Energy-constrained Wireless Networks Research Articles

An efficient hybrid energy harvesting protocol for cooperative NOMA systems: Error and outage performance

Cooperative non-orthogonal multiple access (CNOMA) has been recently adapted with energy harvesting (EH) to increase energy efficiency and extend the lifetime of energy-constrained wireless networks. In EH, two protocols are usually used for CNOMA, namely, power splitting (PS) and time switching (TS). In order to improve the existing EH protocols, this paper investigates a hybrid EH protocol-assisted CNOMA, which is a combination of the two aforementioned main existing EH protocols. The end-to-end bit error rate (BER) and outage probability (OP) expressions of users in our scheme are derived over Nakagami-m fading channels. For the sake of comparison and to highlight the achievable gains, the performance of the hybrid EH (HEH) protocol is compared with the benchmark schemes (i.e., existing EH protocols and no-EH). Based on extensive simulations, it is shown that the analytical results match perfectly with simulations which demonstrates the correctness of the derivations. Numerical results clearly indicate the superiority of the proposed scheme over the existing classical benchmarks. In addition, we discuss the optimum value of EH factors to minimize the error and outage in the proposed scheme and show that an optimum value can be obtained according to channel parameters.

Modeling and Performance Analysis of ECS-HTCARQ Protocol in Interference Scenario

To extend the lifetime of energy-constrained wireless networks, this paper proposes a three-node model of the wireless-powered cooperative communication network (WPCCN). The model consists of an energy-constrained source node, an energy-sufficient relay node, and a destination node and considers two different cochannel interference (CCI) sources at the relay and destination nodes. To ensure the reliability of data transmission, we introduce the cooperative automatic retransmission request (CARQ) protocol, propose the energy-constrained source that harvests and cooperates automatic retransmission request (ECS-HTCARQ) protocol in interference scenario, derive a closed-form expression for the outage probability under Rayleigh fading channels, and establish a discrete-time Markov chain (DTMC) model to analyze the system throughput. The relationship between parameters such as the energy harvesting time allocation factor and energy harvesting efficiency on the outage probability and the system throughput is obtained. Numerical results show that the difference in system throughput is small as the increasing number of transmissions at a high signal-to-interference ratio (SIR), but there is a significant reduction in the outage probability. Finally, the optimal value of the energy harvesting time allocation factor is given under this model.

Forwarding in Energy-Constrained Wireless Information Centric Networks.

Information Centric Networks (ICNs) have been considered one of the most promising candidates to overcome the disadvantages of host-centric architectures when applied to IoT networks, having the potential to address the challenges of a smart city. One of the foundations of a smart city is its sensory capacity, which is obtained through devices associated with the IoT concept. The more sensors spread out, the greater the ability to sense the city. However, such a scale demands high energy requirements and an effective improvement in the energy management is unavoidable. To improve the energy management, we are proposing an efficient forwarding scheme in energy-constrained wireless ICNs. To achieve this goal, we consider the type of devices, their internal energy and the network context, among other parameters. The proposed forwarding strategy extends and adapts concepts of ICNs, by means of packet domain analysis, neighbourhood evaluation and node sleeping and waking strategies. The proposed solution takes advantage of the neighbourhood to be aware of the moments to listen and forward packets in order to consistently address mobility, improving the quality of content delivery. The evaluation is performed by simulation with real datasets of urban mobility, one from the lagoon of “Ria de Aveiro” and the other from a vehicular network in the city of Porto. The results show that the proposed forwarding scheme resulted in significant improvements in network content availability, in the overall energy saving and, consequently, in the network lifetime.

Performance Analysis of Intelligent Reflecting Surface Aided Wireless Networks With Wireless Power Transfer

The low efficiency of wireless power transfer (WPT) poses a key challenge for energy-constrained wireless networks. To address this issue, in this letter, the integration of intelligent reflecting surface (IRS) into a WPT network is investigated. To this end, an accurate approximation for the probability density function of the end-to-end cascaded fading channel is presented. By leveraging the derived result, accurate closed-form expressions of the outage probability (OP) and average symbol error probability (ASER) are derived for the proposed IRS-aided WPT system. To gain further insight into the system performance, asymptotic closed-form expressions for the ASER and OP are further derived and interesting observations are reported. Particularly, our asymptotic analysis reveals that the achievable diversity in the underlying scenario is independent of the reflective elements of the IRS. The analytical derivations, corroborated by simulation results, demonstrate that IRSs can be promising candidates for the realization of a highly efficient power transfer enabled wireless network.

