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IEEE Transactions on Green Communications and Networking
Number of Followers: 1  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Online) 2473-2400
Published by IEEE Homepage  [228 journals]
  • IEEE Transactions on Wireless Communications
    • Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • IEEE Communications Society Information
    • Abstract: Provides a listing of current committee members and society officers.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Erasure Coding for Ultra-Low Power Wireless Networks
    • Authors: Jalaluddin Qureshi;Rizwan Ullah Khan;Chuan Heng Foh;Periklis Chatzimisios;
      Pages: 866 - 875
      Abstract: In this paper, we study erasure coding for ultra-low power wireless networks with power consumption in order of milliwatts. We propose sparse parallel concatenated coding (SPCC) scheme, in which we optimize sparsity and ratio of coded packets over GF(2) (i.e., Galois field of size two) and larger field size such as GF(32) for different values of ${k}$ so that the total energy cost of the network is minimized. While high sparsity decreases energy cost of encoding, it comes at the tradeoff cost of high reception redundancy. The use of GF(2) packets minimizes the computational cost of encoding and decoding, while the use of small fraction of packets over GF(32) minimizes reception redundancies. Testbed implementation shows that SPCC energy gain increases with increasing packet generation size ${k}$ . We show that for the case where ${k}~leq $ 40, SPCC reduces energy cost by up to 100% compared with the next best performing coding scheme.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Energy-Efficient Wireless Powered Secure Transmission With Cooperative
           Jamming for Public Transportation
    • Authors: Linqing Gui;Bo He;Xiaobo Zhou;Chunhua Yu;Feng Shu;Jun Li;
      Pages: 876 - 885
      Abstract: In this paper, wireless power transfer and cooperative jamming (CJ) are combined to enhance physical security in public transportation networks. First, a new secure system model with both fixed and mobile jammers is proposed to guarantee secrecy in the worst-case scenario. All jammers are endowed with energy harvesting (EH) capability. Following this, two CJ-based schemes, namely, beamforming-CJ-SR-maximization (B-CJ-SRM) and beamforming-CJ-transmit-power-minimization (B-CJ-TPM), are proposed, where SRM and TPM are short for secrecy rate maximization and transmit power minimization, respectively. They, respectively, maximize the secrecy rate (SR) with transmit power constraint and minimize the transmit power of the BS with SR constraint, by optimizing beamforming vector and artificial noise covariance matrix. To further reduce the complexity of our proposed optimal schemes, their low-complexity (LC) versions, called LC-B-CJ-SRM and LC-B-CJ-TPM are developed. Simulation results show that our proposed schemes, B-CJ-SRM and B-CJ-TPM, achieve significant SR performance improvement over existing zero-forcing and QoSD methods. Additionally, the SR performance of the proposed LC schemes is close to those of their original versions.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Dynamic RF Chain Selection for Energy Efficient and Low Complexity Hybrid
           Beamforming in Millimeter Wave MIMO Systems
    • Authors: Aryan Kaushik;John Thompson;Evangelos Vlachos;Christos Tsinos;Symeon Chatzinotas;
      Pages: 886 - 900
      Abstract: This paper proposes a novel architecture with a framework that dynamically activates the optimal number of radio frequency (RF) chains used to implement hybrid beamforming in a millimeter wave (mmWave) multiple-input and multiple-output (MIMO) system. We use fractional programming to solve an energy efficiency maximization problem and exploit the Dinkelbach method (DM)-based framework to optimize the number of active RF chains and data streams. This solution is updated dynamically based on the current channel conditions, where the analog/digital (A/D) hybrid precoder and combiner matrices at the transmitter and the receiver, respectively, are designed using a codebook-based fast approximation solution called gradient pursuit (GP). The GP algorithm shows less run time and complexity while compared to the state-of-the-art orthogonal matching pursuit (OMP) solution. The energy and spectral efficiency performance of the proposed framework is compared with the existing state-of-the-art solutions, such as the brute force (BF), the digital beamformer, and the analog beamformer. The codebook-free approaches to design the precoders and combiners, such as alternating direction method of multipliers (ADMMs) and singular value decomposition (SVD)-based solution are also shown to be incorporated into the proposed framework to achieve better energy efficiency performance.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Minimum Cost Design of Cellular Networks in Rural Areas With UAVs, Optical
           Rings, Solar Panels, and Batteries
    • Authors: Luca Chiaraviglio;Lavinia Amorosi;Nicola Blefari-Melazzi;Paolo Dell’Olmo;Antonio Lo Mastro;Carlos Natalino;Paolo Monti;
      Pages: 901 - 918
