Optimal Energy Harvesting Time Research Articles

Maximizing the Sum-Rate of Secondary Cognitive Radio Networks by Jointly Optimizing Beamforming and Energy Harvesting Time

In this paper, we consider an energy harvesting (EH) cooperative cognitive radio network (CCRN) framework, in which the primary network (consisting of a transmitter-receiver pair) shares both energy and spectrum with the secondary network (consisting of two transceivers and multiple amplify-and-forward (AF)-based relays). Since the relays have no power source, they periodically switch between the EH and information transmission (IT) tasks. In particular, we apply a sum-rate maximization strategy to jointly obtain the optimal EH time allocation factor and distributed beamforming coefficients that achieve the best system performance for the secondary network under the individual EH power constraints at relays and an interference power constraint at the primary receiver. Although the formulated optimization problem is non-convex and complicated, we devise an efficient iterative scheme by applying the semi-definite relaxation (SDR) technique followed by the successive upper-bound minimization (SUM) strategy. Our simulation results confirm that the proposed method is spectrally and energy efficient.

Deep Reinforcement Learning for Physical Layer Security Enhancement in Energy Harvesting Based Cognitive Radio Networks

The paper studies the secrecy communication threatened by a single eavesdropper in Energy Harvesting (EH)-based cognitive radio networks, where both the Secure User (SU) and the jammer harvest, store, and utilize RF energy from the Primary Transmitter (PT). Our main goal is to optimize the time slots for energy harvesting and wireless communication for both the secure user as well as the jammer to maximize the long-term performance of secrecy communication. A multi-agent Deep Reinforcement Learning (DRL) method is proposed for solving the optimization of resource allocation and performance. Specifically, each sub-channel from the Secure Transmitter (ST) to the Secure Receiver (SR) link, along with the jammer to the eavesdropper link, is regarded as an agent, which is responsible for exploring optimal power allocation strategy while a time allocation network is established to obtain optimal EH time allocation strategy. Every agent dynamically interacts with the wireless communication environment. Simulation results demonstrate that the proposed DRL-based resource allocation method outperforms the existing schemes in terms of secrecy rate, convergence speed, and the average number of transition steps.

Optimal resource allocation method for energy harvesting based underlay Cognitive Radio networks.

This paper proposes an optimal resource allocation method. The method is to maximize the Energy Efficiency (EE) for an Energy Harvesting (EH) enabled underlay Cognitive Radio (CR) network. First, we assumed the Secondary Users (SUs) can harvest energy from the surrounding Radio Frequency (RF) signals. Then, we modelled the EE maximisation problem as a joint time and power optimization model. Next, the optimal EH time allocation factor can be calculated. After that the optimal power allocation strategy can be obtain by the fractional programming and Lagrange multiplier method. Finally simulation results show that the proposed iterative method can be better performance advantages compared with the exhaustive method and genetic algorithm. And the EE of this system model is significantly improved compared to the EE model without considering EH.

Intelligent reflecting surface empowered WPCN system over generalized κ−μ$$ \kappa -\mu $$ fading channels: Performance analysis and optimization

AbstractIntelligent reflecting surfaces (IRS), which dynamically modify the incident electromagnetic wave propagation characteristics, are appealing as a potential candidate to improve the spectral and energy efficiency of future wireless communication networks. In this paper, we investigate the performance of an IRS‐enabled wireless powered communication network (WPCN), which consists of a dedicated power source (PS), an energy‐constrained wireless device (WD), and a data access point (DAP). Due to energy limitations, WD first performs energy harvesting (EH) operation through the radio‐frequency (RF) signal supplied by the PS and then uses this energy to transmit its information to DAP. In this system setup, an IRS module is employed at both PS and DAP, respectively, in order to enhance the wireless energy transfer and wireless information transfer efficiency. For the underlying system model, we develop a unified performance evaluation framework with regard to outage probability, average throughput, effective throughput, and average, by assuming a generalized fading channels. In addition, we also present an asymptotic analysis, under a high signal‐to‐noise ratio assumption, which helps us to understand the system behavior deeply. Furthermore, an optimal EH time duration is developed for the proposed model to achieve maximum system throughput. The numerical simulation results demonstrate that the IRS‐enabled wireless transmission mechanisms for the WPCN system help to boost the overall performance significantly compared to conventional WPCN networks. All the derived numerical results are verified with Monte‐Carlo simulation results.

