and the energy consumption for circuits and propagation. The neighboring nodes determine whether to become the relay node through competition based on its position, the destination position and the virtual relay node position. The neighboring nodes compute the delay time distributedly according to the competition strategy. The neighboring node with the shortest delay time can respond to the data sender first and become the sole relay node. The handshake mechanism efficiently prevents the collision among the neighboring nodes during competition, which is of high communication efficiency. When a routing hole is found, the relay region is changed and an approaching destination relay strategy is adopted, which reduces the impact of routing holes. The simulation shows that the proposed algorithm is better than BLR, because of the lower energy consumption and lower packet loss ratio. The ESGR algorithm is more appropriate for highly dynamic wireless network.

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Davaslioglu, Kemal, and Ender Ayanoglu. "Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks." IEEE Communications Surveys & Tutorials 16, no. 4 (2014): 2065–91. http://dx.doi.org/10.1109/comst.2014.2322951.

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Kumar V., Shiva, Rajashree V. Biradar, and V. C. Patil. "Design and Performance Analysis of Hybrid Energy Harvesting and WSN Application for More Life Time and High Throughput." International Journal of Circuits, Systems and Signal Processing 16 (January 17, 2022): 686–98. http://dx.doi.org/10.46300/9106.2022.16.85.

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the technology of wireless sensor-actuator networks (WSANs) is widely employed in the applications of IoT due to its wireless nature and it does not involve any wired structure. The wireless systems that are battery-driven can easily reconfigure the existing devices and sensors efficiently in the manufacturing units without employing any cable for power operation as well as for communication. The wireless sensor-actuator networks that are based on IEEE 802.15.4 consumes significantly less power. These networks are designed and built cost-effectively by considering the capacity of battery and expense so that they can be employed for many applications. The application of a typical wireless Autonomous Scheduling and Distributed Graph Routing (DDSR) has illustrated the reliability of employing its basic approaches for almost ten years and it consists of the accurate plot for routing and time-slotted channel hopping therefore ensuring accurate low-power wireless communication in the processing site. Officially declared by the controversial statements associated with the government of Greek experiences fourth industrialization. There is a huge requirement for sensor nodes link via WSAN in the industrial site. Also, reduced computational complexity is one of the drawbacks faced by the existing standards of WSAN which is caused because of their highly centralized traffic management systems and thereby significantly improves the consistency and accessibility of network operations at the expense of optimization. This research work enables the study of efficient Wireless DGR network management and also introduces an alternative for DDSR by enabling the sensor nodes to determine their data traffic routes for the transmission of data. When compared to the above two physical routing protocols, the proposed technique can drastically improve the performance of a network, throughput, and energy consumption under various aspects. Energy harvesting (EH) plays a significant role in the implementation of large IoT devices. The requirement for subsequent employment of power sources is eliminated by The efficient approach of Energy Harvesting and thereby providing a relatively close- perpetual working environment for the network. The structural concept of routing protocols that are designed for the IoT applications which are based on the wireless sensor has been transformed into "energy-harvesting-aware" from the concept of "energy-aware" because of the development in the Energy harvesting techniques. The main objective of the research work is to propose a routing protocol that is energy-harvesting-aware for the various network of IoT in case of acoustic sources of energy. A novel algorithm for routing called Autonomous Scheduling and Distributed Graph Routing (DDSR) has been developed and significantly improved by incorporating a new “energy back-off” factor. The proposed algorithm when integrated with various techniques of energy harvesting enhances the longevity of nodes, quality of service of a network under increased differential traffic, and factors influencing the accessibility of energy. The research work analyses the performance of the system for various constraints of energy harvesting. When compared to previous routing protocols the proposed algorithm achieves very good energy efficiency in the network of distributed IoT by fulfilling the requirements of QoS.

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Liu, Jain-Shing, and Chun-Hung Richard Lin. "Energy-efficiency clustering protocol in wireless sensor networks." Ad Hoc Networks 3, no. 3 (May 2005): 371–88. http://dx.doi.org/10.1016/j.adhoc.2003.09.012.

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Costa, Maice, and Anthony Ephremides. "Energy Efficiency Versus Performance in Cognitive Wireless Networks." IEEE Journal on Selected Areas in Communications 34, no. 5 (May 2016): 1336–47. http://dx.doi.org/10.1109/jsac.2016.2520219.

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Shahid, Muhammad Khalil, Filmon Debretsion, Aman Eyob, Irfan Ahmed, and Tarig Faisal. "Energy Efficiency in 5G Communications – Conventional to Machine Learning Approaches." Journal of Telecommunications and Information Technology 4 (December 30, 2020): 1–9. http://dx.doi.org/10.26636/jtit.2020.146820.

