Sensing Throughput Optimization in Fading Cognitive Multiple Access Channels With Energy Harvesting Secondary Transmitters

The paper investigates the problem of maximizing expected sum throughput in a fading multiple access cognitive radio network when secondary user (SU) transmitters have energy harvesting capability, and perform cooperative spectrum sensing. We formulate the problem as maximization of sum-capacity of the cognitive multiple access network over a finite time horizon subject to a time averaged interference constraint at the primary user (PU) and almost sure energy causality constraints at the SUs. The problem is a mixed integer non-linear program with respect to two decision variables namely spectrum access decision and spectrum sensing decision, and the continuous variables sensing time and transmission power. In general, this problem is known to be NP hard. For optimization over these two decision variables, we use an exhaustive search policy when the length of the time horizon is small, and a heuristic policy for longer horizons. For given values of the decision variables, the problem simplifies into a joint optimization on SU \textit{transmission power} and \textit{sensing time}, which is non-convex in nature. We solve the resulting optimization problem as an alternating convex optimization problem for both non-causal and causal channel state information and harvested energy information patterns at the SU base station (SBS) or fusion center (FC). We present an analytic solution for the non-causal scenario with infinite battery capacity for a general finite horizon problem.We formulate the problem with causal information and finite battery capacity as a stochastic control problem and solve it using the technique of dynamic programming. Numerical results are presented to illustrate the performance of the various algorithms

Design and simulation of dual-band RF energy harvesting antenna for WSNs

[EN] Radio frequency energy harvesting is attracting an increasing deal of attention in order to provide power to the electronic devices, including Wireless Sensor Networks. In this context, we focus on ambient radiofrequency energy available in the ambient environment. The receiving antenna is the main element of radiofrequency harvester, as it has to capture the RF energy from the radiating sources. Our work provides a new design of the receiving antenna to harness RF energy more effectively. Several simulations and optimizations are performed in order to maximize the antenna gain around the Wi-Fi bandwidth (2.45 GHz and 5 GHz). Variation of the return loss passes below -29 dB for 5 GHz frequencies and the radiation shape shows a quasi-omnidirectional pattern in Wi-Fi bands. The dual band antenna proposed is very interesting for the RF harvesting energy system, meeting the desired criteria to maximize the ambient harvested RF energy.This research was supported in part by EMMAG Program, 2014, funded by the European Commission.Bakkali, A.; Pelegrí Sebastiá, J.; Sogorb Devesa, T.; Bou Escrivà, A.; Lyhyaoui, A. (2017). Design and simulation of dual-band RF energy harvesting antenna for WSNs. Energy Procedia. 139:55-60. doi:10.1016/j.egypro.2017.11.172S556013

Radio Frequency Energy Harvesting - Sources and Techniques

Energy harvesting technology is attracting huge attention and holds a promising future for generating electrical power. This process offers various environmentally friendly alternative energy sources. Especially, radio frequency (RF) energy has interesting key attributes that make it very attractive for low-power consumer electronics and wireless sensor networks (WSNs). Ambient RF energy could be provided by commercial RF broadcasting stations such as TV, GSM, Wi-Fi, or radar. In this study, particular attention is given to radio frequency energy harvesting (RFEH) as a green technology, which is very suitable for overcoming problems related to wireless sensor nodes located in harsh environments or inaccessible places. The aim of this paper is to review the progress achievements, the current approaches, and the future directions in the field of RF harvesting energy. Therefore, our aim is to provide RF energy harvesting techniques that open the possibility to power directly electronics or recharge secondary batteries. As a result, this overview is expected to lead to relevant techniques for developing an efficient RF energy harvesting system

Survey of Energy Harvesting Technologies for Wireless Sensor Networks

Energy harvesting (EH) technologies could lead to self-sustaining wireless sensor networks (WSNs) which are set to be a key technology in Industry 4.0. There are numerous methods for small-scale EH but these methods differ greatly in their environmental applicability, energy conversion characteristics, and physical form which makes choosing a suitable EH method for a particular WSN application challenging due to the specific application-dependency. Furthermore, the choice of EH technology is intrinsically linked to non-trivial decisions on energy storage technologies and combinatorial architectures for a given WSN application. In this paper we survey the current state of EH technology for small-scale WSNs in terms of EH methods, energy storage technologies, and EH system architectures for combining methods and storage including multi-source and multi-storage architectures, as well as highlighting a number of other optimisation considerations. This work is intended to provide an introduction to EH technologies in terms of their general working principle, application potential, and other implementation considerations with the aim of accelerating the development of sustainable WSN applications in industry

Integrated Data and Energy Communication Network: A Comprehensive Survey

OAPA In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal – charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice