scholarly journals Optimal Energy Beamforming to Minimize Transmit Power in a Multi-Antenna Wireless Powered Communication Network

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 509
Author(s):  
Iqra Hameed ◽  
Pham-Viet Tuan ◽  
Mario R. Camana ◽  
Insoo Koo
Keyword(s):  
Communication Network ◽  
Minimization Problem ◽  
Time Allocation ◽  
Access Point ◽  
Power Minimization ◽  
Transmit Power ◽  
Optimal Energy ◽  
Single Antenna ◽  
Information Signal ◽  
Energy Beamforming

In this paper, we study the transmit power minimization problem with optimal energy beamforming in a multi-antenna wireless powered communication network (WPCN). The considered network consists of one hybrid access point (H-AP) with multiple antennae and multiple users with a single antenna each. The H-AP broadcasts an energy signal on the downlink, using energy beamforming to enhance the efficiency of the transmit energy. In this paper, we jointly optimize the downlink time allocation for wireless energy transfer (WET), the uplink time allocation for each user to send a wireless information signal to the H-AP, the power allocation to each user on the uplink, and the downlink energy beamforming vectors while controlling the transmit power at the H-AP. It is challenging to solve this non-convex complex optimization problem because it is numerically intractable and involves high computational complexity. We exploit a sequential parametric convex approximation (SPCA)-based iterative method, and propose optimal and sub-optimal solutions for the transmit power minimization problem. All the proposed schemes are verified by numerical simulations. Through the simulation results, we present the performance of the proposed schemes based on the effect of the number of transmit antennae and the number of users in the proposed WPCN. Through the performance evaluation, we show that the SPCA-based joint optimization solution performance is superior to other solutions.

scholarly journals Research on Transmission and Offloading Scheme of MEC-IRS for Distribution Network Service

2021 ◽  
Vol 2087 (1) ◽  
pp. 012074
Author(s):  
Bingsen Xia ◽  
Yuanchun Tang
Keyword(s):  
Reinforcement Learning ◽  
Internet Of Things ◽  
Minimization Problem ◽  
Power Distribution ◽  
Learning Algorithm ◽  
Distribution Network ◽  
Access Point ◽  
Delay Minimization ◽  
Single Antenna ◽  
Computing Node

Abstract the paper introduces IRS to assist offloading, and the propagation Environment can be intelligently changed by changing the reflection unit of the IRS, This article proposes an IRS-assisted MEC power distribution Internet of Things system, and studies the gain effect of IRS in the MEC system. In this system, the single antenna equipment can choose to unload a small part of its computing task to the edge computing node of the distribution Internet of things through the multi antenna access point with the help of IRS. In this paper, the delay minimization problem of the whole system is established, the DNQ reinforcement learning algorithm is used to solve the problem, which can effectively change the coverage of smart substations.

scholarly journals AN-Aided Transmit Beamforming Design for Secured Cognitive Radio Networks with SWIPT

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Weili Ge ◽  
Zhengyu Zhu ◽  
Zhongyong Wang ◽  
Zhengdao Yuan
Keyword(s):  
Cognitive Radio ◽  
Iterative Algorithm ◽  
Cognitive Radio Networks ◽  
Optimization Design ◽  
Original Problem ◽  
Radio Networks ◽  
Artificial Noise ◽  
Transmit Beamforming ◽  
Transmit Power ◽  
Single Antenna

We investigate multiple-input single-output secured cognitive radio networks relying on simultaneous wireless information and power transfer (SWIPT), where a multiantenna secondary transmitter sends confidential information to multiple single-antenna secondary users (SUs) in the presence of multiple single-antenna primary users (PUs) and multiple energy-harvesting receivers (ERs). In order to improve the security of secondary networks, we use the artificial noise (AN) to mask the transmit beamforming. Optimization design of AN-aided transmit beamforming is studied, where the transmit power of the information signal is minimized subject to the secrecy rate constraint, the harvested energy constraint, and the total transmit power. Based on a successive convex approximation (SCA) method, we propose an iterative algorithm which reformulates the original problem as a convex problem under the perfect channel state information (CSI) case. Also, we give the convergence of the SCA-based iterative algorithm. In addition, we extend the original problem to the imperfect CSI case with deterministic channel uncertainties. Then, we study the robust design problem for the case with norm-bounded channel errors. Also, a robust SCA-based iterative algorithm is proposed by adopting the S-Procedure. Simulation results are presented to validate the performance of the proposed algorithms.

scholarly journals Optimal energy beamforming under per‐antenna power constraint

2019 ◽  
Vol 31 (3) ◽  
Author(s):  
Zahra Rezaei ◽  
Ehsan Yazdian ◽  
Foroogh S. Tabataba ◽  
Saeed Gazor
Keyword(s):  
Power Constraint ◽  
Optimal Energy ◽  
Energy Beamforming

Transmit-Power Minimization for NOMA-Enabled Traffic Offloading With Security Provisioning

2018 ◽  
Vol 22 (5) ◽  
pp. 986-989 ◽  
Author(s):  
Changsheng Yu ◽  
Li Yu ◽  
Yuan Wu ◽  
Yanfei He
Keyword(s):  
Power Minimization ◽  
Transmit Power ◽  
Traffic Offloading

scholarly journals Weighted Sum Transmit Power Minimization for Full-Duplex System With SWIPT and Self-Energy Recycling

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 4874-4881 ◽  
Author(s):  
Zhongwei Hu ◽  
Chaowei Yuan ◽  
Fengchao Zhu ◽  
Feifei Gao
Keyword(s):  
Full Duplex ◽  
Weighted Sum ◽  
Power Minimization ◽  
Duplex System ◽  
Transmit Power ◽  
Self Energy
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