      Abstract: Bringing the cellular connectivity in rural zones is a big challenge, due to the large installation costs that are incurred when a legacy cellular network based on fixed Base Stations (BSs) is deployed. To tackle this aspect, we consider an alternative architecture composed of UAV-based BSs to provide cellular coverage, ground sites to connect the UAVs with the rest of the network, Solar Panels (SPs) and batteries to recharge the UAVs and to power the ground sites, and a ring of optical fiber links to connect the installed sites. We then target the minimization of the installation costs for the considered UAV-based cellular architecture, by taking into account the constraints of UAVs coverage, SPs energy consumption, levels of the batteries and the deployment of the optical ring. After providing the problem formulation, we derive an innovative methodology to ensure that a single ring of installed optical fibers is deployed. Moreover, we propose a new algorithm, called DIARIZE, to practically tackle the problem. Our results, obtained over a set of representative rural scenarios, show that DIARIZE performs very close to the optimal solution, and in general outperforms a reference design based on fixed BSs.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • PoM: Power-Efficient Multi-View Video Streaming Over Multi-Antenna
           Wireless Systems
    • Authors: Xu Zhang;Zhe Chen;Yuedong Xu;Yu Zhu;Xin Wang;
      Pages: 919 - 932
      Abstract: Multi-view video streaming is becoming more popular, with increased potential for immersive applications. However, it poses a challenge in terms of energy consumption on the transmission devices with limited battery power due to the vast traffic volume. Previous literature has considered efficient video transmission but not exploited the full potential of joint design of 3D video coding and MIMO physical layer. In this paper, we present the first study on power consumption minimization for multi-view video streaming with a quality guarantee in 802.11 MIMO-OFDM systems. We propose an efficient algorithm to perform antenna assignment and transmission power allocation, by exploiting both the source coding characteristics of MVC and channel diversity of multiple antennas. A proof-of-concept system, namely PoM, is designed on the software-defined radio platform and is evaluated in realistic indoor environments. To the best of our knowledge, this is the first practical system for energy-efficient multi-view video streaming. Experimental results show that PoM can significantly save energy in the transmission by 88% ~ 26% on average for the PSNR requirement ranging from 35dB to 45dB, and 85% ~ 12% for SSIM from 0.80 to 0.95.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Multi-Objective Optimization of User Association in HetNets With Hybrid
           Power Supply
    • Authors: Liangrui Tang;Hailin Hu;
      Pages: 933 - 941
      Abstract: In this paper, we focus on proposing an appropriate user association method to improve the performance of HetNets supplied with hybrid energy sources (on-grid power and renewable energy). We first describe traffic and energy models, and then formulate the user association problem as a multi-objective optimization problem to minimize the average waiting delay of users and on-grid power consumption. Then we reformulate the multi-objective and integer optimization problem to single-objective convex optimization problem by using weight sum and variable substitution method. After that, an iterative algorithm is proposed for the user association problem and can be proved to converge to the global optimal solution. Simulation results show that the proposed algorithm in this paper can achieve different traffic load distributions by using different weight coefficients. In addition, the proposed algorithm has better performance in the average waiting delay of users and on-grid power consumption compared with traditional maxSINR user association algorithm. Finally, simulation results show the performance of the network can be adjusted by the renewable energy output power of BSs in the network.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • UAVs to the Rescue: Prolonging the Lifetime of Wireless Devices Under
           Disaster Situations
    • Authors: Hazim Shakhatreh;Abdallah Khreishah;Bo Ji;
      Pages: 942 - 954
      Abstract: Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider downlink scenarios from an aerial base station to ground users. In this paper, we consider an uplink scenario under disaster situations (such as earthquakes or floods), when cellular networks are down. We formulate the placement problem of UAVs, where the objective is to determine the locations of a set of UAVs that maximize the time duration of uplink transmission until the first wireless device runs out of energy. We prove that this problem is NP-complete. Due to its intractability, we start by restricting the number of UAVs to be one. We show that under this special case the problem can be formulated as a convex optimization problem under a restriction on the coverage angle of the ground users. After that, we propose a gradient projection-based algorithm to find the optimal location of the UAV. Based on this, we then develop an efficient algorithm for the general case of multiple UAVs. The proposed algorithm starts by clustering the wireless devices into several clusters where each cluster being served by one UAV. After it finishes clustering the wireless devices, it applies the gradient projection-based algorithm in each cluster. We also formulate the problem of minimizing the number of UAVs required to serve the ground users such that the time duration of uplink transmission of each wireless device is greater than or equal to a threshold value. We prove that this problem is NP-complete and propose to use two efficient methods to determine the minimum number of UAVs required to serve the wireless devices. We validate the analysis by simulations and demonstrate the effectiveness of the proposed algorithms under different cases.