Cognitive radio network with continuous energy‐harvesting

In this paper, the performance of a cooperative cognitive radio (CR) network is investigated under continuous energy harvesting scenario. A CR node harvests energy from both the sources: non‐radio frequency (RF) signal (ambient sources) or from RF signal (primary user signal). It harvests from non‐RF signal during sensing time of its detection cycle, and from both the sources, RF signal and non‐RF signal, during transmission time as per sensing decision. Several novel analytical expressions are developed to indicate the harvested energy, energy reward, energy cost in a detection frame, and throughput. The performance of the CR network is investigated to maximize the throughput considering energy causality constraints and collision constraints. Analytical results are validated through extensive simulation results. Copyright © 2016 John Wiley & Sons, Ltd.     

Self‐Powered Sensors Enabled by Wide‐Bandgap Perovskite Indoor Photovoltaic Cells

A new approach to ubiquitous sensing for indoor applications is presented, using low‐cost indoor perovskite photovoltaic cells as external power sources for backscatter sensors. Wide‐bandgap perovskite photovoltaic cells for indoor light energy harvesting are presented with the 1.63 and 1.84 eV devices that demonstrate efficiencies of 21% and 18.5%, respectively, under indoor compact fluorescent lighting, with a champion open‐circuit voltage of 0.95 V in a 1.84 eV cell under a light intensity of 0.16 mW cm^?2. Subsequently, a wireless temperature sensor self‐powered by a perovskite indoor light‐harvesting module is demonstrated. Three perovskite photovoltaic cells are connected in series to create a module that produces 14.5 µW output power under 0.16 mW cm^?2 of compact fluorescent illumination with an efficiency of 13.2%. This module is used as an external power source for a battery‐assisted radio‐frequency identification temperature sensor and demonstrates a read range by of 5.1 m while maintaining very high frequency measurements every 1.24 s. The combined indoor perovskite photovoltaic modules and backscatter radio‐frequency sensors are further discussed as a route to ubiquitous sensing in buildings given their potential to be manufactured in an integrated manner at very low cost, their lack of a need for battery replacement, and the high frequency data collection possible.     

环境射频能量收集技术的研究进展及应用

随着超低功耗集成电路技术的发展,电子微系统的功耗已进入微瓦（μW）级范围,使其利用周围环境中的射频能量为自身供电成为可能。在回顾无线能量传输的历史以及介绍环境射频能量收集的可行性及其应用研究成果和进展的基础上,分析环境射频能量收集在超低功耗电子微系统中广泛应用所面临的关键技术、难点以及可能的解决方法;最后讨论了环境射频能量收集技术的发展方向,使该领域有待于研究的问题和方向更加具体化、明确化。     

射频能量捕获传感网移动能量源的布置策略研究

射频能量捕获传感网（RF Energy Harvesting Wireless Sensor Network,RFEH-WSN）由专用射频能量源设备（Energy Transmitter,ET）和具有射频能量捕获功能的传感器节点（Energy Harvesting Recevier,简称EHR）组成.该网络解决了传感器网络中电池不易更换与节点能量容易耗尽的问题,使得RFEH-WSN应用前景更加广阔.RFEH-WSN应用中一个值得研究的问题是如何布置ET的充电位置,降低ET能耗且提高覆盖率.已有的工作主要考虑ET布置中单目标优化问题,如最小充电时间、最小功耗、最大覆盖率等.本文以时间最小和覆盖率最大为目标建立多目标优化模型,并提出利用粒子群算法（Particle Swarm Optimization,PSO）求解多目标函数（Multiple Object Program,MOP）的低复杂度近似算法,获得了最优Pareto解集.仿真结果表明,多目标优化可以满足不同情况的需求,提高充电效用.     

