scholarly journals Robust Beamforming Design for Secure V2X Downlink System with Wireless Information and Power Transfer under a Nonlinear Energy Harvesting Model

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3294 ◽  
Author(s):  
Shidang Li ◽  
Chunguo Li ◽  
Weiqiang Tan ◽  
Baofeng Ji ◽  
Luxi Yang
Keyword(s):  
Energy Harvesting ◽  
Traffic Safety ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Base Station ◽  
Power Splitting ◽  
Power Transfer ◽  
Vehicular Communication ◽  
Downlink System ◽  
Nonlinear Energy

Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only conveys data and energy to two types of wireless vehicular receivers, such as one hybrid power-splitting vehicular receiver, and multiple energy vehicular receivers, but also prevents information from being intercepted by the potential eavesdroppers (idle energy vehicular receivers). Both the base station and the energy vehicular receivers are equipped with multiple antennas, whereas the information vehicular receiver is equipped with a single antenna. In particular, the imperfect channel state information (CSI) and the practical nonlinear energy harvesting (EH) model are taken into account. The non-convex optimization problem is formulated to maximize the minimum harvested energy power among the energy vehicular receivers satisfying the lowest harvested energy power threshold at the information vehicular receiver and secure vehicular communication requirements. In light of the intractability of the optimization problem, the semidefinite relaxation (SDR) technique and variable substitutions are applied, and the optimal solution is proven to be tight. A number of results demonstrate that the proposed robust secure beamforming scheme has better performance than other schemes.

Multicast Beamforming for SWIPT in MISO Full-Duplex Systems

2021 ◽  
Vol 16 (1) ◽  
pp. 26-33
Author(s):  
Alexander Akpofure Okandeji
Keyword(s):  
Energy Harvesting ◽  
Channel State Information ◽  
Base Station ◽  
Semidefinite Relaxation ◽  
Full Duplex ◽  
Power Splitting ◽  
Power Transfer ◽  
Imperfect Channel State Information ◽  
Channel State ◽  
State Information

This paper considers the multicast transmit beamforming and receive power splitting problem for sum transmit power minimization for a simultaneous wireless information and power transfer (SWIPT) system subject to signal-to-interference-plus-noise ratio (SINR), and energy harvesting constraints at the receiver. In particular, we consider the case of perfect and imperfect channel state information (CSI) at the base station. Using semidefinite relaxation (SDR) technique, we obtain solution to the problem with imperfect channel state information of the self-interfering channels. Keywords: Simultaneous wireless information and power transfer, channel state information, Energy harvesting, semidefinite relaxation.

scholarly journals Energy Harvesting for Internet of Things with Heterogeneous Users

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Desheng Wang ◽  
Haizhen Liu ◽  
Xiaoqiang Ma ◽  
Jun Wang ◽  
Yanrong Peng ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Internet Of Things ◽  
Minimum Energy ◽  
Optimal Solution ◽  
Base Station ◽  
Power Splitting ◽  
Zero Forcing ◽  
Single Antenna ◽  
Dirty Paper Coding ◽  
The Internet Of Things

We study the energy harvesting problem in the Internet of Things with heterogeneous users, where there are three types of single-antenna users: ID users that only receive information, EH users that can only receive energy, and ID/EH users that receive information and energy simultaneously from a multiantenna base station via power splitting. We aim to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of the ID users and ID/EH users by jointly designing the power allocation at the transmitter and the power splitting strategy at the ID/EH receivers under the maximum transmit power and the minimum energy harvesting constraints. Specifically, we first apply the semidefinite relaxation (SDR), zero-forcing (ZF), and maximum ratio transmission (MRT) techniques to solve the nonconvex problems. We then apply the zero-forcing dirty paper coding (ZF-DPC) technique to eliminate the multiuser interference and derive the closed-form optimal solution. Numerical results show that ZF-DPC provides higher achievable minimum SINR than SDR and ZF in most cases.

scholarly journals RF Energy Harvesting with Multiple Sources in Wireless Mesh Network

2018 ◽  
Vol 10 (2) ◽  
pp. 606 ◽  
Author(s):  
K.N Puniran ◽  
Ahmad Robiah ◽  
Rudzidatul Akmam Dziyauddin
Keyword(s):  
Energy Harvesting ◽  
Base Station ◽  
Mesh Network ◽  
System Throughput ◽  
Power Splitting ◽  
Multiple Sources ◽  
Wireless Mesh ◽  
Optimal Value ◽  
Rf Energy ◽  
Single Relay