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Load-Based On/Off Scheduling for Energy-Efficient Delay-Tolerant 5G
           Networks
    • Authors: Haluk Çelebi;Yavuz Yapıcı;İsmail Güvenç;Henning Schulzrinne;
      Pages: 955 - 970
      Abstract: Dense deployment of small cells is seen as one of the major approaches for addressing the traffic demands in next-generation 5G wireless networks. The energy efficiency, however, becomes a concern along with the deployment of massive amount of small cells. In this paper, we consider the energy-efficient small cell networks (SCNs) using smart on/off scheduling (OOS) strategies, where a certain fraction of small base stations (SBSs) are put into less energy-consuming sleeping states to save energy. To this end, we first represent the overall SCN traffic by a new load variable, and analyze its statistics rigorously using Gamma approximation. We then propose two novel OOS algorithms exploiting this load variable in centralized and distributed fashions. We show that proposed load-based OOS algorithms can lead to as high as 50% of energy savings without sacrificing the average SCN throughput. In addition, load-based strategies are shown to work well under high SCN traffic and delay-intolerant circumstances, and can be implemented efficiently using the load statistics. We also show that the performance of load-based algorithms gets maximized for certain length of sleeping periods, where assuming short sleep periods is as energy-inefficient as keeping SBSs in sleep states for very long.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Energy Efficiency of the Cell-Free Massive MIMO Uplink With Optimal
           Uniform Quantization
    • Authors: Manijeh Bashar;Kanapathippillai Cumanan;Alister G. Burr;Hien Quoc Ngo;Erik G. Larsson;Pei Xiao;
      Pages: 971 - 987
      Abstract: A cell-free Massive multiple-input multiple-output (MIMO) uplink is considered, where the access points (APs) are connected to a central processing unit (CPU) through limited-capacity wireless microwave links. The quantized version of the weighted signals are available at the CPU, by exploiting the Bussgang decomposition to model the effect of quantization. A closed-form expression for spectral efficiency is derived taking into account the effects of channel estimation error and quantization distortion. The energy efficiency maximization problem is considered with per-user power, backhaul capacity and throughput requirement constraints. To solve this non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design, and power allocation. The receiver filter coefficient design is formulated as a generalized eigenvalue problem whereas a successive convex approximation (SCA) and a heuristic sub-optimal scheme are exploited to convert the power allocation problem into a standard geometric programming (GP) problem. An iterative algorithm is proposed to alternately solve each sub-problem. Complexity analysis and convergence of the proposed schemes are investigated. Numerical results indicate the superiority of the proposed algorithms over the case of equal power allocation.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Are Run-Length Limited Codes Suitable for Simultaneous Energy and
           Information Transfer'
    • Authors: Anshoo Tandon;Mehul Motani;Lav R. Varshney;
      Pages: 988 - 996
      Abstract: Run-length limited (RLL) codes are a well-studied class of constrained codes having application in diverse areas, such as optical and magnetic data recording systems, DNA-based storage, and visible light communication. RLL codes have also been proposed for the emerging area of simultaneous energy and information transfer, where the receiver uses the received signal for decoding information as well as for harvesting energy to run its circuitry. In this paper, we show that RLL codes are not the best codes for simultaneous energy and information transfer, in terms of the maximum number of codewords which avoid energy outage, i.e., outage-constrained capacity. Specifically, we show that sliding window constrained (SWC) codes and sub-block energy constrained (SEC) codes have significantly higher outage-constrained capacities than RLL codes for moderate to large energy buffer sizes.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Harvest-or-Transmit Policy for Cognitive Radio Networks: A Learning
           Theoretic Approach
    • Authors: Kalpant Pathak;Adrish Banerjee;
      Pages: 997 - 1011