A joint sensing and transmission power control policy for RF energy harvesting cognitive radio networks

We consider a radio frequency energy harvesting cognitive radio network in which a secondary user (SU) can opportunistically access channel to transmit packets or harvest radio frequency energy when the channel is idle or occupied by a primary user. The channel occupancy state and the channel fading state are both modeled as finite state Markov chains. At the beginning of each time slot, the SU should determine whether to harvest energy for future use or sense the primary channel to acquire the current channel occupancy state. It then needs to select an appropriate transmission power to execute the packet transmission or harvest energy if the channel is detected to be idle or busy, respectively. This sequential decision‐making, done to maximize the SU's expected throughput, requires to design a joint spectrum sensing and transmission power control policy based on the amount of stored energy, the retransmission index, and the belief on the channel state. We formulate this as a partially observable Markov decision process and use a computationally tractable point‐based value iteration algorithm. Section 5 illustrate the significant outperformance of the proposed optimal policy compared with the optimal fixed‐power policy and the greedy fixed‐power policy.     

Optimal Mode Selection Policies in Cognitive Radio Networks with RF Energy Harvesting

Applying energy harvesting technology in cognitive radio networks (CRNs) leads to a tradeoff between the time allocated for spectrum sensing followed by spectrum accessing and that for energy harvesting. This tradeoff can be formulated as a mode selection problem for the secondary users. In this paper, we consider a CRN working in the time-slotted manner. The secondary users powered by radio frequency energy harvesting can perform overlay transmission or cooperate with the primary users. To maximize the long-term throughput of the secondary network, we propose two optimal mode selection policies by formulating this problem under a partially observable Markov decision process framework. Numerical simulations show that both of our proposed policies achieve more throughput than the overlay-only policy. Finally, we also evaluate the effect of the cooperative threshold and the energy harvesting process on the optimal policies.     

Achieving energy‐neutral data transmission by adjusting transmission power for energy‐harvesting wireless sensor networks

Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery‐powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy‐harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy‐neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy‐neutral operation, we first propose a polynomial‐time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial‐time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near‐optimal algorithm based on the Ford–Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.     

Statistical analysis on ambient RF energy harvesting for low‐power wireless applications

Renewable energy sources from the earth constitute another option apart from the available ones for wellspring of energy for economizing on cost of power supply. The energy obtained from ambient sources is called energy harvesting. Energy‐harvesting low‐power systems have acquired a remarkable consideration as a viable hotspot for expanding both energy efficiency and spectral efficiency. Radio frequency (RF) energy harvesting from ambient source is a promising technique for fulfilling the irreplaceable power prerequisites for powering the low‐power devices. Hence, it requires the development of an antenna for harvesting RF energy. In this paper, a coplanar waveguide (CPW) antenna has been designed and fabricated using FR4 lossy substrate. This CPW antenna covers frequency bands from the most important RF patrons (GSM 900, GSM 1800, 3G, and Wi‐Fi) within the frequency range from (0.58 to 3 GHz) with a percentage fractional bandwidth of 116% with the center frequency of 1.65 GHz. The fabricated antenna then has been experimentally validated at SSN College of Engineering campus. The effects on the RF power density level for CPW antenna are examined by statistical approach known as Taguchi method. The L9 and L8 orthogonal arrays and analysis of variance are implemented to analyze the execution qualities. The CPW antenna control factors are distance, time, and number of receivers. Then, statistical test (P) are used to determine the significant factors on RF power density.     

Energy‐efficient resource allocation in D2D communications for energy harvesting–enabled NOMA‐based cellular networks