Energy harvesting (EH) module for wireless sensor network has become a promising feature to prolong the conventional battery inside the devices. This emerging technology is gaining interest from sensor manufacturers as well as academicians across the globe. The concept of employing EH module must be cost effective and practical. In such, the use of EH module type besides RF is more realistic due to the size of the scavenger module, the availability of the resources and conversion efficiency. Most of the oil and gas plants have some drawbacks in scavenging RF from surrounding (i.e. router, Wi-Fi, base station, cell phone) due to its placement in remote area and thus limited energy sources could be a threat in this application. Multiple sources, including co-channel interference (CCI) in any constraint nodes is a feasible way of scavenging several wastes from ambient RF energy via wireless mesh topology. In this paper, a 3-node decode-and-forward (DF) model is proposed where the relay node is subject to an energy constraint. Multiple primary sources and CCI are added in the system model known as Multiple-Source and Single-Relay (MSSR). A mathematical model is derived in Time Switching Relaying (TSR) and Power Splitting Relaying (PSR) schemes to obtain an average system throughput at a destination. Numerical simulation with respect to the average throughput and EH ratio was performed and compared with the Single-Source and Single-Relay (SSSR) and ideal receiver. By applying multiple sources and CCI as an energy enhancement at the constraint node, the optimal value of EH ratio for TSR can be reduced significantly by 10% as compared to the ideal receiver whereas the optimal value of EH ratio for PSR is outweigh TSR in terms of overall system throughput.

scholarly journals Dynamic Power Splitting Strategy for SWIPT Based Two-Way Multiplicative AF Relay Networks with Nonlinear Energy Harvesting Model

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Tianci Wang ◽  
Guangyue Lu ◽  
Yinghui Ye ◽  
Yuan Ren
Keyword(s):  
Energy Harvesting ◽  
Iterative Method ◽  
Relay Network ◽  
Power Splitting ◽  
Amplify And Forward ◽  
Channel State ◽  
Dynamic Power ◽  
Energy Constrained ◽  
Af Relay ◽  
Nonlinear Energy

This paper investigates an energy-constrained two-way multiplicative amplify-and-forward (AF) relay network, where a practical nonlinear energy harvesting (NLEH) model is equipped at the relay to realize simultaneous wireless information and power transfer (SWIPT). We focus on the design of dynamic power splitting (DPS) strategy, in which the PS ratio is able to adjust itself according to the instantaneous channel state information (CSI). Specifically, we first formulate an optimization problem to maximize the outage throughput, subject to the NLEH. Since this formulated problem is nonconvex and difficult to solve, we further transfer it into an equivalent problem and develop a Dinkelbach iterative method to obtain the corresponding solution. Numerical results are given to verify the quick convergence of the proposed iterative method and show the superior outage throughput of the designed DPS strategy by comparing with two peer strategies designed for the linear energy harvesting (LEH) model.

scholarly journals Throughput Fairness in Cognitive Backscatter Networks With Residual Hardware Impairments and a Nonlinear EH Model

2021 ◽  
Author(s):  
Xiaona Gao ◽  
Liqin Shi ◽  
Guangyue Lu
Keyword(s):  
Iterative Algorithm ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Primary User ◽  
Energy Harvesters ◽  
Hardware Impairments ◽  
Convex Problem ◽  
Resource Allocation Scheme ◽  
Nonlinear Energy

Abstract This paper is to design a throughput fairness-aware resource allocation scheme for a cognitive backscatter network (CBN), where multiple backscatter devices (BDs) take turns to modulate information on the primary signals and backscatter the modulated signals to a cooperative receiver (C-Rx), while harvesting energy to sustain their operations. The nonlinear energy harvesting (EH) circuits at the BDs and the residual hardware impairments (HWIs) at the transceivers are considered to better reflect the properties of the practical energy harvesters and transceivers, respectively. To ensure the throughput fairness among BDs, we formulate an optimization problem to maximize the minimum throughput of BDs by jointly optimizing the transmit power of the primary transmitter, the backscattering time and reflection coefficient for each BD, subject to the primary user’s quality of service (QoS) and BDs’ energy-causality constraints. We introduce the variable slack and decoupling methods to transform the formulated non-convex problem, and propose an iterative algorithm based on block coordinate descent (BCD) technique to solve the transformation problem. We also investigate a special CBN with a single BD and derive the optimal solution in the closed form to maximize the BD's throughput. Numerical results validate the quick convergence of the proposed iterative algorithm and that the proposed scheme ensures much fairness than the existing schemes.

