Special Issue "Green Radio, Energy Harvesting, and Wireless-Powered Communications for Beyond-5G Wireless Systems"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electrical Power and Energy System".

Deadline for manuscript submissions: closed (10 October 2019).

Special Issue Editors

Prof. Bang Chul Jung
E-Mail Website
Guest Editor
Chungnam National University, Department of Electronics Engineering, Daejeon 34134, South Korea
Interests: Wireless Communications; Radio Resource Management; Statistical Signal Processing; Information Theory; Machine Learning; Radar Signal Processing
Prof. Won-Yong Shin
E-Mail Website
Guest Editor
Yonsei University, Department of Computational Science & Engineering, Seoul 03722, South Korea
Interests: Information Theory; Communications; Mobile Computing; Big Data Analytics; Social Network Analysis
Prof. Howon Lee
E-Mail Website
Guest Editor
1. University of California, San Diego, Qualcomm Institute, La Jolla, CA 92093, USA
2. Hankyong National University, Department of Electrical, Electronic and Control Engineering, Anseong, 17579, South Korea
Interests: Wireless Communications; Radio Resource Management; Clustering Algorithms; D2D Communications; 5G Vertical Services

Special Issue Information

Dear Colleagues,

Energy efficiency is considered one of the most important performance metrics for beyond-5G wireless communication systems, which are expected to support tremendous mobile data traffic from/to massive mobile devices including smartphones, various sensors, Internet-of-Things (IoT) devices, etc. Thus, advanced green radio techniques are being proposed to reduce the overall power consumption of wireless communication systems, including energy efficient transmission/reception design, medium access control, scheduling algorithms, network operation methods, etc. Energy harvesting wireless networks refer to wireless networks deploying energy harvesting devices, where various natural sources such as solar/indoor lightening, vibrational, thermal, biological, chemical, and electromagnetic sources can be utilized for energy harvesting. Many promising techniques are currently being proposed to improve the performance of energy harvesting wireless networks. In particular, wireless-powered communication techniques have recently been emerging as a promising energy harvesting technique from electromagnetic wireless signals. Simultaneously wireless information and power transfer (SWIPT) has also received much attention from both academia and industry.

The goal of this Special Issue is to disseminate the recent theoretical and practical results in green radio technologies, energy harvesting wireless networks, and wireless-powered communication techniques for beyond-5G wireless communication systems. Review papers on these topics are also welcome.

Potential topics include, but are not limited to, the following:

  • Green communications
  • Green radio techniques for 5G/beyond-5G wireless networks
  • Energy-efficient wireless communication techniques
  • Energy efficiency and spectrum efficiency trade-offs in wireless networks
  • Energy-efficient IoT networks
  • Wireless protocols for energy saving in wireless networks
  • Green computing and communication technologies
  • Green applications for wireless systems
  • Energy harvesting techniques for wireless networks
  • Energy harvesting wireless communications
  • Simultaneous wireless information and power transfer
  • Wireless-powered communication protocols
  • Wireless-powered IoT
  • Scheduling and resource management for wireless-powered networks
  • Green energy management systems
  • Smart grid

Prof. Bang Chul Jung
Prof. Won-Yong Shin
Prof. Howon Lee
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Green radio techniques
  • Energy-efficient wireless communications
  • Energy harvesting (EH) techniques
  • Energy harvesting wireless communications
  • Power transfer
  • Wireless-powered communication networks
  • Simultaneous wireless information and power transfer (SWIPT)
  • Energy management systems

Published Papers (9 papers)