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Demand for wireless and mobile data is increasing along with development of virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (ER) applications. In order to handle ultra-high data exchange rates while offering low latency levels, fifth generation (5G) networks have been proposed. Energy efficiency is one of the key objectives of 5G networks. The notion is defined as the ratio of throughput and total power consumption, and is measured using the number of transmission bits per Joule. In this paper, we review state-of-the-art techniques ensuring good energy efficiency in 5G wireless networks. We cover the base-station on/off technique, simultaneous wireless information and power transfer, small cells, coexistence of long term evolution (LTE) and 5G, signal processing algorithms, and the latest machine learning techniques. Finally, a comparison of a few recent research papers focusing on energy-efficient hybrid beamforming designs in massive multiple-input multiple-output (MIMO) systems is presented. Results show that machine learningbased designs may replace best performing conventional techniques thanks to a reduced complexity machine learning encoder

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Zappone, Alessio, and Eduard Jorswieck. "Energy Efficiency in Wireless Networks via Fractional Programming Theory." Foundations and Trends® in Communications and Information Theory 11, no. 3-4 (2015): 185–396. http://dx.doi.org/10.1561/0100000088.

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Sadek, Ahmed K., Wei Yu, and K. J. Ray Liu. "On the energy efficiency of cooperative communications in wireless sensor networks." ACM Transactions on Sensor Networks 6, no. 1 (December 2009): 1–21. http://dx.doi.org/10.1145/1653760.1653765.

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Lorincz, Josip. "Energy-Efficient Wireless Cellular Communications through Network Resource Dynamic Adaptation." International Journal of Business Data Communications and Networking 9, no. 2 (April 2013): 11–26. http://dx.doi.org/10.4018/jbdcn.2013040102.

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Cellular networks represent one of the major energy consumers of communication networks and their contribution to the global carbon footprint and energy consumption continuously and rapidly increases. Improving energy efficiency of the cellular access networks become an important requirement and has recently gained considerable attention of the research community and operators. In this paper, improving cellular networks energy efficiency through dynamic adaptation of network resources is presented with foundations which justify practical realization of such approach. Paper gives insight into how the traffic pattern variations and transmitted power scaling influence on the instantaneous power consumption of the base stations. Also, impact of the base stations Tx power on two prominent energy efficiency metrics of the cellular access network is discussed. Results of a proposed optimization approach which is based on dynamic adaptation of the base stations on/off activity and the transmitted power in accordance with the spatial and temporal variations of traffic are presented. According to obtained results, dynamic adaptation of network resources can offer significant monthly energy savings on the level of complete cellular access network.

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Wang, Luyao, Kwan-Wu Chin, and Sieteng Soh. "Link Schedulers for Green Wireless Networks With Energy Sharing." IEEE Transactions on Green Communications and Networking 5, no. 3 (September 2021): 1580–93. http://dx.doi.org/10.1109/tgcn.2021.3081404.

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Rault, Tifenn, Abdelmadjid Bouabdallah, and Yacine Challal. "Energy efficiency in wireless sensor networks: A top-down survey." Computer Networks 67 (July 2014): 104–22. http://dx.doi.org/10.1016/j.comnet.2014.03.027.

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Yu, Yinpeng, Yuhuai Peng, Yejun Liu, Lei Guo, and Meng Song. "Survivable Routing Protocol for green wireless mesh networks based on energy efficiency." China Communications 11, no. 8 (August 2014): 117–24. http://dx.doi.org/10.1109/cc.2014.6911093.

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Chehri, Abdellah, and Hussein T. Mouftah. "Energy Efficiency Adaptation for Multihop Routing in Wireless Sensor Networks." Journal of Computer Networks and Communications 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/767920.

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Wireless sensor networks (WSNs) are considered as a suitable solution for long-time and large-scale outdoor environmental monitoring. However, an important feature that distinguishes the WSNs from traditional monitoring systems is their energy constraints. In fact, these nodes have often a limited and usually nonreplenishable power source. Therefore managing these limited resources is a key challenge. In this paper we use an optimization scheme based on adaptive modulation and power control for a green routing protocol. The optimization mechanism is subject to certain QoS requirements in terms of total end-to-end delay time and bit error rate. The simulation results show that the proposed algorithm can, theoretically, reduce the consumed energy of the sensor nodes almost to half.

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Mazumdar, Arka Prokash, Anandghan Waghmare, and Ashok Singh Sairam. "Modelling energy efficiency of OR protocols in wireless networks." International Journal of Ad Hoc and Ubiquitous Computing 16, no. 1 (2014): 42. http://dx.doi.org/10.1504/ijahuc.2014.062490.

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Islam, Kazi Yasin, Iftekhar Ahmad, Daryoush Habibi, and Adnan Waqar. "A survey on energy efficiency in underwater wireless communications." Journal of Network and Computer Applications 198 (February 2022): 103295. http://dx.doi.org/10.1016/j.jnca.2021.103295.

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Baianifar, Mahdi, S. Mohammad Razavizadeh, Hossein Akhlaghpasand, and Inkyu Lee. "Energy efficiency maximization in mmWave wireless networks with 3D beamforming." Journal of Communications and Networks 21, no. 2 (April 2019): 125–35. http://dx.doi.org/10.1109/jcn.2019.000011.