Intelligent Reflecting Surface assisted RF Energy Harvesting Mobile Edge Computing NOMA Networks: Performance Analysis and Optimization

In this paper, we focus on the performance analysis and optimization of an RF energy harvesting (EH) mobile edge computing (MEC) network by the assistance of the intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) schemes. Specifically, a pair of users harvest RF energy from a hybrid access point (HAP) and offloads their tasks to the MEC server at HAP through wireless links by employing an IRS-aided and uplink NOMA scheme. To evaluate the performance of this proposed system, the closed-form expressions of successful computation and energy transfer efficiency probabilities are derived. We further formulate a multi-objective optimization problem and propose an algorithm to find the optimal energy harvesting time switching ratio value to achieve the best performance, namely SENSGA-II. Moreover, the impacts of the network parameters are provided to draw helpful insight into the system performance. Finally, the Monte-Carlo simulation results are shown to confirm the correctness of our analysis. The results have shown that the deployment of IRS can improve the performance of this considered RF EH NOMA system by increasing the number of reflecting elements.

System Performance Analysis for an Energy Harvesting IoT System Using a DF/AF UAV-Enabled Relay with Downlink NOMA under Nakagami-m Fading.

This paper investigates system performance in the Internet of Things (IoT) with an energy harvesting (EH) unmanned aerial vehicle (UAV)-enabled relay under Nakagami-m fading, where the time switching (TS) and adaptive power splitting (APS) protocols are applied for the UAV. Our proposed system model consists of a base station (BS), two IoT device (ID) clusters (i.e., a far cluster and a near cluster), and a multiantenna UAV-enabled relay (UR). We adopt a UR-aided TS and APS (U-TSAPS) protocol, in which the UR can dynamically optimize the respective power splitting ratio (PSR) according to the channel conditions. To improve the throughput, the nonorthogonal multiple access (NOMA) technique is applied in the transmission of both hops (i.e., from the BS to the UR and from the UR to the ID clusters). The U-TSAPS protocol is divided into two phases. In the first phase, the BS transmits a signal to the UR. The UR then splits the received signal into two streams for information processing and EH using the APS scheme. In the second phase, the selected antenna of the UR forwards the received signal to the best far ID (BFID) in the far cluster and the best near ID (BNID) in the near cluster using the decode-and-forward (DF) or amplify-and-forward (AF) NOMA scheme. We derive closed-form expressions for the outage probabilities (OPs) at the BFID and BNID with the APS ratio under imperfect channel state information (ICSI) to evaluate the system performance. Based on these derivations, the throughputs of the considered system are also evaluated. Moreover, we propose an algorithm for determining the nearly optimal EH time for the system to minimize the OP. In addition, Monte Carlo simulation results are presented to confirm the accuracy of our analysis based on simulations of the system performance under various system parameters, such as the EH time, the height and position of the UR, the number of UR antennas, and the number of IDs in each cluster.

On the Capacity of Full‐Duplex AF/DF Relay System with Energy Harvesting for Vehicle‐to‐Vehicle Communications

This paper studies the ergodic capacity (EC) of full‐duplex (FD) amplify‐and‐forward (AF) and decode‐and‐forward (DF) relay system with energy harvesting (EH) for vehicle‐to‐vehicle (V2V) communications. Unlike previous works on FD‐EH systems, we consider the case that both relay and destination are mobile vehicles while the source is a static base station. We mathematically derive the exact closed‐form expressions of ECs of both AF and DF protocols of the considered FD‐EH‐V2V relay system over cascade (double) Rayleigh fading. Our numerical results show that the ECs in the case of the V2V communication system are reduced compared to those in the case of stationary nodes. Also, with a specific value of residual self‐interference (RSI), the ECs of the considered FD‐EH‐V2V relay system can be higher or lower than those of half‐duplex‐ (HD‐) EH‐V2V system, depending on the average transmission power of the source. Furthermore, when the transmission power of the source and RSI are fixed, the ECs of the considered system can achieve peak values by using optimal EH time duration. On the other hand, the ECs of both AF and DF protocols reach the capacity floors in the high signal‐to‐noise ratio (SNR) regime due to the RSI impact. Also, the effect of RSI dominates the impact of cascade Rayleigh fading in the high SNR regime. Finally, we validate our analysis approach through Monte‐Carlo simulations.

