Non-energy Harvesting Research Articles

On the Performance of SLIPT-Enabled DF Relay-Aided Hybrid OW/RF Network

Thisarticle investigates a decode-and-forward (DF) relay-aided hybrid optical wireless/radio frequency (OW/RF) network. The OW subsystem exploits simultaneous transfer of energy and information to increase the system’s lifespan. The end-to-end signal-to-noise ratio statistics are derived using the optical energy transfer at the DF relay. For the proposed DF relay-aided hybrid OW/RF system, Malaga ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {M}$</tex-math></inline-formula> )-distribution with non-zero boresight pointing/misalignment error is considered to model the OW channel, and Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m$</tex-math></inline-formula> model is assumed for the RF channel. In particular, analytical expressions of outage probability (OP), average bit error rate (BER), ergodic capacity, and effective capacity are derived in terms of Meijer’s G-function. To gain additional insights, we also derive the asymptotic expressions of average BER, OP, and effective capacity and estimate the diversity order mathematically. The impact of various system and channel parameters like dc bias, turbulence, weather conditions, and visibility is explored on the system performance. Through numerical results, we show that the proposed DF relay-aided and simultaneous lightwave information and power transfer (SLIPT) -enabled hybrid OW/RF system surpasses its amplify-and-forward-based counterpart. The superiority of the proposed system over non-energy harvesting (EH) and RF-EH-based hybrid OW/RF system is also shown. The analytical formulations are validated with the Monte-Carlo simulations.

Learning to Charge RF-Energy Harvesting Devices in WiFi Networks

In this paper, we consider a solar-powered Access Point (AP) that is tasked with supporting both non-energy harvesting or legacy data users such as laptops, and devices with Radio Frequency (RF)-energy harvesting and sensing capabilities. We propose two solutions that enable the AP to manage its harvested energy via transmit power control and also ensure devices perform sensing tasks frequently. Advantageously, our solutions are suitable for current wireless networks and do not require perfect channel gain information or non-causal energy arrival at devices. The first solution uses a deep Q-network (DQN) whilst the second solution uses Model Predictive Control (MPC) to control the AP's transmit power. Our results show that our DQN and MPC solutions improve energy efficiency and user satisfaction by respectively 16% to 35%, and 10% to 42% as compared to competing algorithms.

Unification of RF energy harvesting schemes under mixed Rayleigh-Rician fading channels

In this work, a generalized approach is proposed to review the performance of relaying designs with energy harvesting capability. The unified modeling of generalized energy harvesting relaying (GEHR) design covers the non-energy harvesting designs and the well-known energy harvesting designs, i.e., time-based relaying (TR) and power-based relaying (PR). Moreover, the hybrid of both TR and PR designs is also catered. We find the mathematical representations for the outage probability, ergodic capacity and average throughput in Rayleigh fading channels for amplify-and-forward (AF) and decode-and-forward (DF) relaying modes. The closed-form expressions are derived for the outage probability. To validate that GEHR design is a generalization of TR and PR designs, we study the individual cases of GEHR design from the perspectives of schematic diagram, signal analysis and the performance evaluation parameters comparison. Furthermore, the GEHR design is studied for the mixed Rayleigh-Rician fading channels. We considered two sub-cases of mixed fading, i.e., in case 01, source to relay (SR) link is considered as Rayleigh channel and relay to destination (RD) link is considered as a Rician channel. Conversely, in case 02, SR link is taken as Rician channel and RD link is a Rayleigh channel. We find the mathematical expressions for the ergodic capacity, outage probability and average throughput for DF and AF relaying for both cases of mixed fading channels. The analytical results in both channel configurations are presented for throughput and verified using extensive Monte-Carlo simulations. The results show that the proposed GEHR design can be set to work as not only for the conventional TR and PR designs but also for hybrid of them. Furthermore, with some slight modifications in the proposed design, it can work as a conventional non-energy harvesting cooperative relaying model.

Energy-Efficient LoRaWAN for Industry 4.0 Applications

Thanks to its inherent capabilities (such as fairly long radio coverage with extremely low power consumption), long-range wide area network (LoRaWAN) can support a wide spectrum of low-rate use-cases in Industry 4.0. In this article, both plain and energy harvesting (EH) industrial environments are considered to study the performance of LoRa radios for industrial automation. In the first instance, a model is presented to investigate LoRaWAN in Industry 4.0 in terms of battery life, battery replacement cost, and damage penalty. Then, the EH potential, available within an Industry 4.0, is highlighted to demonstrate the impact of harvested energy on the battery life and sensing interval of LoRa motes deployed across a production facility. The key outcome of these investigations is the cost trade-off analysis between battery replacement and damage penalty along different sensing intervals which demonstrates a linear increase in aggregate cost up to £1500 in case of 5 min sensing interval in the plain (nonenergy harvesting) industrial environment while it tends to decrease after a certain interval up to five times lower in EH scenarios. In addition, the carbon emissions due to the presence of LoRa motes and the annual CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emission savings per node have been recorded up to 3 kg/kWh when fed through renewable energy sources. The analysis presented herein could be of great significance toward a green industry with cost and energy efficiency optimization.