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Research

Open AccessFeature PaperArticle
Countrywide Mobile Spectrum Sharing with Small Indoor Cells for Massive Spectral and Energy Efficiencies in 5G and Beyond Mobile Networks
Energies 2019, 12(20), 3825; https://doi.org/10.3390/en12203825 - 10 Oct 2019
Abstract
In this paper, we propose a technique to share the licensed spectrums of all mobile network operators (MNOs) of a country with in-building small cells per MNO by exploiting the external wall penetration loss of a building and introducing the time-domain eICIC technique. [...] Read more.
In this paper, we propose a technique to share the licensed spectrums of all mobile network operators (MNOs) of a country with in-building small cells per MNO by exploiting the external wall penetration loss of a building and introducing the time-domain eICIC technique. The proposed technique considers allocating the dedicated spectrum Bop per MNO only its to outdoor macro UEs, whereas the total spectrum of all MNOs of the country Bco to its small cells indoor per building such that technically any small indoor cell of an MNO can have access to Bco instead of merely Bop assigned only to the MNO itself. We develop an interference management strategy as well as an algorithm for the proposed technique. System-level capacity, spectral efficiency, and energy efficiency performance metrics are derived, and a generic model for energy efficiency is presented. An optimal amount of small indoor cell density in terms of the number of buildings L carrying these small cells per MNO to trade-off the spectral efficiency and the energy efficiency is derived. With the system-level numerical and simulation results, we define an optimal value of L for a dense deployment of small indoor cells of an MNO and show that the proposed spectrum sharing technique can achieve massive indoor capacity, spectral efficiency, and energy efficiency for the MNO. Finally, we demonstrate that the proposed spectrum sharing technique could meet both the spectral efficiency and the energy efficiency requirements for 5G mobile networks for numerous traffic arrival rates to small indoor cells per building of an MNO. Full article
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Open AccessArticle
Multi-User AF Relay Networks with Power Allocation and Transfer: A Joint Approach
Energies 2019, 12(16), 3157; https://doi.org/10.3390/en12163157 - 16 Aug 2019
Abstract
The Internet-of-Things (IoT) framework has been considered as an enabler of the smart world where all devices will be deployed with extra-sensory power in order to sense the world as well as communicate with other sensor nodes. As a result, smart devices require [...] Read more.
The Internet-of-Things (IoT) framework has been considered as an enabler of the smart world where all devices will be deployed with extra-sensory power in order to sense the world as well as communicate with other sensor nodes. As a result, smart devices require more energy. Therefore, energy harvesting (EH) and wireless power transfer (WPT) emerge as a remedy for relieving the battery limitations of wireless devices. In this work, we consider a multi-user amplify-and-forward (AF)-assisted network, wherein multiple source nodes communicate with destination nodes with the help of a relay node. All the source nodes and the relay node have the capability of EH. In addition, to cope with a single point of failure i.e., failure of the relay node due to the lack of transmit power, we consider the WPT from the source nodes to the relay node. For WPT, a dedicated energy control channel is utilized by the source nodes. To maximize the sum rate using a deadline, we adopt a joint approach of power allocation and WPT and formulate an optimization problem under the constraints of the battery as well as energy causality. The formulated problem is non-convex and intractable. In order to make the problem solvable, we utilize a successive convex approximation method. Furthermore, an iterative algorithm based on the dual decomposition technique is investigated to get the optimal power allocation and transfer. Numerical examples are used to illustrate the performance of the proposed iterative algorithm. Full article
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Open AccessArticle
An Energy-Efficient Cross-Layer Routing Protocol for Cognitive Radio Networks Using Apprenticeship Deep Reinforcement Learning
Energies 2019, 12(14), 2829; https://doi.org/10.3390/en12142829 - 22 Jul 2019
Abstract
Deep reinforcement learning (DRL) has been successfully used for the joint routing and resource management in large-scale cognitive radio networks. However, it needs lots of interactions with the environment through trial and error, which results in large energy consumption and transmission delay. In [...] Read more.
Deep reinforcement learning (DRL) has been successfully used for the joint routing and resource management in large-scale cognitive radio networks. However, it needs lots of interactions with the environment through trial and error, which results in large energy consumption and transmission delay. In this paper, an apprenticeship learning scheme is proposed for the energy-efficient cross-layer routing design. Firstly, to guarantee energy efficiency and compress huge action space, a novel concept called dynamic adjustment rating is introduced, which regulates transmit power efficiently with multi-level transition mechanism. On top of this, the Prioritized Memories Deep Q-learning from Demonstrations (PM-DQfD) is presented to speed up the convergence and reduce the memory occupation. Then the PM-DQfD is applied to the cross-layer routing design for power efficiency improvement and routing latency reduction. Simulation results confirm that the proposed method achieves higher energy efficiency, shorter routing latency and larger packet delivery ratio compared to traditional algorithms such as Cognitive Radio Q-routing (CRQ-routing), Prioritized Memories Deep Q-Network (PM-DQN), and Conjecture Based Multi-agent Q-learning Scheme (CBMQ). Full article