Stochastic Latency Guarantee in Wireless Powered Virtualized Sensor Networks

How to guarantee the data rate and latency requirement for an application with limited energy is an open issue in wireless virtualized sensor networks. In this paper, we integrate the wireless energy transfer technology into the wireless virtualized sensor network and focus on the stochastic performance guarantee. Firstly, a joint task and resource allocation optimization problem are formulated. In order to characterize the stochastic latency of data transmission, effective capacity theory is resorted to study the relationship between network latency violation probability and the transmission capability of each node. The performance under the FDMA mode and that under the TDMA mode are first proved to be identical. We then propose a bisection search approach to ascertain the optimal task allocation with the objective to minimize the application latency violation probability. Furthermore, a one-dimensional searching scheme is proposed to find out the optimal energy harvesting time in each time block. The effectiveness of the proposed scheme is finally validated by extensive numerical simulations. Particularly, the proposed scheme is able to lower the latency violation probability by 11.6 times and 4600 times while comparing with the proportional task allocation scheme and the equal task allocation scheme, respectively.

Optimal Resource Allocation for Wireless Powered Sensors: A Perspective From Age of Information

We investigate a wireless powered sensor network, in which multiple sensors generate data and send their data to a base station (BS) periodically. Each sensor first harvests energy from the BS via wireless power transfer and then uses its available energy to transmit to the BS its data. We target minimal average age of information, by optimizing the energy harvesting time and the bandwidth allocation during the sensors’ transmissions. The research problem is hard to solve, as some notations in the problem do not have a closed-form expression. To optimally solve the problem, we first show that there is a one-to-one mapping from the energy harvesting time to the bandwidth allocation. We also develop a method to obtain the bandwidth allocation vector corresponding to each value of the energy harvesting time. Then we get the optimal energy harvesting time by investigating and comparing different sub-regions of energy harvesting time. Numerical results show optimality of our solution and its performance gain over a benchmark scheme based on the traditional threshold-based method.

On the performance of roadside unit-assisted energy harvesting full-duplex amplify-and-forward vehicle-to-vehicle relay systems

This paper considers the performance of a full-duplex (FD) vehicle-to-vehicle (V2V) relay system where the relay uses amplify-and-forward (AF) protocol and harvests the energy from the radio frequency (RF) signals transmitted by source. Unlike previous reports, we investigate the case that both relay and destination are moving vehicles. Therefore, the channel between source and relay is Rayleigh fading while the channel between relay and destination is cascade (double) Raleigh fading. In addition, both fixed and variable gains are used at the FD relay. Based on mathematical analysis, we successfully derive the exact closed-form expressions of the outage probability (OP) and symbol error probability (SEP) to evaluate the system performance. Monte-Carlo simulations are exploited to demonstrate the correctness of all derived mathematical expressions. Numerical results clearly indicate that the OP and SEP performance of the considered energy harvesting (EH)-FD-V2V relay system with variable gain is much better than that with fixed gain. Moreover, the OP and SEP performance are strongly impacted by residual self-interference (RSI) due to the incomplete noise cancellation during the FD transmission. Besides the RSI, the OP and SEP performance is greatly reduced because of the cascade Rayleigh fading. We also observe that there is an optimal EH time duration to minimize the OP and SEP and this optimal value is different for fixed and variable gains. Therefore, from the transmission power of source and the type of gains used at FD relay, we can choose a suitable time EH time duration to get the best system performance.

On the Throughput of Interference-Based Wireless Powered Communications With Receive Antenna Selection

We propose an interference-based wireless powered communication system in which an energy constrained source harvests energy from a single dominant co-channel interferer and then transmits information to a destination equipped with N receive antennas. Assuming interference dominates noise power at the destination and the receive antenna that maximizes the signal-to-interference ratio is selected, we investigate the average throughput for the delay-limited and delay-tolerant transmission modes. In particular, we derive an analytical expression of the average throughput for the delay-limited transmission mode, and a precise lower bound on the average throughput for the delay-tolerant transmission mode. Furthermore, we derive simplified asymptotic expressions of the average throughput for both transmission modes assuming asymptotically large number of receive antennas (i.e., N → ∞). We use the obtained asymptotic expressions to derive insightful closed-form expressions for the optimal energy harvesting time, which maximizes the average throughput, for both transmission modes. We show that the throughput-optimal energy harvesting time for the delay-limited and the delay-tolerant transmission scale like O(1/√N) and O(1/log(N)), respectively, for asymptotically large N.

