A Novel Energy Efficient Harvesting Technique for SDWSN using RF Transmitters with MISO Beamforming

  • Ghadeer Written by
  • Update: 29/12/2022

A Novel Energy Efficient Harvesting Technique for SDWSN using RF Transmitters with MISO Beamforming

Subaselvi Sundarraj

Department of Electronics and Communication Engineering, Anna University, India

This email address is being protected from spambots. You need JavaScript enabled to view it.

Gunaseelan Konganathan

Department of Electronics and Communication Engineering, Anna University, India

This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract: Software Defined Wireless Sensor Networks (SDWSN) is emerged to overcome the additional energy consumption in WSN. Even then the sensor nodes in the SDWSN suffer from scarce battery resources. Generally, the Radio Frequency (RF) transmitters are deployed around the base station in the SDWSN to overcome the high energy consumption problem. To enhance harvesting energy and coverage of nodes in the network, a new energy harvesting technique using RF transmitters with Multiple Input and Single Output (MISO) beamforming is proposed. In this method, multiple antenna RF transmitters and single antenna sensor nodes are deployed. The optimization problem subject to Signal to Noise Ratio (SNR) and energy harvesting constraints is formulated for hybrid beamforming design to reduce the transmit power in the network. The optimization problem based on convex Second Order Cone Programming (SOCP) is derived to get the optimal solution for hybrid beamforming design. The beamforming technique is used to steer the beam in the desired direction and null to the other direction improves the energy harvesting. The simulation results show that the proposed technique provides better average harvesting energy, average transmit power, average residual energy and throughput than the existing RF transmitter based energy harvesting methods.

Keywords: SDWSN, RF transmitters, energy harvesting, MISO, beamforming, SOCP, convex optimization.

Received January 22, 2021; accepted April 3, 2022

https://doi.org/10.34028/iajit/20/1/13

Full text

Read 817 times Last modified on Monday, 02 January 2023 07:01
Top
We use cookies to improve our website. By continuing to use this website, you are giving consent to cookies being used. More details…