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Al Kabi, Amin. "Enhancement of Energy Harvesting Efficiency in Mobile Wireless Sensor Networks." WSEAS TRANSACTIONS ON COMMUNICATIONS 21 (May 19, 2022): 129–34. http://dx.doi.org/10.37394/23204.2022.21.18.

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Mobile wireless sensor networks suffer from the restricted availability of energy supplies. In this research work, a proposed method for extending the lifetime of energy-constrained mobile wireless sensor networks (MWSNs) is presented. This method is based on the fact that RF signal carries both information and energy at the same time. Hence, by increasing the efficiency of energy harvesting from radio frequency (RF) signals, the lifetime of the wireless network can be significantly extended. The Simultaneous Wireless Information and Power Transfer (SWIPT) technique enables harvesting of energy by relay nodes which in turn can be used for wireless data transmission. To enhance the lifetime of the mobile wireless network, the transmitted RF energy can be recycled at the receiver side. On the other hand, a balance between energy harvesting and wireless data transmission is required in to maximize the overall efficiency of the system. Particle Swarm Optimization (PSO) is employed to obtain the optimum resource allocation policy which maximizes the system energy efficiency. A cost function is framed for this purpose and PSO attains the maximum energy efficiency by improving the solution of the cost function at each iteration with respect to given constraints.

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Zheng, Kechen, Xiao-Yang Liu, Luoyi Fu, Xinbing Wang, and Yihua Zhu. "Energy Efficiency in Multihop Wireless Networks with Unreliable Links." IEEE Transactions on Network Science and Engineering 7, no. 1 (January 1, 2020): 576–88. http://dx.doi.org/10.1109/tnse.2018.2890430.

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Alsharif, Mohammed H., Rosdiadee Nordin, and Mahamod Ismail. "Survey of Green Radio Communications Networks: Techniques and Recent Advances." Journal of Computer Networks and Communications 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/453893.

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Energy efficiency in cellular networks has received significant attention from both academia and industry because of the importance of reducing the operational expenditures and maintaining the profitability of cellular networks, in addition to making these networks “greener.” Because the base station is the primary energy consumer in the network, efforts have been made to study base station energy consumption and to find ways to improve energy efficiency. In this paper, we present a brief review of the techniques that have been used recently to improve energy efficiency, such as energy-efficient power amplifier techniques, time-domain techniques, cell switching, management of the physical layer through multiple-input multiple-output (MIMO) management, heterogeneous network architectures based on Micro-Pico-Femtocells, cell zooming, and relay techniques. In addition, this paper discusses the advantages and disadvantages of each technique to contribute to a better understanding of each of the techniques and thereby offer clear insights to researchers about how to choose the best ways to reduce energy consumption in future green radio networks.

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Wenxing, Liao, Wu Muqing, and Wu Yuewei. "Design of multi-energy-space-based energy-efficient algorithm in novel software-defined wireless sensor networks." International Journal of Distributed Sensor Networks 13, no. 7 (July 2017): 155014771771811. http://dx.doi.org/10.1177/1550147717718113.

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Energy efficiency has always been a hot issue in wireless sensor networks. A lot of energy-efficient algorithms have been proposed to reduce energy consumption in traditional wireless sensor networks. With the emergence of software-defined networking, researchers have demonstrated the feasibility of software-defined networking over traditional wireless sensor networks. Thus, energy-efficient algorithms in software-defined wireless sensor networks have been studied. In this article, we propose an energy-efficient algorithm based on multi-energy-space in software-defined wireless sensor networks. First, we propose a novel architecture of software-defined wireless sensor networks according to current research on software-defined wireless sensor networks. Then, we introduce the concept of multi-energy-space which is based on the residual energy. Based on the novel architecture of software-defined wireless sensor networks and the concept of multi-energy-space, we give a detailed introduction of the main idea of our multi-energy-space-based energy-efficient algorithm. Simulation results show that our proposed algorithm performs better in energy consumption balance and network lifetime extension compared with the typical energy-efficient algorithms in traditional wireless sensor networks.

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Lu, Huibin, Baozhu Hu, Zhiyuan Ma, and Shuhuan Wen. "Reinforcement Learning Optimization for Energy-Efficient Cellular Networks with Coordinated Multipoint Communications." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/698797.

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Recently, there is an emerging trend of addressing “energy efficiency” aspect of wireless communications. And coordinated multipoint (CoMP) communication is a promising method to improve energy efficiency. However, since the downlink performance is also important for users, we should improve the energy efficiency as well as keeping a perfect downlink performance. This paper presents a control theoretical approach to study the energy efficiency and downlink performance issues in cooperative wireless cellular networks with CoMP communications. Specifically, to make the decisions for optimal base station grouping in energy-efficient transmissions in CoMP, we develop a Reinforcement Learning (RL) Algorithm. We apply theQ-learning of the RL Algorithm to get the optimal policy for base station grouping with introduction of variations at the beginning of theQ-learning to preventQfrom falling into local maximum points. Simulation results are provided to show the process and effectiveness of the proposed scheme.

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Journal articles on the topic 'Wireless Communications, Energy Efficiency, Green Networks'

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