      Abstract: We consider an underlay cognitive radio network where the secondary user (SU) harvests energy from the environment. We consider a slotted-mode of operation where each slot of SU is used for either energy harvesting or data transmission. Considering block fading with memory, we model the energy arrival and fading processes as a stationary Markov process of first-order. We propose a harvest-or-transmit policy for the SU along with optimal transmit powers that maximize its expected throughput under three different settings. First, we consider a learning-theoretic approach where we do not assume any a priori knowledge about the underlying Markov processes. In this case, we obtain an online policy using Q-learning. Then, we assume that the full statistical knowledge of the governing Markov process is known a priori. Under this assumption, we obtain an optimal online policy using infinite horizon stochastic dynamic programming. Finally, we obtain an optimal offline policy using the generalized Benders decomposition algorithm. The offline policy assumes that for a given time deadline, the energy arrivals and channel states are known in advance at all the transmitters. Finally, we compare all policies and study the effects of various system parameters on the system performance.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Full-Duplex SWIPT Relaying Based on Spatial-Modulation
    • Authors: Weilin Qu;Xiang Cheng;Chen Chen;Liuqing Yang;
      Pages: 1012 - 1022
      Abstract: In this paper, we investigate the application of spatial-modulation (SM) in multi-antenna full-duplex (FD) decode-and-forward (DF) relay networks with simultaneous wireless information and power transfer (SWIPT). Both the time switching (TS) and power splitting (PS) protocols are employed. In the proposed scheme, a subset of relay antennas are selected to forward the received information signal with the harvested energy and the remaining inactive antennas receive the energy signal/information signal from the source node. The application of SM at the relay node leads to the throughput improvement of the relay-to-destination link because of the additional information mapped to the active antenna indices, which consequently leads to the overall system throughput improvement. According to the proposed tight SM mutual information (MI) upper bound, we provide a theoretical solution for the system throughput optimization. Monte-Carlo simulations verify the significant throughput gain facilitated by SM as well as the validity of the throughput optimization.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Delay-Optimal Resource Scheduling of Energy Harvesting-Based Devices
    • Authors: Ibrahim Fawaz;Mireille Sarkiss;Philippe Ciblat;
      Pages: 1023 - 1034
      Abstract: This paper investigates resource scheduling in a wireless communication system operating with energy harvesting (EH)-based devices and perfect channel state information (CSI). The aim is to minimize the packet loss that occurs when the buffer is overflowed or when the queued packet is older than a certain pre-defined threshold. So, we consider a strict delay constraint rather than an average delay constraint. The associated optimization problem is modeled as the Markov decision process (MDP) where the actions are the number of packets sent on the known channel at each slot. The optimal deterministic offline policy is exhibited through dynamic programming techniques, i.e., value iteration (VI) algorithm. We show that the gain in the number of transmitted packets and the consumed energy is substantial compared to: 1) a naive policy which forces the system to send the maximum number of packets using the available energy in the battery; 2) two variants of the previous policy that take into account the buffer state; and 3) a policy optimized with an average delay constraint. Finally, we evaluate our optimal policy under imperfect CSI scenario where only an estimate of the channel state is available.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Parameter-Adaptive Dynamic and Adjustable DRX Schemes for LTE/LTE-A
    • Authors: Huei-Wen Ferng;Ying-Tsu Tseng;Teng-Hui Wang;
      Pages: 1035 - 1043
      Abstract: In LTE/LTE-A, the discontinuous reception (DRX) was originally defined to save power for a user equipment (UE). To exhibit flexibility, two dynamic and adjustable DRX (DADRX) schemes, i.e., DADRX- ${m}$ and P-DADRX, were designed in the literature. However, they cannot work adaptively according to some preset goals, for example, delay or power constraints. To achieve such goals, the DADRX with adaptive parameters (DADRX-AP) schemes are further proposed in this paper based on DADRX- ${m}$ . These DADRX-AP schemes allow UEs to pose their constraints on delay or power consumption and the evolved node B (eNB) is able to estimate the packet arrival rate and find feasible parameters for UEs in an iterative manner so that the constraints can be satisfied. Obviously, the delay-constrained or power-constrained features as well as adaptive parameters make our proposed DADRX-AP schemes more practical than DADRX- ${m}$ , CDA-DRX, and the original DRX in LTE/LTE-A. Via simulations, we successfully demonstrate that our proposed DADRX-AP schemes can set suitable parameters to meet the preset constraints with an acceptable convergence rate.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • UAV-Assisted Cooperative Communications With Power-Splitting Information