On Communication Performance in Energy Harvesting WSNs Under a Cooperative Jamming Attack

In this article, we consider the system performance of an energy harvesting (EH) wireless sensor network in terms of reliable communications when subjected to a cooperative jamming attack. A set of strategically located nodes acting as cluster heads (CHs) transfer energy to the wireless sensors within range, forming a cluster. The sensors use this energy to transmit data to the CHs, which, in turn, deliver the information to a base station (BS) using nonorthogonal multiple access. The BS processes the collected information and synchronizes the operation of all CHs. Furthermore, there exist two adversaries, namely, a jamming attacker and an eavesdropper, who cooperate to attack the considered system. To protect against this attack, the CHs should be controlled by suitable power allocation coefficients obtained from the security constraints of the CHs. Using these constraints, closed-form expressions are derived to find the power allocation coefficients that will enable reliable and secure communication. In addition, we propose an interference channel selection policy for the sensor-to-CHs links and CHs-to-BS links to improve the reliability of communication while enhancing energy utilization. Finally, an algorithm for finding the optimal EH time is also proposed.

Performance Analysis and Optimization for Power Beacon-Assisted Wireless Powered Cooperative NOMA Systems

Wireless power transfer (WPT) is an effective way to prolong the lifetime of the energy-constraint networks. In this paper, we investigate a wireless powered cooperative non-orthogonal multiple access (WP-CNOMA) system, consisting of a power beacon (PB), an information transmitter (S), multiple relays (R) and two information receiving devices with near device <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{1}$ </tex-math></inline-formula> and far device <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{2}$ </tex-math></inline-formula> . We assume both S and R are energy-constraint and there is no direct link between S and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{2}$ </tex-math></inline-formula> . With the help of PB, S and R can harvest energy from it to restart the communication for WP-CNOMA network. For such a system, low-complexity but effective relay and antenna selection schemes are applied. To characterize the performance, outage probabilities and average throughput are derived for linear and non-linear energy harvesting (EH) models, respectively. Moreover, to maximize the average throughput, invoking the unimodal feature for average throughput with respect to the EH time, we find the optimal EH time via Golden section search method. Simulation results validate the accuracy of analytical results, and reveal the performance gain for our system over the benchmark schemes. Also, it can be seen that the non-linear EH model shows different outage behaviors from the linear one. On the other hand, considering the practical application and to improve the performance, the optimization for a simple WP-CNOMA system with single-antenna PB and single relay is also investigated, in which we aim to maximize the minimum throughput by jointly optimizing EH time and power allocation. A low-complexity analytical method is developed to find the max-min rate. Numerical results show that through optimization, the system performance can be improved significantly.

Time Allocation Optimization and Trajectory Design in UAV-Assisted Energy and Spectrum Harvesting Network

The scarcity of energy resources and spectrum resources has become an urgent problem with the exponential increase of communication devices. Meanwhile, unmanned aerial vehicle (UAV) is widely used to help communication network recently due to its maneuverability and flexibility. In this paper, we consider a UAV-assisted energy and spectrum harvesting (ESH) network to better solve the spectrum and energy scarcity problem, where nearby secondary users (SUs) harvest energy from the base station (BS) and perform data transmission to the BS, while remote SUs harvest energy from both BS and UAV but only transmit data to UAV to reduce the influence of near-far problem. We propose an unaligned time allocation scheme (UTAS) in which the uplink phase and downlink phase of nearby SUs and remote SUs are unaligned to achieve more flexible time schedule, including schemes (a) and (b) in remote SUs due to the half-duplex of energy harvesting circuit. In addition, maximum throughput optimization problems are formulated for nearby SUs and remote SUs respectively to find the optimal time allocation. The optimization problem can be divided into three cases according to the relationship between practical data volume and theoretical throughput to avoid the waste of time resource. The expressions of optimal energy harvesting time and data transmission time of each node are derived. Lastly, a successive convex approximation based iterative algorithm (SCAIA) is designed to get the optimal UAV trajectory in broadcast mode. Simulation results show that the proposed UTAS can achieve better performance than traditional time allocation schemes.