In this paper, we propose an energy‐efficient power control and harvesting time scheduling scheme for resource allocation of the subchannels in a nonorthogonal multiple access (NOMA)–based device‐to‐device (D2D) communications in cellular networks. In these networks, D2D users can communicate by sharing the radio resources assigned to cellular users (CUs). Device‐to‐device users harvest energy from the base station (BS) in the downlink and transmit information to their receivers. Using NOMA, more than one user can access the same frequency‐time resource simultaneously, and the signals of the multiusers can be separated successfully using successive interference cancellation (SIC). In fact, NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time by implementing adaptive power allocation. Our aim is to maximize the energy efficiency of the D2D pairs, which is the ratio of the achievable throughput of the D2D pairs to their energy consumption by allocating the proper subchannel of each cell to each device user equipment (DUE), managing their transmission power, and setting the harvesting and transmission time. The constraints of the problem are the quality of service of the CUs, minimum required throughput of the subchannels, and energy harvesting of DUEs. We formulate the problem and propose a low‐complexity iterative algorithm on the basis of the convex optimization method and Karush‐Kuhn‐Tucker conditions to obtain the optimal solution of the problem. Simulation results validate the performance of our proposed algorithm for different values of the system parameters.     

基于射频能量收集的无线中继网络资源分配

针对现有射频能量收集网络资源分配研究局限于单个数据源场景,无法适配于多数据源网络的问题,提出了一种适用于多数据源场景的射频能量收集中继网络传输协议框架,在该框架内节点可作为源节点或中继节点传输自身数据或转发数据,并在其他节点的数据传输过程中完成射频能量收集。以协议框架为基础,分别以系统吞吐量及用户公平性为优化目标设计两种资源分配方案。仿真表明,两种方案可有效改善网络吞吐量及资源分配公平性。     

反向散射通信辅助的认知无线能量通信网络的时间分配研究

为了改善次发射机的性能,本文在衬底式(Underlay)认知无线能量通信网络(Cognitive Wireless Powered Communication Networks, CWPCNs)中提出了一种新的网络模型,该网络含有一个主发射机和两个由次发射机和次接收机组成的次用户对。次发射机可工作在反向散射通信(Backscatter Communication, BackCom)和收集再传输(Harvest-then-transmit, HTT)两种协议下。针对提高次网络的系统容量,根据收集的能量是否可以驱动次发射机工作,本文考虑了三种场景并针对每种场景设计了最优的时间分配方案。仿真结果表明,相比于单独利用BackCom或HTT协议以及协作式CWPCN,本文提出的新方法性能更佳。      

Throughput optimization using simultaneous sensing and transmission in energy harvesting cognitive radio networks

A three‐dimensional continuous‐time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade‐off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self‐interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works.     

A smart spectrum utilization approach using multiantenna‐based cognitive relays in cognitive radio network

Efficient spectrum utilization is a promising technique for a prolonged unused radio frequency (RF) spectrum in a wireless network. In this paper, an adaptive spectrum sharing cognitive radio (CR) network has been proposed consisting of a primary user (PU) and secondary user transmitter (SU ? Tx) that communicates with secondary user receiver (SU ? Rx) via multiantenna‐based proactive decode‐and‐forward (DF) relay selection scheme. In our model, strategically an adaptable joint venture on underlay/overlay protocol is defined based on channel occupancy using spectrum sensing technique. Here, secondary transmitters (i.e., source transmitter) continuously sense the PU activities by energy detector and can simultaneously transmit to secondary receivers. Depending on sensing result secondary transmitters automatically switches in underlay mode if PU is active otherwise operates in overlay mode. The advantage of this scheme is that the joint mode of transmission allows the SUs to maximize their transmission rate. The outage performance at SU ? Rx and closed‐form expressions of joint underlay/overlay protocol has been evaluated. The power control policies at different transmitter nodes are taken care of. With the same diversity order, a trade‐off between multiantenna and multirelay is shown. This comparison shows improvement in outage behavior when the count in relays surpasses the number of antennas. Finally, the analytical model of smart efficient spectrum utilization without harming license users in CR is validated by MATLAB simulation.     

