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Advanced Technologies on Green Radio Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 51403

Special Issue Editors


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Guest Editor
Department of Electrical and Electronic Engineering, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand
Interests: machine learning techniques applied to software defined vehicular networks; wireless/mobile communications systems including radio resource management, multiple access, MANETs/VANETs, green radio networks, and 5G-V2X networks
Special Issues, Collections and Topics in MDPI journals
Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1010, New Zealand
Interests: wireless networking; wireless communications; networking protocols; radio frequency integrated circuits; wireless sensor networks; video streaming; system optimization; evolutionary computing
Special Issues, Collections and Topics in MDPI journals

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Co-Guest Editor
Robotics Lab, School of Mathematics, Computer Science and Engineering, Liverpool Hope University, Hope Park, Liverpool L16 9JD, UK
Interests: robotics; life-like systems; wearable sensors
Special Issues, Collections and Topics in MDPI journals

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Co-Guest Editor
Electrical and Computer Engineering, Memorial University of Newfoundland, St. John's, Newfoundland, A1B 3X5, Canada

Special Issue Information

Dear Colleagues,

The amount of mobile data traffic has experienced a compound annual growth rate (CAGR) of 53% since 2015, and it is expected to reach 30.6 exabytes (EB) by 2020. This fast growth of data size is supported by the ever-increasing number of mobile subscribers. It is anticipated that a widespread use of complex spectrum efficient techniques will lead to extremely high power consumption. Currently consuming 3% of world-wide energy and causing 2% of global CO2 emissions, Information and Communication Technology (ICT) industries are facing an increase of associated energy consumption of 16–20% per year. Therefore, the increasing share of wireless systems in the global energy and CO2 footprint has now created an urgent need for a short-term emphasis on the energy efficiency of telecommunication networks.

While there is a great deal of leeway for energy efficient and low power solutions, today’s communication architectures are still only, to a very small degree, determined by energy consumption considerations because this topic is not yet a focus of practical work, and thus far, no solid research work has given support for any technique’s capability of reducing overall system power consumption. This Special Issue will put together high-quality research articles on recent advances in the theory and application of technologies in Green Radio Networks (GRNs) to support green communications/networks/IoT and to serve as valuable references and directions for researchers in this field, from industry as well as academia.

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

  • Current status of power consumption issue in wireless communications
  • Trends and challenges of power consumption in wireless communications
  • Energy efficient metrics and measurements
  • Energy efficient radio access architectures
  • Enabling radio networking techniques
  • Green technologies for 5G
  • Transmission power control
  • Optimal transmit power with given partners
  • Adapting transmit power to packet size
  • Adapting transmit power to channel state
  • ON/OFF switching of network interface and processor
  • Energy efficient digital signal processing
  • Lower power devices and energy efficient base station hardware design
  • Green radio IC design
  • Energy applications for green radio
  • Green communications
  • Energy-efficient M2M wireless networking
  • Cooling systems
  • Power supply system with alternative energy
  • Test-Bed, experimental results, and hardware prototypes
  • Green computing and communication technologies
  • Green applications for wireless system

Prof. Dr. Peter Chong
Dr. Xuejun Li
Dr. Emanuele Lindo Secco
Prof. Dr. Cheng Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sensors 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 2600 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 Networks
  • Green IoT
  • Wireless Networking
  • Next Generation Mobile Networks
  • Wireless Sensor Networks

Published Papers (9 papers)