           and Power Transfer
    • Authors: Sixing Yin;Yifei Zhao;Lihua Li;F. Richard Yu;
      Pages: 1044 - 1057
      Abstract: In this paper, we focus on a unmanned aerial vehicle (UAV)-assisted cooperative communication system with simultaneous wireless information and power transfer (SWIPT), where the UAV serves as a mobile relay and is powered by radio signal from the source via power-splitting mechanism. We study the end-to-end cooperative throughput maximization problem by optimizing the UAV’s power profile, power-splitting ratio profile and trajectory for both amplify-and-forward (AF) and decode-and-forward (DF) protocols. The problem is decomposed into two subproblems: 1) profile optimization and 2) trajectory optimization. The former one is solved via dual decomposition and the latter one is solved via successive convex optimization. Then the cooperative throughput is optimized by alternately solving the two subproblems. Simulation results show that with the proposed optimal solution, choice for the UAV’s power profile and power-splitting ratio profile is more long-sighted than two greedy strategies and successive optimization for trajectory design can converge in a few rounds of iteration. The proposed optimal solution outperforms not only mobile and static greedy strategies but also a similar solution from an existing work without consideration of SWIPT with performance gain up to 30%. Moreover, we also show that the convergence speed of the proposed algorithm is acceptable even with high improvement requirement.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Efficient Algorithms for Mobile Sink Aided Data Collection From Dedicated
           and Virtual Aggregation Nodes in Energy Harvesting Wireless Sensor
           Networks
    • Authors: Lei Tao;Xin Ming Zhang;Weifa Liang;
      Pages: 1058 - 1071
      Abstract: We study the mobile data collection problem in an energy harvesting wireless sensor network (EH-WSN), where sensor nodes are densely deployed in a monitoring area and a mobile sink (MS) travels around the area to collect sensory data from the sensors. In order to optimize the network performance while achieving perpetual network operation, we propose efficient algorithms to dynamically schedule the MS for collecting data from sensors with different data generation rates. Specifically, in this paper, we propose an optimization framework that consists of three stages. We first deal with the reliable, stable, and energy neutral energy assignment for sensors. We then find a closed trajectory for the MS for sensory data collection that covers as many as aggregation nodes, and devise a decentralized algorithm to determine the data generation rate of each sensor and the data flow rate of each link to optimize the network performance. We also develop a fast heuristic algorithm for the problem. We finally evaluate the performance of the proposed algorithms through numerical experiments. The simulation results demonstrate that the proposed algorithms are efficient.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Optimal Relaying in Energy Harvesting Wireless Networks With
           Wireless-Powered Relays
    • Authors: Masoumeh Moradian;Farid Ashtiani;Ying Jun Zhang;
      Pages: 1072 - 1086
      Abstract: In this paper, we consider a wireless cooperative network with a wireless-powered energy harvesting (EH) relay. The relay employs a time switching (TS) policy that switches between the EH and data decoding (DD) modes. Both energy and data buffers are kept at the relay to store the harvested energy and decoded data packets, respectively. In this paper, we derive static and dynamic TS policies that maximize the system throughput or minimize the average transmission delay. In particular, in the static policies, the EH or DD mode is selected with a pre-determined probability. In contrast, in a dynamic policy, the mode is selected dynamically according to the states of data and energy buffers. We prove that the throughput-optimal static and dynamic policies keep the relay data buffer at the boundary of stability. More specifically, we show that the throughput-optimal dynamic policy has a threshold-based structure. Moreover, we prove that the delay-optimal dynamic policy is threshold-based and keeps at most one packet at the relay. We notice that unlike the static case, the delay-optimal and throughput-optimal dynamic policies coincide in most cases. Finally, through extensive numerical results, we demonstrate the efficiency of the optimal dynamic policies compared with the static ones.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Ambient Backscatter-Assisted Wireless-Powered Relaying
    • Authors: Xiao Lu;Dusit Niyato;Hai Jiang;Ekram Hossain;Ping Wang;
      Pages: 1087 - 1105