Energy harvesting,cooperative spectrum sensing,and data transmission improvement in energy‐efficient multichannel cognitive sensor networks

In this paper, we investigate the energy harvesting capability in a multichannel wireless cognitive sensor networks for energy‐efficient cooperative spectrum sensing and data transmission. Spectrum sensors can cooperatively scan the spectrum for available channels, whereas data sensors transmit data to the fusion center (FC) over those channels. We select the sensing, data transmission, and harvesting sensors by setting the sensing time, data transmission time, and also harvesting time to maximize the network data transmission rate and improve the total energy consumption in the multichannel network under global probability of false alarm and global probability of detection constraints. We formulate our optimization problem and employ the convex optimization method to obtain the optimal times and nodes for spectrum sensing, data transmission, and harvesting energy in each subchannel for multiband cognitive sensor networks. Simulation results show that in our proposed algorithm, the network data transmission rate is improved while more energy is saved compared with the baseline methods with equal sensing time in all subchannels.     

Improving physical layer security via cooperative diversity in energy‐constrained cognitive radio networks with multiple eavesdroppers

In this paper, a scheme that exploits cooperative diversity of multiple relays to provide physical layer security against an eavesdropping attack is concerned. Relay‐based cognitive radio network (CRN) faces issues multiple issues other than the same as faced by conventional wireless communications. If the nodes in a CRN are able to harvest energy and then spend less energy than the total energy available, we can ensure a perpetual lifetime for the network. In this paper, an energy‐constrained CRN is considered where relay nodes are able to harvest energy. A cooperative diversity‐based relay and subchannel‐selection algorithm is proposed, which selects a relay and a subchannel to achieve the maximum secrecy rate while keeping the energy consumed under a certain limit. A transmission power factor is also selected by the algorithm, which ensures long‐term operation of the network. The power allocation problem at the selected relay and at the source also satisfies the maximum‐interference constraint with the primary user (PU). The proposed scheme is compared with a variant of the proposed scheme where the relays are assumed to have an infinite battery capacity (so maximum transmission power is available in every time slot) and is compared with a scheme that uses jamming for physical layer security. The simulation results show that the infinite battery‐capacity scheme outperforms the jamming‐based physical layer security scheme, thus validating that cooperative diversity‐based schemes are suitable to use when channel conditions are better employed, instead of jamming for physical layer security.     

Optimization of energy efficiency for cognitive radio with partial RF energy harvesting

The cognitive radio (CR) with energy harvesting is a potential technology to improve both the spectrum efficiency (SE) and the energy efficiency (EE). In this letter, we consider that the secondary users can harvest radio frequency (RF) energy from primary signal and its own signal. The goal is to maximize the energy efficiency of the CR system subject to sufficient protection to the primary user and the power constraint. An efficient algorithm is proposed to optimize the sensing time and the power of the secondary transmitter. Simulation results show that the EE is further improved by using the proposed mechanism.     

Secrecy Performance of CCRN with an EHAF Relay under Source and Destination Jamming

In this paper, we investigate the secrecy performance of a cooperative cognitive radio network (CCRN) considering a single energy harvesting (EH) half‐duplex amplify and forward (AF) relay and an eavesdropper (EAV). Power is allocated to each node under cognitive constraints. Because of the absence of a direct wireless link, secondary source (SS) communicates with secondary destination (SD) in two time slots. The SD and the SS broadcast jamming signal to confuse the EAV in the first and in the second time slots, respectively. The relay harvests energy in the first time slot and amplifies and forwards the signal to SD in the second time slot. The EAV employs maximal ratio combining scheme to extract the information. We evaluate the performance in terms of secrecy outage probability (SOP) of the proposed CCRN. The approximate expression of SOP is obtained in integration form. Improvement in SOP is expected for the proposed CCRN because of the use of jamming signals. The secrecy performance of CCRN improves with increase in primary transmit power, peak transmit power of secondary nodes, channel mean power, and energy conversion efficiency but degrades with increase in threshold outage rate of primary receiver and threshold secrecy rate. A MATLAB‐based simulation framework has been developed to validate the analytical work.     