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Research

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13 pages, 22819 KiB  
Article
Sensor Fusion and State Estimation of IoT Enabled Wind Energy Conversion System
by Md. Noor-A-Rahim, M. O. Khyam, Xinde Li and Dirk Pesch
Sensors 2019, 19(7), 1566; https://doi.org/10.3390/s19071566 - 01 Apr 2019
Cited by 25 | Viewed by 4123
Abstract
The use of renewable energy has increased dramatically over the past couple of decades. Wind farms, consisting of wind turbines, play a vital role in the generation of renewable energy. For monitoring and maintenance purposes, a wind turbine has a variety of sensors [...] Read more.
The use of renewable energy has increased dramatically over the past couple of decades. Wind farms, consisting of wind turbines, play a vital role in the generation of renewable energy. For monitoring and maintenance purposes, a wind turbine has a variety of sensors to measure the state of the turbine. Sensor measurements are transmitted to a control center, which is located away from the wind farm, for monitoring and maintenance purposes. It is therefore desirable to ensure reliable wireless communication between the wind turbines and the control center while integrating the observations from different sensors. In this paper, we propose an IoT based communication framework for the purpose of reliable communication between wind turbines and control center. The communication framework is based on repeat-accumulate coded communication to enhance reliability. A fusion algorithm is proposed to exploit the observations from multiple sensors while taking into consideration the unpredictable nature of the wireless channel. The numerical results show that the proposed scheme can closely predict the state of a wind turbine. We also show that the proposed scheme significantly outperforms traditional estimation schemes. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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19 pages, 1867 KiB  
Article
Multi-Server Multi-User Multi-Task Computation Offloading for Mobile Edge Computing Networks
by Liang Huang, Xu Feng, Luxin Zhang, Liping Qian and Yuan Wu
Sensors 2019, 19(6), 1446; https://doi.org/10.3390/s19061446 - 24 Mar 2019
Cited by 92 | Viewed by 6874
Abstract
This paper studies mobile edge computing (MEC) networks where multiple wireless devices (WDs) offload their computation tasks to multiple edge servers and one cloud server. Considering different real-time computation tasks at different WDs, every task is decided to be processed locally at its [...] Read more.
This paper studies mobile edge computing (MEC) networks where multiple wireless devices (WDs) offload their computation tasks to multiple edge servers and one cloud server. Considering different real-time computation tasks at different WDs, every task is decided to be processed locally at its WD or to be offloaded to and processed at one of the edge servers or the cloud server. In this paper, we investigate low-complexity computation offloading policies to guarantee quality of service of the MEC network and to minimize WDs’ energy consumption. Specifically, both a linear programing relaxation-based (LR-based) algorithm and a distributed deep learning-based offloading (DDLO) algorithm are independently studied for MEC networks. We further propose a heterogeneous DDLO to achieve better convergence performance than DDLO. Extensive numerical results show that the DDLO algorithms guarantee better performance than the LR-based algorithm. Furthermore, the DDLO algorithm generates an offloading decision in less than 1 millisecond, which is several orders faster than the LR-based algorithm. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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21 pages, 2925 KiB  
Article
Energy-Efficient Nonuniform Content Edge Pre-Caching to Improve Quality of Service in Fog Radio Access Networks
by Yi Cen, Yigang Cen, Ke Wang and Jingcong Li
Sensors 2019, 19(6), 1422; https://doi.org/10.3390/s19061422 - 22 Mar 2019
Cited by 5 | Viewed by 2811
Abstract
The fog radio access network (F-RAN) equipped with enhanced remote radio heads (eRRHs), which can pre-store some requested files in the edge cache and support mobile edge computing (MEC). To guarantee the quality-of-service (QoS) and energy efficiency of F-RAN, a proper content caching [...] Read more.
The fog radio access network (F-RAN) equipped with enhanced remote radio heads (eRRHs), which can pre-store some requested files in the edge cache and support mobile edge computing (MEC). To guarantee the quality-of-service (QoS) and energy efficiency of F-RAN, a proper content caching strategy is necessary to avoid coarse content storing locally in the cache or frequent fetching from a centralized baseband signal processing unit (BBU) pool via backhauls. In this paper we investigate the relationships among eRRH/terminal activities and content requesting in F-RANs, and propose an edge content caching strategy for eRRHs by mining out mobile network behavior information. Especially, to attain the inference for appropriate content caching, we establish a pre-mapping containing content preference information and geographical influence by an efficient non-uniformed accelerated matrix completion algorithm. The energy consumption analysis is given in order to discuss the energy saving properties of the proposed edge content caching strategy. Simulation results demonstrate our theoretical analysis on the inference validity of the pre-mapping construction method in static and dynamic cases, and show the energy efficiency achieved by the proposed edge content pre-caching strategy. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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16 pages, 4261 KiB  