      Abstract: Internet-of-Things (IoT) features with low-power communications among a massive number of ubiquitously-deployed and energy-constrained electronics, e.g., sensors and actuators. To cope with the demand, wireless-powered cooperative relaying emerges as a promising communication paradigm to extend data transmission coverage and solve energy scarcity for the IoT devices. In this paper, we propose a novel hybrid relaying strategy by combining wireless-powered communication and ambient backscattering functions to improve the applicability and performance of data transfer. In particular, the hybrid relay can harvest energy from radio frequency (RF) signals and use the energy for active transmission. Alternatively, the hybrid relay can choose to perform ambient backscattering of incident RF signals for passive transmission. For the operation of the hybrid relaying, selecting a proper mode based on the network environment is the key to better relaying performance. To address this issue, we design mode selection protocols to coordinate between the active and passive relaying in the cases with and without instantaneous channel state information (CSI) of active transmission, respectively. In the former case, since the hybrid relay is aware of whether the two relaying modes are applicable for the current time slot based on the CSI, it selects active relaying if applicable due to higher capacity and selects passive relaying otherwise. In the latter case, the hybrid relay first explores the two relaying modes and commits to the mode that achieves more successful transmissions during the exploration period. With different mode selection protocols, we characterize the success probability and ergodic capacity of a dual-hop relaying system with the hybrid relay in the field of randomly located ambient transmitters. The analytical and the numerical results demonstrate the effectiveness of the mode selection protocols in adapting the hybrid relaying into the network environment and rev-al the impacts of system parameters on the performance of the hybrid relaying. As applications of our analytical framework which is computationally tractable, we formulate optimization problems based on the derived expressions to optimize the system parameters with different objectives. The optimal solutions exhibit a tradeoff between the maximum energy efficiency and target success probability.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Online Energy Harvesting Problem Over an Arbitrary Directed Acyclic Graph
           Network
    • Authors: Rahul Vaze;Sibi Raj B. Pillai;
      Pages: 1106 - 1116
      Abstract: A communication network modelled by a directed acyclic graph (DAG) is considered, over which a source wishes to send a specified number of bits to a destination node. Each node of the DAG is powered by a separate renewable energy source, and the harvested energy is used to facilitate the source destination data flow. The challenge here is to find the optimal rate and power allocations across time for each node on its outgoing edges so as to minimize the time by which the destination receives a specified number of bits. An online setting is considered where an algorithm only has causal information about the energy arrivals. Using the competitive ratio as the performance metric, i.e., the ratio of the cost of the online algorithm and the optimal offline algorithm, maximized over all inputs, a lazy online algorithm with a competitive ratio of $2{pmb {+}}delta $ for any $delta >0$ is proposed. Incidentally, 2 is also a lower bound to the competitive ratio of any online algorithm for this problem. Our lazy online algorithm is described and analyzed via defining a novel max-flow problem over a DAG, where the rate on the subset of outgoing edges of any node are related/constrained. An optimal algorithm to find max-flow with these constraints is also provided, which may be of independent interest.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • UAV-Assisted RFET: A Novel Framework for Sustainable WSN
    • Authors: Suraj Suman;Sidharth Kumar;Swades De;
      Pages: 1117 - 1131
      Abstract: Limited battery capacity is one of the major hurdles towards perpetual operation of wireless sensor networks. In this paper, a novel framework for charging the sensor nodes using unmanned aerial vehicle (UAV)-assisted radio frequency energy transfer (RFET) is presented. First, the notion of RFET zone is conceptualized and a closed-form expression for RFET zone radius is obtained. The sensor nodes located inside this zone can harvest energy from the transmitter mounted on UAV. The effective power harvested at the sensor node situated at different spatial locations is evaluated by considering the impact of shadowing statistics of path loss and non-linear RF-to-direct current conversion efficiency. With these findings on sensor nodes deployed in a given area, an optimization problem is formulated with the objective of minimizing the total time in a charging cycle, which is comprised of travel time and charging time. This problem is decomposed into two sub-problems and they are solved individually in sequential steps. The optimal solution of the first sub-problem, which provides the sequence of charging having minimum travel time, is a Traveling Salesman Problem (TSP). In the second sub-problem, the presence of Lambert function makes it analytically intractable, and hence, approximations are presented to solve this. Subsequently, to account for the health parameters of the sensor nodes in estimating the charging cycle, three variants of order of charging, namely, Voltage-aware Charging Sequence, Operational Time-aware Charging Sequence, and Iterative Charging Sequence, are proposed. Through system simulations it is demonstrated that, in a generalized setting, the charging sequence offered by the proposed variants perform increasingly better in comparison to the state-of-the-art TSP approach.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • AUV-Aided Energy-Efficient Clustering in the Internet of Underwater Things