Wireless powered underlay cognitive radio network with multiple primary transceivers: Energy constraint,node arrangement,and performance analysis

This paper considers a cognitive radio–assisted wireless information and power transfer system consisting of multipair of transceiver in primary network and 2‐hop relaying link in secondary network. In this investigation, a decoded‐and‐forward–assisted relay node and power splitting protocol are deployed to obtain ability of wireless energy transfer. The relay node harvests energy from the radio frequency signals of the secondary transmitter and primary transmitters in data transmission to the destination by reusing the licensed spectrum resource. We propose 2 policies for wireless power transfer at the relay, namely, (1) multisource power transfer and (2) single‐source power transfer. To evaluate performance under energy harvesting regime, we derive the closed‐form outage probability expressions and achievable throughput of the secondary network in delay‐limited transmission mode. In addition, we investigate the impact of various system parameters including number of primary transceivers, primary outage threshold, and position arrangement of nodes in primary transceivers on the outage performance of the proposed scheme. Furthermore, we evaluate the system energy efficiency to show trade‐off metric of energy consumption and throughput. Performance results are presented to validate our theoretical derivation and illustrate the impacts of various system parameters. An important result is that the secondary network is more beneficial than harmful from the primary interference under power constraint and reasonable node location arrangement.     

Secure communication in cognitive radio networks with untrusted AF relays

In this paper, two underlay based cognitive cooperative radio networks, each with one secondary source (SS), one secondary destination (SD), N untrusted secondary amplify and forward relays (USAFRs), one primary transmitter, and one primary receiver (PU‐RX), are considered for evaluating the secrecy performance. The SS sends the information to the SD in two time slots via multiple USAFRs in the absence of direct link between SS and SD. In the first time slot, SS and SD transmit the message and jamming signal to multiple USAFRs, respectively. In the second slot, a selected USAFR amplifies and forwards the combined received signals to the SD. The transmit powers of the secondary nodes are chosen so as to maintain the overall interference at PU‐RX below a specified limit. The transmit power of a selected USAFR is derived using the harvested energy from the RF signals of SS and SD. Two network scenarios of eavesdropping by USAFRs are studied: in one case, all USAFRs eavesdrop; while in the second case, only the selected USAFR eavesdrops the message during forwarding of the signal and power is allocated to secondary nodes on the basis of outage threshold of primary network. We investigate the secrecy outage probability (SOP) in both of the networks under several physical parameters. Analytical framework for evaluating SOP for both the cases are given while SOP in single integration form is given for the second case. MATLAB simulation results are presented for both the cases.     

Fingerprint‐Inspired Conducting Hierarchical Wrinkles for Energy‐Harvesting E‐Skin

In the field of bionics, sophisticated and multifunctional electronic skins with a mechanosensing function that are inspired by nature are developed. Here, an energy‐harvesting electronic skin (energy‐E‐skin), i.e., a pressure sensor with energy‐harvesting functions is demonstrated, based on fingerprint‐inspired conducting hierarchical wrinkles. The conducting hierarchical wrinkles, fabricated via 2D stretching and subsequent Ar plasma treatment, are composed of polydimethylsiloxane (PDMS) wrinkles as the primary microstructure and embedded Ag nanowires (AgNWs) as the secondary nanostructure. The structure and resistance of the conducting hierarchical wrinkles are deterministically controlled by varying the stretching direction, Ar plasma power, and treatment time. This hierarchical‐wrinkle‐based conductor successfully harvests mechanical energy via contact electrification and electrostatic induction and also realizes self‐powered pressure sensing. The energy‐E‐skin delivers an average output power of 3.5 mW with an open‐circuit voltage of 300 V and a short‐circuit current of 35 µA; this power is sufficient to drive commercial light‐emitting diodes and portable electronic devices. The hierarchical‐wrinkle‐based conductor is also utilized as a self‐powered tactile pressure sensor with a sensitivity of 1.187 mV Pa^‐1 in both contact‐separation mode and the single‐electrode mode. The proposed energy‐E‐skin has great potential for use as a next‐generation multifunctional artificial skin, self‐powered human–machine interface, wearable thin‐film power source, and so on.