The Energy-Aware Matrix Completion-Based Data Gathering Scheme for Wireless Sensor Networks

In the Wireless Sensor Networks (WSNs), ensuring long-term survival of the sensor devices is crucial, especially for non-energy harvesting networks where the sensors have to deal with the available limited power. Thus, there is a huge need to efficiently select, in each time-slot, a small set of source nodes to monitor the network area and deliver their data to the sink. Note that there is a trade-off between energy efficiency, achieved through data-compression, and the informative quality received by the sink. Moreover, although applying a high data compression ratio extremely reduces the overall network energy consumption, the network lifetime is not necessarily extended due to the uneven energy depletion of the nodes' batteries. To this end, in this paper, we propose the Energy-Aware Matrix Completion based data gathering approach (EAMC), which designates the active nodes according to their residual energy levels. To collect data readings, the proposed EAMC relies on a nodes clustering phase and a MC based data sampling. Then, the interpolation of all the missing data is performed by the sink thanks to a Three-stage MC based recovery framework. Since we are interested in high data loss scenarios, the limited amount of delivered data must be sufficient in terms of informative quality it holds in order to reach a satisfactory recovery accuracy for the entire data. Hence, the EAMC selects the nodes depending on their inter-correlation as well as the network energy efficiency, with the use of a combined energy-aware and correlation-based metric. This introduced active node cost function changes with the type of application one wants to perform with the intention to reach a longer lifespan for the network. Therewith, the numerical results show that the EAMC achieves an attractive and competitive trade-off between the data reconstruction quality and the network lifetime for all the investigated scenarios.

Joint Relay Selection, Full-Duplex and Device-to-Device Transmission in Wireless Powered NOMA Networks

This paper investigates non-orthogonal multiple access (NOMA), cooperative relaying, and energy harvesting to support device-to-device (D2D) transmission. In particular, we deploy multiple relay nodes and a cell-center D2D device which can operate in full-duplex (FD) or half-duplex (HD) mode to communicate with a cell-edge D2D device. In this context, there are two possible signal transmission paths from the base station (BS) to the far D2D user either through multiple decode-and-forward (DF) relay nodes or through a near D2D user. Consequently, we propose three schemes to support D2D-NOMA systems, namely non-energy harvesting relaying (Non-EHR), energy harvesting relaying (EHR) and quantize-map-forward relaying (QMFR) schemes. For each of the proposed schemes, closed-form expressions of the outage probabilities of both D2D users are derived. Extensive Monte-Carlo simulation results are provided to validate the derived analytical expressions. The study results show that the proposed schemes can improve the outage performance compared to conventional orthogonal multiple access (OMA) schemes. Moreover, it is shown that the Non-EHR scheme achieves the best outage performance among the three considered schemes.

Outage and Throughput Analysis of Spectrum Sharing Cognitive Radio Network Incorporating Energy Harvesting Hybrid Relay

In this paper, cooperative spectrum sharing in cognitive radio (CR) network is incorporated with multi-antenna based RF energy harvesting relays (EH). The performance has been analyzed in the presence of multiple primary users. The relays can harvest energy from source signal and interference from primary transmitter. The relays follow adaptive hybrid protocol (AHR) for forwarding the received signal from source to destination. Outage probability and achievable throughput have been analyzed using a time-splitting relaying (TSR) scheme at the destination where best relay selection (BRS) strategy is used. The outage performances of energy harvesting and non-energy harvesting model have been compared. Throughput and outage performance comparison for AF, DF and AHR have been analyzed. The effect of the number of primary users is also investigated. A trade-off is shown between the number of relays and the number of antennas to achieve the desired throughput. The results depict that the use of energy harvesting strategy in cognitive radio network can result in an energy-efficient solution for future wireless communication.

M86 NOVEL MUTATION IN PPEF2 REPORTED IN A FAMILY AFFECTED WITH SCHIZOPHRENIA: WHOLE GENOME SEQUENCING STUDY

In this paper, cooperative non-orthogonal multiple access (NOMA) network is investigated to aid device-to-device (D2D) communication. In such D2D NOMA, Amplify and Forward (AF) and Decode and Forward (DF) mode are deployed to signal processing at relay who intends to serve NOMA far user. To ensure the quality of service (QoS) for the NOMA devices, a minimum rate requirement is pre-defined for each device. Two main schemes are considered insightfully: i) The first scenario is that the first device intends to communicate with the second device through the assistance of AF/DF-assisted base station (BS), where equips individual power; and ii) The second scenario is that the wireless powered device is able to communicate with non-energy harvesting device. Because of the QoS requirement, it is first necessary to determine performance gap in two folds: relay and direct mode; non-wireless power transfer (NWPT) scenario and wireless power transfer (WPT) scenario, by comparing the outage performance with the required power for satisfying the QoS of the devices. To further evaluation, we extend our analysis on non-linear energy harvesting policy and multiple NOMA far users which are deployed in such D2D transmission. If feasible, a closed-form solution is provided for system performance evaluation. Numerical results are presented to validate the effectiveness of the proposed D2D transmission strategies.