Reinforcement Learning Based Adaptive Resource Allocation for Wireless Powered Communication Systems

Wireless powered communication (WPC) is one of the promising techniques for future energy-constrained wireless networks. In this letter, we consider a WPC system composed of a hybrid access point and an energy harvesting node (EHN). In this system, we propose a reinforcement learning based adaptive resource allocation scheme that dynamically assigns the channel resources to minimize the outage probability of information transfer while satisfying the average power constraint at the EHN, which is formulated as a constrained Markov decision process (MDP) problem. To solve this challenging problem, we first transform the originally formulated problem into its equivalent unconstrained MDP with multi-objective. Then, to find the resource allocation policy, we propose a novel Q-learning algorithm. Numerical results demonstrate the superior performance and effectiveness of the proposed scheme.

OPCIO

Battery lifetime is one of the main challenges that impedes the deployment of energy-constrained wireless networks, such as unattended Internet-of-Things (IoT) systems. To prolong battery lifetime, the duty-cycle mode is utilized in many IoT systems, especially in environment monitoring Wireless Sensor Networks (WSN) and Low-Power Wide-Area Networks (LPWAN). In duty-cycle mode, devices transmit packets during the active phase, which lasts for a short time, and sleeps the rest of the time. Prior research mainly focuses on energy efficiency in the active phase; energy consumption during the sleep phase, however, is always ignored, as it is assumed to have little margin to be optimized. In this work, we reveal that sleep phase can become a significant battery consumer due to the misconfiguration of General-Purpose Input/Output (GPIO) pins of micro-controllers. We propose OPCIO, which incorporates a genetic algorithm to obtain energy-efficient GPIO configurations automatically to squeeze the energy waste during the sleep phase. We prototype OPCIO on off-the-shelf devices and evaluate it on two ARM devices. Experiment results show that OPCIO can effectively find multiple low-power configurations that prolong the lifespans up to 10×.

Design and Implementation of Genetic Algorithm Based Multi Coil (MC) Optimization Technique of Wireless Power Transfer to Biomedical Implants

Recent research is going on about the radio frequency energy harvesting technique or RF harvesting, we can convert the received RF signals into electricity. This technique becomes a solution to power energy-constrained wireless networks. Whereas, the energy-constrained wireless networks, have a limited lifetime which largely confines the network performance. In contrast, an RF energy harvesting network (RF-EHN) has a power supply. This paper therefore discuss the RF energy harvesting capability that allows the wireless devices to harvest energy from RF signals for processing and also can be transmitting the signal. The increasing demand of RF energy harvesting has introduced commercialized products, like (Power caster and Cota system). This paper proposes a Genetic algorithm based Multi coil (MC) optimization technique to optimize the circuit design of a WPT system.

Power Beacon-Assisted Energy Harvesting in a Half-Duplex Communication Network under Co-Channel Interference over a Rayleigh Fading Environment: Energy Efficiency and Outage Probability Analysis

In this time, energy efficiency (EE), measured in bits per Watt, has been considered as an important emerging metric in energy-constrained wireless communication networks because of their energy shortage. In this paper, we investigate power beacon assisted (PB) energy harvesting (EH) in half-duplex (HD) communication network under co-channel Interferer over Rayleigh fading environment. In this work, we investigate the model system with the time switching (TS) protocol. Firstly, the exact and asymptotic form expressions of the outage probability (OP) are analyzed and derived. Then the system EE is investigated and the influence of the primary system parameters on the system performance. Finally, we verify the correctness of the analytical expressions using Monte Carlo simulation. Finally, we can state that the simulation and analytical results are the same.

Robust Optimization for Energy Efficiency in MIMO Two-Way Relay Networks With SWIPT

Energy efficiency (EE) is a key issue in energy-constrained wireless networks because of the energy scarcity. In this paper, we present the robust energy-efficient optimization design for multiple-input–multiple-output two-way relay networks with simultaneous wireless information and power transfer, where the available channel state information is considered to be imperfect. We model the channel errors by using the norm bounded model, and aim to maximize the worst-case EE by jointly designing the precoders of the sources and relay, and the power splitting ratio of the relay under the worst-case transmit power constraints at the sources and relay. To solve the robust EE optimization problem, we propose an iterative optimization algorithm based on the weighted minimum mean-square-error method, where the $\mathcal {S}$ -procedure and sign-definiteness lemma are employed to eliminate the channel errors. To balance the performance and complexity, we propose a channel diagonalization algorithm based on the generalized singular value decomposition, which has lower complexity. The effectiveness of the proposed algorithms is shown by numerical results.

Minimizing the Energy Consumption of Wireless Sensor Network by Comparing the Performances of Maxweight and Minimum Energy Scheduling Algorithms

In this project we use MES algorithm is more favorable for dynamic link scheduling and network protocol designs in energy-constrained wireless networks such as wireless sensor networks which is well known to be throughput optimal. Before that we implement a novel scheduling method named Virtual Backbone Scheduling which schedules multiple overlapped backbones so that the network energy consumption is evenly distributed among all sensor nodes. In this way, the energy of all of the sensor nodes in the network is fully utilized, which in turn prolongs the network lifetime. Here the data is only forwarded by the backbone sensor nodes and other sensor nodes turn off the radios saves energy. The Energy Consumption is balanced by rotating the multiple backbones. Approximation algorithms are used for solving the MLBS problems. MES significantly reduces the energy consumption compared to the original MaxWeight algorithm. In addition, we analytically show that the MES algorithm is essentially energy optimal in the sense that the average energy expenditure of the MES algorithm can be pushed arbitrarily close to the global minimum solution.