충전식과 비충전식 배터리를 동시에 사용하는 복호 후 전송 중계 네트워크를 위한 에너지 수확 시간 최적화 기법

충전식과 비충전식 배터리를 동시에 사용하는 복호 후 전송 중계 네트워크를 위한 에너지 수확 시간 최적화 기법

Wireless powered UAV relay communications over fluctuating two-ray fading channels

The unmanned aerial vehicle (UAV) relay has recently attracted a large amount of research interests, due to its relative ease of development to enhance cooperative communication performance when the direct link between transmitters and receivers is severely blocked. With simultaneous wireless information and power transfer, the UAV relay can harvest energy from radio frequency and prolong the network lifetime. In this paper, we use the time-switching relaying protocol for UAV energy harvesting (EH) and data forwarding. Different from prior works, the ground-to-air links are modeled as fluctuating two-ray fading channels, which provide a very good fit to the UAV relay communication. In addition, we obtain novel exact analytical expressions for the outage probability, symbol error rate and average capacity of the considered system employing decode-and-forward and amplify-and-forward protocols, respectively. Furthermore, we offer valuable insights into the impact of system and fading parameters on the performance. For example, the optimal EH time can be selected to enhance the system performance. Finally, numerical results are provided to validate the derived results.

Secrecy Performance in the Internet of Things: Optimal Energy Harvesting Time Under Constraints of Sensors and Eavesdroppers

In this paper, we investigate the physical layer security (PLS) performance for the Internet of Things (IoT), which is modeled as an IoT sensor network (ISN). The considered system consists of multiple power transfer stations (PTSs), multiple IoT sensor nodes (SNs), one legitimate fusion center (LFC) and multiple eavesdropping fusion centers (EFCs), which attempt to extract the transmitted information at SNs without an active attack. The SNs and the EFCs are equipped with a single antenna, while the LFC is equipped with multiple antennas. Specifically, the SNs harvest energy from the PTSs and then use the harvested energy to transmit the information to the LFC. In this research, the energy harvesting (EH) process is considered in the following two strategies: 1) the SN harvests energy from all PTSs, and 2) the SN harvests energy from the best PTS. To guarantee security for the considered system before the SN sends the packet, the SN’s power is controlled by a suitable power policy that is based on the channel state information (CSI), harvested energy, and security constraints. An algorithm for the nearly optimal EH time is implemented. Accordingly, the analytical expressions for the existence probability of secrecy capacity and secrecy outage probability (SOP) are derived by using the statistical characteristics of the signal-to-noise ratio (SNR). In addition, we analyze the secrecy performance for various system parameters, such as the location of system elements, the number of PTSs, and the number of EFCs. Finally, the results of Monte Carlo simulations are provided to confirm the correctness of our analysis and derivation.

Outage Performance Analysis of Energy Harvesting Wireless Sensor Networks for NOMA Transmissions

In this paper, we investigate radio frequency (RF) energy harvesting (EH) in wireless sensor networks (WSNs) using non-orthogonal multiple access (NOMA) uplink transmission with regard to a probable secrecy outage during the transmission between sensor nodes (SNs) and base station (BS) in the presence of eavesdroppers (EAVs). In particular, the communication protocol is divided into two phases: 1) first, the SNs harvest energy from multiple power transfer stations (PTSs), and then, 2) the cluster heads are elected to transmit information to the BS using the harvested energy. In the first phase, we derive a 2D RF energy model to harvest energy for the SNs. During the second phase, the communication faces multiple EAVs who attempt to capture the information of legitimate users; thus, we propose a strategy to select cluster heads and implement the NOMA technique in the transmission of the cluster heads to enhance the secrecy performance. For the performance evaluation, the exact closed-form expressions for the secrecy outage probability (SOP) at the cluster heads are derived. A nearly optimal EH time algorithm for the cluster head is also proposed. In addition, the impacts of system parameters, such as the EH time, the EH efficiency coefficient, the distance between the cluster heads and the BS, and the number of SNs as well as EAVs on the SOP, are investigated. Finally, Monte Carlo simulations are performed to show the accuracy of the theoretical analysis; it is also shown that the secrecy performance of NOMA in RF EH WSN can be improved using the optimal EH time.

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.

Bidirectional Communication in Full Duplex Wireless-Powered Relaying Networks: Time-Switching Protocol and Performance Analysis

In this paper, we consider two-way full-duplex relay with energy harvesting system, in which the relay node harvests transmitted power from the two source nodes to forward signals to destinations. We also analyze the relay network model with decode-and-forward protocol for information cooperation and time switching-based relaying protocol for power transfer. In particular, the outage probability, average throughput and optimal energy harvesting time of novel scheme in simultaneous wireless information and power transfer are presented. We obtain analytic closed-form expressions for both tight bounded and asymptotic of outage probability and average throughput of system. Using numerical and analytic simulations, the performances of different situations are presented and discussed more clearly. The results show that the better performance is achieved in case of worse self-interference. As important result, the better self interference cancellation leads to superior system performance.