Device-to-device transmission modes in NOMA network with and without Wireless Power Transfer

In this paper, cooperative non-orthogonal multiple access (NOMA) network is investigated to aid device-to-device (D2D) communication. In such D2D NOMA, Amplify and Forward (AF) and Decode and Forward (DF) mode are deployed to signal processing at relay who intends to serve NOMA far user. To ensure the quality of service (QoS) for the NOMA devices, a minimum rate requirement is pre-defined for each device. Two main schemes are considered insightfully: i) The first scenario is that the first device intends to communicate with the second device through the assistance of AF/DF-assisted base station (BS), where equips individual power; and ii) The second scenario is that the wireless powered device is able to communicate with non-energy harvesting device. Because of the QoS requirement, it is first necessary to determine performance gap in two folds: relay and direct mode; non-wireless power transfer (NWPT) scenario and wireless power transfer (WPT) scenario, by comparing the outage performance with the required power for satisfying the QoS of the devices. To further evaluation, we extend our analysis on non-linear energy harvesting policy and multiple NOMA far users which are deployed in such D2D transmission. If feasible, a closed-form solution is provided for system performance evaluation. Numerical results are presented to validate the effectiveness of the proposed D2D transmission strategies.

Fair and Low Complexity Node Selection in Energy Harvesting Wireless Sensor Networks

The use of energy harvesting in wireless sensor networks is an emerging wireless communication technology with a wide range of applications. Maximizing the number of samples collected by the sensor nodes and transmitted to the sink is a key element in order to minimize uncertainties for those applications. This work considers energy harvesting sensor nodes that are transmitting to a nonenergy harvesting sink. Using a zero-forcing (ZF) receiver, the sink selects the largest possible set of transmitting sensor nodes to maximize the received quantity of information while the selected transmissions should satisfy a given quality of service defined by signal-to-noise ratio and certain fairness constraint. The maximization problem is formulated as an integer nonlinear program and it is proved to be NP-hard. Thus, two low complexity and efficient heuristic algorithms are proposed to solve this problem. Two other variants are also proposed in order to improve the system fairness. We demonstrate via simulations in a node selection context that the proposed algorithms which consider the energy state of the system better exploit the full system resources compared to state-of-the-art algorithms which only consider channel conditions. Interestingly, simulation results show that the performance of the proposed algorithms varies as a function of the energy availability. Hence, they are adapted to the energy harvesting context.

Video multicast cooperative communication in 5G systems with radio frequency energy harvesting

In this paper, the performance of radio frequency energy harvesting cooperative multicast communication is analyzed in terms of outage probability. The multicast communication between base station (BS) and multiple destinations is assisted by one energy harvesting relay chosen from multiple energy harvesting relays. The relays harvest energy from the BS transmissions to be able to transmit for cooperation. We propose two power splitting approaches at the relays for energy harvesting. The first approach splits the received signal at the relays into two portions and send them to decoding/energy harvesting circuitry, simultaneously. In the second approach, the received signal during any receiving time is either sent to the information decoding circuitry or energy harvesting circuitry depending on the strength of the received signal. Analytical expressions of outage probability for these two power splitting approaches are derived. The derived expressions are validated by comparing them with the simulation results. Further, the outage probability of our proposed energy harvesting cooperative multicast system is almost equal to the non-energy harvesting cooperative multicast system.

Interference-Aided Energy Harvesting: Cognitive Relaying With Multiple Primary Transceivers

We consider a spectrum sharing scenario where a secondary transmitter (ST) communicates with its destination via a decode-and-forward secondary relay (SR) in the presence of interference from multiple primary transmitters. The SR harvests energy from received radio-frequency signals that include primary interference and uses it to forward the information to the secondary destination. The relay adopts a time switching policy that switches between energy harvesting and information decoding over the time. Under the primary outage constraints and the peak power constraints at both ST and SR, to determine the average secondary throughput, we derive exact analytical expressions for the secondary outage probability and the ergodic capacity, which characterize the delay-limited and the delay-tolerant transmissions, respectively. We also investigate the effects of the number of primary transceivers and the peak power constraints on the optimal energy harvesting time that maximizes the secondary throughput. By utilizing the primary interference as an energy source, the secondary network achieves a better throughput performance compared to the case where the primary interference is ignored for energy harvesting purpose. Finally, we consider a case where ST also harvests energy from primary transmissions and compare its throughput performance with that of the non-energy harvesting ST case.