M2M Communication Assessment in Energy-Harvesting and Wake-Up Radio Assisted Scenarios Using Practical Components.

Techniques for wireless energy harvesting (WEH) are emerging as a fascinating set of solutions to extend the lifetime of energy-constrained wireless networks, and are commonly regarded as a key functional technique for almost perpetual communications. For example, with WEH technology, wireless devices are able to harvest energy from different light sources or Radio Frequency (RF) signals broadcast by ambient or dedicated wireless transmitters to support their operation and communications capabilities. WEH technology will have increasingly wider range of use in upcoming applications such as wireless sensor networks, Machine-to-Machine (M2M) communications, and the Internet of Things. In this paper, the usability and fundamental limits of joint RF and solar cell or photovoltaic harvesting based M2M communication systems are studied and presented. The derived theoretical bounds are in essence based on the Shannon capacity theorem, combined with selected propagation loss models, assumed additional link nonidealities, diversity processing, as well as the given energy harvesting and storage capabilities. Fundamental performance limits and available capacity of the communicating link are derived and analyzed, together with extensive numerical results evaluated in different practical scenarios, including realistic implementation losses and state-of-the-art printed supercapacitor performance figures with voltage doubler-based voltage regulator. In particular, low power sensor type communication applications using passive and semi-passive wake-up radio (WuR) are addressed in the study. The presented analysis principles and results establish clear feasibility regions and performance bounds for wireless energy harvesting based low rate M2M communications in the future IoT networks.

IoT Communications Network for Wireless Power Transfer System State Estimation and Stabilization

Wireless energy harvesting has emerged as an appealing solution to prolong the lifespan of energy-constrained wireless networks and been regarded as a main functional unit for almost all perpetual communications. This paper proposes a channel coding-based Internet of Things communication network, and state estimation as well as stabilization algorithms for wireless power transfer systems. After modeling the energy harvesting module like wireless energy transfer systems as a state-space framework, Web-enabled smart sensors are deployed to obtain measurements. The sensing information is transmitted to the nearby base station for collection and digital communication under the condition of packet losses. A recursive systematic convolutional code is used to add redundancy into the quantize system states. After digital modulation, the signal is transmitted to a control center for system state estimation and stabilization. The optimal gain of the state estimation scheme is determined after minimizing the mean squared errors. Afterward, a stabilization algorithm is designed considering packet losses in the communication networks using the semidefinite programming approach. Furthermore, the convergence of the developed estimation algorithm is proved. Numerical simulation results demonstrate, considering packet loss, sensor faults, disturbances, and delay into account, that the proposed algorithms can estimate and stabilize the system states within a short period of time.

Research on the Energy Allocation Scheme Based on SWIPT Relaying System

Simultaneous wireless information and power transfer (SWIPT) is a promising communication solution for energy-constrained wireless network. While the interference affects the performance of the system, it also carries energy. In this paper, we investigate an amplify-and-forward (AF) relaying network. In the network, an energy-constrained relay harvests energy from the received RF signal. During the information transmission (IT) period, the relay uses the harvested energy to forward the signal. When the IT is interrupted for some reason, such as strong interference, the relay stores the harvested energy into the energy storage till the interference ends. Particularly, in the IT period, the relay allocates the energy of its storage to the blocks of the IT. Based on the time switching (TS) architecture, the system rates of two energy allocation cases are discussed. It is proved that the scheme based on the energy-allocated-evenly (EAE) is the optimal solution of the system rate maximization, and the mathematical expressions of the system rate based on the EAE scheme is obtained. Then, we discuss the influence of the EAE scheme on the system rate, and the numerical analysis provides practical insights into the effect of two system parameters, namely, interference power and interference factor on the performance of wireless energy harvesting (EH) and IT using AF relay. The results show that the proposed EAE scheme can effectively improve the relaying system rate under an interference channel.

Cooperative Strategies for Wireless-Powered Communications: An Overview

Radio frequency (RF) energy transfer and harvesting has been intensively studied recently as a promising approach to significantly extend the lifetime of energy-constrained wireless networks. This technique has a great potential to provide relatively stable and continuous RF energy to devices wirelessly; it thus opened a new research paradigm, termed wireless-powered communication (WPC), which has raised many new research opportunities with wide applications. Among these, the design and analysis of cooperative schemes towards efficient WPC have attracted tremendous research interests nowadays. This article provides an overview of various cooperative strategies for WPC, with particular emphasis on relaying protocols for wireless-powered cooperative communications, cooperative spectrum sharing schemes for cognitive wireless-powered networks, and cooperative jamming strategies towards wireless-powered secure communications. We also identify several interesting research directions in this area before concluding this article.