scholarly journals Dynamic Wireless Energy Harvesting and Optimal Distribution in Multipair DF Relay Network with Nonlinear Energy Conversion Model

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Syed Tariq Shah ◽  
Daniel B. da Costa ◽  
Kae Won Choi ◽  
Min Young Chung
Keyword(s):  
Energy Harvesting ◽  
Energy Conversion ◽  
Relay Network ◽  
Power Splitting ◽  
Decode And Forward ◽  
Conversion Model ◽  
Transmission Modes ◽  
Energy Constrained ◽  
Wireless Energy Harvesting ◽  
Nonlinear Energy

Wireless energy harvesting has emerged as an efficient solution to prolong the lifetime of wireless networks composed of energy-constrained nodes. In this paper, we consider a multipoint-to-multipoint relay network, where multiple source nodes communicate with their respective destination nodes via intermediate energy-constrained decode-and-forward (DF) relay. The performance of two different transmission modes, namely, delay tolerant and delay nontolerant, is studied. Based on power-splitting relaying protocol (PSR), optimal energy harvesting and distribution schemes for both transmission modes are provided. In addition, for more realistic and practical analysis, we consider a nonlinear energy conversion model for energy harvesting at the relay node. Our numerical results provide useful insights into different system parameters of a nonlinear energy harvesting-based multipair DF relay network.

scholarly journals Price-Based Resource Allocation in Wireless Power Transfer-Enabled Massive MIMO Networks

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3298 ◽  
Author(s):  
Zhengqiang Wang ◽  
Kunhao Huang ◽  
Xiaona Yang ◽  
Xiaoyu Wan ◽  
Zifu Fan ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Convex Optimization ◽  
Optimization Problem ◽  
Wireless Power Transfer ◽  
Base Station ◽  
Power Transfer ◽  
Wireless Power ◽  
Convex Optimization Problem ◽  
Harvesting Time ◽  
Mimo Networks

This paper considers the price-based resource allocation problem for wireless power transfer (WPT)-enabled massive multiple-input multiple-output (MIMO) networks. The power beacon (PB) can transmit energy to the sensor nodes (SNs) by pricing their harvested energy. Then, the SNs transmit their data to the base station (BS) with large scale antennas by the harvesting energy. The interaction between PB and SNs is modeled as a Stackelberg game. The revenue maximization problem of the PB is transformed into the non-convex optimization problem of the transmit power and the harvesting time of the PB by backward induction. Based on the equivalent convex optimization problem, an optimal resource allocation algorithm is proposed to find the optimal price, energy harvesting time, and power allocation for the PB to maximize its revenue. Finally, simulation results show the effectiveness of the proposed algorithm.

scholarly journals Resource allocation for energy harvesting assisted D2D communications underlaying OFDMA cellular networks

2021 ◽  
Author(s):  
Shuo Yu ◽  
Ling Guan
Keyword(s):  
Resource Allocation ◽  
Energy Harvesting ◽  
Cellular Networks ◽  
Time Slot ◽  
Optimal Solution ◽  
Base Station ◽  
Multiple Time ◽  
Time Cost ◽  
D2d Communications ◽  
Transmission Process

D2D communications underlaying cellular networks has become very popular recently. Inter- ference between cellular users and D2D users is one of the tricky issues we need to solve. Another challenging issue is limited battery lives. In this thesis, we address these two issues together by introducing an energy harvesting (EH) assisted D2D model where the whole transmission process is divided into multiple time slots. At the beginning of every time slot, each D2D user will update the remaining energy level to the base station (BS) and the BS will then decide whether the D2D user should harvest energy or transmit data. The objective is to maximize sum throughput for all D2D users. To solve the problem, we first adopt the NOMAD algorithm, then propose a heuristic algorithm as sub-optimal solution. Numerical results show that our proposed algorithm can achieve almost the same sum throughput at a significantly smaller time cost.

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