Article
Design and Analysis of a Continuously Tunable Low Noise Amplifier for Software Defined Radio
by Aayush Aneja and Xue Jun Li
Sensors 2019, 19(6), 1273; https://doi.org/10.3390/s19061273 - 13 Mar 2019
Cited by 9 | Viewed by 3540
Abstract
This paper presents the design and analysis of a continuously tunable low noise amplifier (LNA) with an operating frequency from 2.2 GHz to 2.8 GHz. Continuous tuning is achieved through a radio frequency impedance transformer network in the input matching stage. The proposed [...] Read more.
This paper presents the design and analysis of a continuously tunable low noise amplifier (LNA) with an operating frequency from 2.2 GHz to 2.8 GHz. Continuous tuning is achieved through a radio frequency impedance transformer network in the input matching stage. The proposed circuit consists of four stages, namely transformer stage, tuning stage, phase shifter and gain stage. Frequency tuning is controlled by varying output current through bias voltage of tuning stage. The circuit includes an active phase shifter in the feedback path of amplifier to shift the phase of the amplified signal. Phase shift is required to further achieve tunability through transformer. The LNA achieves a maximum simulated gain of 18 dB. The LNA attains a perfect impedance match across the tuning range with stable operation. In addition, it achieves a minimum noise figure of 1.4 dB. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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19 pages, 2432 KiB  
Article
Adaptive Dynamic Programming-Based Multi-Sensor Scheduling for Collaborative Target Tracking in Energy Harvesting Wireless Sensor Networks
by Fen Liu, Wendong Xiao, Shuai Chen and Chengpeng Jiang
Sensors 2018, 18(12), 4090; https://doi.org/10.3390/s18124090 - 22 Nov 2018
Cited by 5 | Viewed by 4088
Abstract
Collaborative target tracking is one of the most important applications of wireless sensor networks (WSNs), in which the network must rely on sensor scheduling to balance the tracking accuracy and energy consumption, due to the limited network resources for sensing, communication, and computation. [...] Read more.
Collaborative target tracking is one of the most important applications of wireless sensor networks (WSNs), in which the network must rely on sensor scheduling to balance the tracking accuracy and energy consumption, due to the limited network resources for sensing, communication, and computation. With the recent development of energy acquisition technologies, the building of WSNs based on energy harvesting has become possible to overcome the limitation of battery energy in WSNs, where theoretically the lifetime of the network could be extended to infinite. However, energy-harvesting WSNs pose new technical challenges for collaborative target tracking on how to schedule sensors over the infinite horizon under the restriction on limited sensor energy harvesting capabilities. In this paper, we propose a novel adaptive dynamic programming (ADP)-based multi-sensor scheduling algorithm (ADP-MSS) for collaborative target tracking for energy-harvesting WSNs. ADP-MSS can schedule multiple sensors for each time step over an infinite horizon to achieve high tracking accuracy, based on the extended Kalman filter (EKF) for target state prediction and estimation. Theoretical analysis shows the optimality of ADP-MSS, and simulation results demonstrate its superior tracking accuracy compared with an ADP-based single-sensor scheduling scheme and a simulated-annealing based multi-sensor scheduling scheme. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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14 pages, 345 KiB  
Article
Optimal Time Assignment Policy for Maximizing Throughput in Cognitive Sensor Network with Energy Harvesting
by Hao Wu and Yong Chen
Sensors 2018, 18(8), 2540; https://doi.org/10.3390/s18082540 - 03 Aug 2018
Cited by 2 | Viewed by 2628
Abstract
A cognitive sensor network with energy harvesting (EH-CSN) is a promising paradigm to address the issues both in spectrum efficiency and in energy efficiency. The cognitive sensors (CSs) equipped with energy harvesting devices are assumed to operate in a harvesting-sensing-transmission mode and permitted [...] Read more.
A cognitive sensor network with energy harvesting (EH-CSN) is a promising paradigm to address the issues both in spectrum efficiency and in energy efficiency. The cognitive sensors (CSs) equipped with energy harvesting devices are assumed to operate in a harvesting-sensing-transmission mode and permitted to access the idle licensed frequency bands without causing any harmful jamming to the primary user. By identifying the time fractions of harvesting, sensing, and transmission, we can discuss some design considerations for the EH-CSN. In the meantime, considering the possibility that the primary user may reoccupy the idle channel during the CS’s data transmission duration, we formulate an optimization problem to maximize the average throughput of EH-CSN under a collision constraint and an energy constraint. After deriving the lower and upper bounds of the time fraction for energy harvesting, the uniqueness and existence of the optimal time fraction set have been proved. Finally, our theoretical analysis is also verified through numerical simulations. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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13 pages, 668 KiB  