−31 dBm sensitivity high efficiency rectifier for energy scavenging

RF energy scavenging is capable in converting RF signals into electricity and has become a promising solution to power energy-constrained wireless networks. However, it has low power conversion efficiency especially when the harvested RF power is small. For this reason, we propose an enhanced differential-drive rectifier to improve the efficiency and the sensitivity of rectifier for energy scavenging applications. The proposed rectifier achieves dynamically controlled threshold voltage and reduces leakage current in the transistors through DTMOS transistor in differential-drive topology. The voltage boosting circuit further increases the sensitivity through step up the input signal before the signal enters the rectifier. The decoupling capacitor shunts the noise of the input signal before the signal is injected into the cross-connected gate reducing the voltage drop and maintaining the PCE of the rectifier. The rectifier is designed based on the 0.18 µm Silterra CMOS process technology. Effects of decoupling capacitors, voltage boosting circuit and output load on PCE of the rectifier have been evaluated. Technology scaling and parasitic effects to the rectifier have also been presented. Performance of N-stages proposed rectifier has been compared with the conventional BTMOS rectifier. The proposed method achieves the highest sensitivity of −31 dBm for 1, 3 and 5 stages rectifiers without the need of off-chip load capacitor.

Editorial for the Special Issue on “Wireless Energy Harvesting for Future Wireless Communications”

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Availability of Ambient RF Energy in d-Dimensional Wireless Networks

Radio frequency (RF) enabled energy harvesting has garnered increasingly broad applications in energy-constrained wireless networks. In this context, the actual available energy is constrained by the harvesting threshold of RF harvesters. In this paper, we first propose two new metrics, effective energy harvesting probability (EEHP) and spatial mean harvestable energy (SMHE) to characterize the availability of ambient RF energy. Assuming that the transmitters are spatially distributed according to a d-dimensional homogeneous Poisson point process (HPPP), we derive the distributions of the ambient RF energy for networks, from the perspective of information receivers, with and without interference control (IC). The corresponding EEHP and SMHE are given in integral forms for the case with IC and inverse Laplace transform form for the case without IC, respectively. For a special case where the dimension to path loss ratio equals 0.5, closed-form exact/approximate expressions for EEHP and SMHE are derived. Analytical results are validated by Monte Carlo simulations. Numerical results with distinct network parameters indicate that the harvesting threshold always has a significant effect on the EEHP, while the impact on SMHE can be ignored as the transmitter density increases. The general unified framework considered in this paper expands the applicability of the derived results to arbitrary dimensional networks.

Energy-Aware Routing for SWIPT in Multi-Hop Energy-Constrained Wireless Network

Simultaneous wireless information and power transfer (SWIPT) transmits information and powers wireless nodes with the same radio frequency signal. It can prolong the life time of the energy-constrained wireless nodes. Current works of SWIPT focus on one-hop and two-hop wireless network. In order to verify the performance of SWIPT in multi-hop energy-constrained wireless network (MECWN) where the energy harvested by the receiver node can be as an energy compensation for data forwarding, this paper concurrently considers SWIPT and routing selection in MECWN. To reduce the energy consumption, we first formulate the information and energy allocation problem of link in a forwarding path, which is dependent on the next-hop node, and solve it by an iterative allocation algorithm. A novel routing metric evaluates the energy consumption of link transmitted with or without SWIPT. The energy-aware SWIPT routing algorithm allocates the information and energy of link with allocation algorithm during path finding process. To the best of our knowledge, this is the first solution that takes account of SWIPT and routing in MECWN. Our performance studies demonstrate that our proposed algorithms can effectively exploit those node resources whose energy are not enough and significantly decrease the energy consumption.

Stochastic Wireless Powered Communication Networks With Truncated Cluster Point Process

Wireless powered communication network (WPCN) can prolong the lifetime of energy constrained wireless networks in a sustainable way without replacing or recharging the batteries. A popular approach for analyzing stochastic WPCN is to model the location of different nodes according to a homogeneous Poisson point process. However, it is more reasonable to place user equipments (UEs) around a power beacon considering the inefficiency and difficulty of wireless energy transfer. This motivates us to model the location of UEs as a cluster point process (CPP). With practical transmission range considered, the truncated Matern CPP and Thomas CPP are proposed. The performances of coverage probability and the average received signal-to-interference-plus-noise ratio are derived. Then, we optimize the time allocation fraction to maximize the average network throughput by pseudo-convexity optimization, and the closed-form optimal results are presented.

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN’s achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.