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Open AccessArticle
Realization of Licensed/Unlicensed Spectrum Sharing Using eICIC in Indoor Small Cells for High Spectral and Energy Efficiencies of 5G Networks
Energies 2019, 12(14), 2828; https://doi.org/10.3390/en12142828 - 22 Jul 2019
Cited by 1
Abstract
In this paper, we show how to realize numerous spectrum licensing policies by means of time-domain enhanced inter-cell interference coordination (eICIC) technique to share both the licensed and unlicensed spectrums with small cells in order to address the increasing demand of capacity, spectral [...] Read more.
In this paper, we show how to realize numerous spectrum licensing policies by means of time-domain enhanced inter-cell interference coordination (eICIC) technique to share both the licensed and unlicensed spectrums with small cells in order to address the increasing demand of capacity, spectral efficiency, and energy efficiency of future mobile networks. Small cells are deployed only in 3-dimensional (3D) buildings within a macrocell coverage of a mobile network operator (MNO). We exploit the external wall penetration loss of each building to realize traditional dedicated access, co-primary shared access (CoPSA), and licensed shared access (LSA) techniques for the licensed spectrum access, whereas, for the unlicensed spectrum access, the licensed assisted access (LAA) technique operating in the 60 GHz unlicensed band is realized. We consider that small cells are facilitated with dual-band, and derive the average capacity, spectral efficiency, and energy efficiency metrics for each technique. We perform extensive evaluation of various performance metrics and show that LAA outperforms considerably all other techniques concerning particularly spectral and energy efficiencies. Finally, we define an optimal density of small cells satisfying both the spectral efficiency and energy efficiency requirements for the fifth-generation (5G) mobile networks. Full article
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Open AccessArticle
Exact Performance Analysis of Amplify-and-Forward Bidirectional Relaying over Nakagami-m Fading Channels with Arbitrary Parameters
Energies 2019, 12(7), 1277; https://doi.org/10.3390/en12071277 - 03 Apr 2019
Abstract
The exact performance of amplify-and-forward (AF) bidirectional relay systems is studied in generalized and versatile Nakagami-m fading channels, where the parameter m is an arbitrary positive number. We consider three relaying modes: two, three, and four time slot bidirectional relaying. Closed form [...] Read more.
The exact performance of amplify-and-forward (AF) bidirectional relay systems is studied in generalized and versatile Nakagami-m fading channels, where the parameter m is an arbitrary positive number. We consider three relaying modes: two, three, and four time slot bidirectional relaying. Closed form expressions of the moment generating function (MGF), higher order moments of signal-to-noise ratio (SNR), ergodic capacity, and average signal error probability (SEP) are derived, which are different from previous works. The obtained expressions are very concise, easy to calculate, and evaluated instantaneously without a complex summation operation, in contrast to the nested multifold numerical integrals and truncated infinite series expansions used in previous work, which lead to computational inefficiency, especially when the fading parameter m increases. Simulation results corroborate the correctness and tightness of the theoretical analysis. Full article
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Open AccessArticle
Effect of Prediction Error of Machine Learning Schemes on Photovoltaic Power Trading Based on Energy Storage Systems
Energies 2019, 12(7), 1249; https://doi.org/10.3390/en12071249 - 01 Apr 2019
Cited by 1
Abstract
Photovoltaic (PV) output power inherently exhibits an intermittent property depending on the variation of weather conditions. Since PV power producers may be charged to large penalties in forthcoming energy markets due to the uncertainty of PV power generation, they need a more accurate [...] Read more.
Photovoltaic (PV) output power inherently exhibits an intermittent property depending on the variation of weather conditions. Since PV power producers may be charged to large penalties in forthcoming energy markets due to the uncertainty of PV power generation, they need a more accurate PV power prediction scheme in energy market operation. In this paper, we characterize the effect of PV power prediction errors on energy storage system (ESS)-based PV power trading in energy markets. First, we analyze the prediction accuracy of two machine learning (ML) schemes for the PV output power and estimate their error distributions. We propose an efficient ESS management scheme for charging and discharging operation of ESS in order to reduce the deviations between the day-ahead (DA) and real-time (RT) dispatch in energy markets. In addition, we estimate the capacity of ESSs, which can absorb the prediction errors and then compare the PV power producer’s profit according to ML-based prediction schemes with/without ESS. In case of ML-based prediction schemes with ESS, the ANN and SVM schemes yield a decrease in the deviation penalty by up to 87% and 74%, respectively, compared with the profit of those schemes without ESS. Full article