Article
Directional Paging for 5G Communications Based on Partitioned User ID
by Mamta Agiwal and Hu Jin
Sensors 2018, 18(6), 1845; https://doi.org/10.3390/s18061845 - 05 Jun 2018
Cited by 11 | Viewed by 5622
Abstract
The millimeter-wave (mmWave) spectrum is one of the important propositions of 5G mobile networks due to its ability to accommodate massive traffic demands and an ever-increasing number of wireless devices. The beam-formed directional technique overcomes the propagation and path loss challenges of mmWave [...] Read more.
The millimeter-wave (mmWave) spectrum is one of the important propositions of 5G mobile networks due to its ability to accommodate massive traffic demands and an ever-increasing number of wireless devices. The beam-formed directional technique overcomes the propagation and path loss challenges of mmWave high frequencies. Though the directional convergence is expected to unleash new possibilities, it cannot be implemented with conventional power-saving solutions optimized over omnidirectional communications. Paging broadcast, for users in Idle Discontinuous Reception (IDRX) mode for energy saving, is one such necessary function in a wireless communication that needs modification in highly directional beam-based transmissions. Due to the limited spatial coverage of directional beams, the paging transmission takes place over multiple beams, which increases the paging resource overheads of the network substantially. In this article, we present a novel paging mechanism for the directional air interface in mmWave-enabled 5G communications. Numerical analysis of the proposed Partitioned UE ID-based Directional Paging (PIDP) mechanism reduces the paging resource overheads of the network, resulting in a 15 % gain in power savings compared to directional paging transmission without the UE ID partition. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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21 pages, 1504 KiB  
Article
Joint Cache Content Placement and Task Offloading in C-RAN Enabled by Multi-Layer MEC
by Haibo Mei, Kezhi Wang and Kun Yang
Sensors 2018, 18(6), 1826; https://doi.org/10.3390/s18061826 - 05 Jun 2018
Cited by 14 | Viewed by 3675
Abstract
In this paper, we work on a Cache and Multi-layer MEC enabled C-RAN (CMM-CRAN) to handle various user tasks with minimized latency and energy cost. We intend to solve two particular problems of CMM-CRAN. First, because CMM-CRAN has to maximally cache the most [...] Read more.
In this paper, we work on a Cache and Multi-layer MEC enabled C-RAN (CMM-CRAN) to handle various user tasks with minimized latency and energy cost. We intend to solve two particular problems of CMM-CRAN. First, because CMM-CRAN has to maximally cache the most frequently requested data from Service Provide Server (SPS) to Remote Radio Head (RRH) and later offered to proximity mobile users, the cache content placement from SPSs to RRHs becomes a many-to-many matching problem with peer effects. Second, because of multi-layer MEC, a user task has to be dynamically controlled to be offloaded to the best fit cloud, i.e., either local MEC or remote MEC, to get served. This dynamic task offloading is a Multi-Dimension Multiple-Choice Knapsack (MMCK) problem. To solve these two problems, we provide a Joint Cache content placement and task Offloading Solution (JCOS) to CMM-CRAN that utilizes Proportional Fairness (PF) as the user scheduling policy. JCOS applies a Gale-Shaply (GS) method to work out the cache content placement, and a Population Evolution (PE) game theory coupled with a use of Analytic Hierarchy Process(AHP) to work out the dynamic user task offloading. According to the simulation results, CMM-CRAN with JCOS is proved to be able to provide highly desired low-latency communication and computation services with decreased energy cost to mobile users. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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Review

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22 pages, 812 KiB  
Review
Visible Light Communication: A System Perspective—Overview and Challenges
by Saeed Ur Rehman, Shakir Ullah, Peter Han Joo Chong, Sira Yongchareon and Dan Komosny
Sensors 2019, 19(5), 1153; https://doi.org/10.3390/s19051153 - 07 Mar 2019
Cited by 166 | Viewed by 16933
Abstract
Visible light communication (VLC) is a new paradigm that could revolutionise the future of wireless communication. In VLC, information is transmitted through modulating the visible light spectrum (400–700 nm) that is used for illumination. Analytical and experimental work has shown the potential of [...] Read more.
Visible light communication (VLC) is a new paradigm that could revolutionise the future of wireless communication. In VLC, information is transmitted through modulating the visible light spectrum (400–700 nm) that is used for illumination. Analytical and experimental work has shown the potential of VLC to provide high-speed data communication with the added advantage of improved energy efficiency and communication security/privacy. VLC is still in the early phase of research. There are fewer review articles published on this topic mostly addressing the physical layer research. Unlike other reviews, this article gives a system prespective of VLC along with the survey on existing literature and potential challenges toward the implementation and integration of VLC. Full article
(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)
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