    • Authors: Muhammad Toaha Raza Khan;Syed Hassan Ahmed;Dongkyun Kim;
      Pages: 1132 - 1141
      Abstract: The integration of the Internet of Things (IoT) in our lives has become reality during the last decade. Mostly, IoT is considered a system of systems, where sensors make a big chunk of any IoT communication system. Similarly, in this paper, we introduce a notion of the Internet of Underwater Things (IoUT), where we consider a set of sensors deployed in the deep sea to form a communication network for any possible application, such as military, environmental, pollution surveillance, etc. Since it is too optimistic to recharge or replace sensor batteries in an underwater environment, efficient management of the available resources can extend the overall network lifetime. To do so, nodes clustering is a potential solution, however, exchange of multiple packets for cluster head selection requires a considerable amount of energy. In this paper, we present an autonomous unmanned vehicles (AUVs) assisted energy-efficient clustering (AEC) mechanism that introduces wake-up sleep cycle for the underwater nodes. AUV onus includes cluster creation, the cluster head nomination, and creation of a wakeup sleep schedule that relieves the additional burden from energy limited underwater sensor nodes. Due to no additional packets been exchanged, our protocol outperforms traditional clustering schemes and we validate this through simulations.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Energy-Efficient On-Demand Resource Provisioning in Cloud Radio Access
           Networks
    • Authors: Qiang Liu;Tao Han;Nirwan Ansari;
      Pages: 1142 - 1151
      Abstract: By leveraging the elasticity of cloud computing, cloud radio access network (C-RAN) facilitates flexible resource management and is one of the key techniques of enabling 5G. In this paper, we study the energy-efficient on-demand resource provisioning in C-RAN by dynamically provisioning the radio and computing resources according to network traffic demands. The network energy consumption of C-RAN is minimized by jointly optimizing the cooperative beamforming, remote radio head (RRH) selection, and virtual baseband units (vBBUs) provisioning. It is challenging to resolve the optimization problem because of the interdependence between the RRH selection and vBBU provisioning. We propose the energy-efficient on-demand C-RAN virtualization (REACT) algorithm to solve the problem in two steps. First, we cluster RRHs into groups by using the hierarchical clustering analysis (HCA) algorithm and assign a vBBU to each RRH group for the baseband signal processing. Second, we determine the RRH selection by optimizing the cooperative beamforming. The performance of the proposed algorithm is validated through extensive simulations, which show that the proposed algorithm significantly reduces the network energy consumption.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • Distributed Energy Efficient Channel Allocation
    • Authors: Oshri Naparstek;S. M. Zafaruddin;Amir Leshem;Eduard A. Jorswieck;
      Pages: 1152 - 1166
      Abstract: Design of energy efficient protocols for modern wireless systems has become an important area of research. In this paper, we propose a distributed optimization algorithm for the channel assignment problem for multiple interfering transceiver pairs that cannot communicate with each other. We first modify the auction algorithm for maximal energy efficiency and show that the problem can be solved without explicit message passing using the carrier sense multiple access (CSMA) protocol. We then develop a novel scheme by converting the channel assignment problem into perfect matchings on bipartite graphs. The proposed scheme improves the energy efficiency and does not require any explicit message passing or a shared memory between the users. We derive bounds on the convergence rate and show that the proposed algorithm converges faster than the distributed auction algorithm and achieves near-optimal performance under Rayleigh fading channels. We also present an asymptotic performance analysis of the fast matching algorithm for energy efficient resource allocation and prove the optimality for a large enough number of users and number of channels. Finally, we provide numerical assessments that confirm the faster convergence of the proposed algorithm compared to the distributed auction algorithm.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
  • 2019 Index IEEE Transactions on Green Communications and Networking Vol. 3
    • Pages: 1167 - 1185
      Abstract: Presents the 2019 subject/author index for this publication.
      PubDate: Dec. 2019
      Issue No: Vol. 3, No. 4 (2019)
       
 
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