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Open AccessArticle
Energy-Efficient Multicast Precoding for Massive MIMO Transmission with Statistical CSI
Energies 2018, 11(11), 3175; https://doi.org/10.3390/en11113175 - 15 Nov 2018
Cited by 4
Abstract
In this paper, we investigate energy-efficient multicast precoding for massive multiple-input multiple-output (MIMO) transmission. In contrast with most previous work, where instantaneous channel state information (CSI) is exploited to facilitate energy-efficient wireless transmission design, we assume that the base station can only exploit [...] Read more.
In this paper, we investigate energy-efficient multicast precoding for massive multiple-input multiple-output (MIMO) transmission. In contrast with most previous work, where instantaneous channel state information (CSI) is exploited to facilitate energy-efficient wireless transmission design, we assume that the base station can only exploit statistical CSI of the user terminals for downlink multicast precoding. First, in terms of maximizing the system energy efficiency, the eigenvectors of the optimal energy-efficient multicast transmit covariance matrix are identified in closed form, which indicates that optimal energy-efficient multicast precoding should be performed in the beam domain in massive MIMO. Then, the large-dimensional matrix-valued precoding design is simplified into an energy-efficient power allocation problem in the beam domain with significantly reduced optimization variables. Using Dinkelbach’s transform, we further propose a sequential beam domain power allocation algorithm which is guaranteed to converge to the global optimum. In addition, we use the large-dimensional random matrix theory to derive the deterministic equivalent of the objective to reduce the computational complexity involved in sample averaging. We present numerical results to illustrate the near-optimal performance of our proposed energy-efficient multicast precoding for massive MIMO. Full article
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Open AccessArticle
Energy-Efficient Path Selection Using SNR Correlation for Wireless Multi-Hop Cooperative Communications
Energies 2018, 11(11), 3004; https://doi.org/10.3390/en11113004 - 01 Nov 2018
Abstract
In this paper, we consider partial path selection (PPS) for a multi-hop decode-and-forward cooperative system with limited channel state information (CSI) feedback, where the PPS utilizes local CSI only for a subset of hops on each of all independent paths between a source [...] Read more.
In this paper, we consider partial path selection (PPS) for a multi-hop decode-and-forward cooperative system with limited channel state information (CSI) feedback, where the PPS utilizes local CSI only for a subset of hops on each of all independent paths between a source and a destination to reduce the energy consumption for CSI feedback. To enhance the end-to-end performance of the PPS, we propose a novel PPS method with local CSI chosen by the correlation between the end-to-end signal-to-noise ratios (SNRs) based on global and local CSI under Nakagami-m fading channels. For each path, we pick a subset of hops to report CSI with the highest correlation for a given CSI feedback overhead requirement, which can achieve the similar end-to-end outage probability to the best path selection with global CSI. We provide an exact and closed-form expression for the SNR correlation coefficient and present an impact of the SNR correlation on the end-to-end outage probability. Full article
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Open AccessArticle
Multi-Dimensional Sparse-Coded Ambient Backscatter Communication for Massive IoT Networks
Energies 2018, 11(10), 2855; https://doi.org/10.3390/en11102855 - 22 Oct 2018
Abstract
In this paper, we propose a multi-dimensional sparse-coded ambient backscatter communication (MSC-AmBC) system for long-range and high-rate massive Internet of things (IoT) networks. We utilize the characteristics of the ambient sources employing orthogonal frequency division multiplexing (OFDM) modulation to mitigate strong direct-link interference [...] Read more.
In this paper, we propose a multi-dimensional sparse-coded ambient backscatter communication (MSC-AmBC) system for long-range and high-rate massive Internet of things (IoT) networks. We utilize the characteristics of the ambient sources employing orthogonal frequency division multiplexing (OFDM) modulation to mitigate strong direct-link interference and improve signal detection of AmBC at the reader. Also, utilization of the sparsity originated from the duty-cycling operation of batteryless RF tags is proposed to increase the dimension of signal space of backscatter signals to achieve either diversity or multiplexing gains in AmBC. We propose optimal constellation mapping and reflection coefficient projection and expansion methods to effectively construct multi-dimensional constellation for high-order backscatter modulation while guaranteeing sufficient energy harvesting opportunities at these tags. Simulation results confirm the feasibility of the long-range and high-rate AmBC in massive IoT networks where a huge number of active ambient sources and passive RF tags coexist. Full article
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