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.

[1] Abdolmaleki N., Ahmadi M., Malazi H., and Milardo S., “Fuzzy Topology Discovery Protocol for SDN-Based Wireless Sensor Networks,” Simulation Modelling Practice and Theory- Elseiver, vol. 79, pp. 54-68, 2017.

[2] Alamouti S., “A Simple Transmit Diversity Technique for Wireless Communications,” IEEE Journal on Selected Areas in Communications, vol. 16, no. 8, pp. 1451- 1458, 1998.

[3] Alsharif M., Kim S., and Kuruoglu N., 132 The International Arab Journal of Information Technology, Vol. 20, No. 1, January 2023 “Energy Harvesting techniques for Wireless Sensor Networks/Radio Frequency Identification: A Review,” Symmetry, vol. 11, no. 7, pp. 1-24, 2019.

[4] Altinel D. and Kurt G., “Modeling of Hybrid Energy Harvesting Communication Systems,” IEEE Transactions on Green Communications and Networking, vol. 3, no. 2, pp. 523-534, 2019.

[5] Duan Y., Luo Y., Li W., Pace P., and Fortino G., “Software Defined Wireless Sensor Networks: A Review,” in Preceding of IEEE 22nd International Conference on Computer Supported Cooperative Work in Design, Nanjing, pp. 826-831, 2018.

[6] Ejaz W., Naeem M., Basharat M., Anpalagan A., and Kandeepan S., “Efficient Wireless Power Transfer in Software-Defined Wireless Sensor Networks,” IEEE Sensors Journal, vol. 16, no. 20, pp. 7409-7420, 2016.

[7] Guo S., Wang F., Yang Y., and Xiao B., “Energy-Efficient Cooperative Transmission for Simultaneous Wireless Information and Power Transfer in Clustered Wireless Sensor Networks,” IEEE Transactions on Communications, vol. 63, no. 11, pp. 4405- 4417, 2015.

[8] Huang H., Wu Z., Ge J., and Wang L., “Toward Building Video Multicast Tree with Congestion Avoidance Capability in Software-Defined Networks,” The International Arab Journal of Information Technology, vol. 17, no. 2, pp. 162- 169, 2020.

[9] Kumar N. and Vidyarthi D., “A Green Routing Algorithm for IoT-Enabled Software Defined Wireless Sensor Network,” IEEE Sensors Journal, vol. 18, no. 22, pp. 9449-9460, 2018.

[10] Lim H. and Hwang T., “User-Centric Energy Efficiency Optimization for MISO Wireless Powered Communications,” IEEE Transactions on Wireless Communications, vol. 18, no. 2, pp. 864-878, 2019.

[11] Lo T., “Maximum Ratio Transmission,” IEEE Transactions on Communications, vol. 47, no. 10, pp. 1458-1461, 1999.

[12] Lou Y., Pu L., Wang G., and Zhao Y., “RF Energy Harvesting Wireless Communications: RF Environment, Design Hardware and Practical Issues,” Sensors, vol. 19, no. 13, pp. 1-28, 2019.

[13] Luo T., Tan H., and Quek T., “Sensor OpenFlow: Enabling Software-Defined Wireless Sensor Networks,” IEEE Communications Letters, vol. 16, no. 11, pp. 1896-1899, 2012.

[14] Lu X., Wang P., Niyato D., Kim D., and Han Z., “Wireless Networks With RF Energy Harvesting: A Contemporary Survey,” IEEE Communications Surveys and Tutorials, vol. 17, no. 2, pp. 757-789, 2015.

[15] Lindsey S. and Raghavendra C., “Pegasis: Power-Efficient Gathering in Sensor Information Systems,” in Proceedings of IEEE Aerospace Conference, Big Sky, pp. 1125- 1130, 2002.

[16] Mahmood D., Javaid N., Mahmood S., Qureshi S., Memon A., and Zaman T., “MODLEACH: A Variant of LEACH for WSNs,” in Proceedings of 8th International Conference on Broadband and Wireless Computing, Communication and Applications, Compiegne, pp. 158-163, 2013.

[17] Manjeshwar A. and Dharma A., “TEEN: A Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks,” in Proceedings 15th International Parallel and Distributed Processing Symposium, San Francisco, pp. 2009-2015, 2001.

[18] Medra M., Huang Y., and Davidson N., “Offset-Based Beamforming: A New Approach to Robust Downlink Transmission,” IEEE Transactions on Signal Processing, vol. 67, no. 1, pp. 70-82, 2019.

[19] Mishra D., Alexandropoulos G., and De S., “Energy Sustainable IoT with Individual QoS Constraints through MISO SWIPT Multicasting,” IEEE Internet of Things Journal, vol. 5, no. 4, pp. 2856-2867, 2018.

[20] Modieginyan K., Letswamotse B., Malekian R., and Abu-Mahfouz A., “Software Defined Wireless Sensor Networks Application Opportunities for Efficient Network Management: A Survey,” Computers and Electrical Engineering, vol. 66, pp. 274-287, 2018.

[21] Nguyen T., Khan J., and Ngo D., “A Distributed Energy-Harvesting-Aware Routing Algorithm for Heterogeneous IoT Networks,” IEEE Transactions on Green Communications and Networking, vol. 2, no. 4, pp. 1115-1127, 2018.

[22] Peel C., Hochwald B., and Swindlerhurst A., “A Vector-Perturbation Technique for Near Capacity Multiantenna Multiuser Communication-Part I: Channel Inversion and Regularization,” IEEE Transactions on Communications, vol. 53, no. 1, pp. 195-202, 2005.

[23] Peizhe L., Muqing W., Wenxing L., and Min Z., “A Game-Theoretic and Energy-Efficient Algorithm in an Improved Software-Defined Wireless Sensor Network,” IEEE Access, vol. 5, pp. 13430-13445, 2017.

[24] Quoc D., Liu N., and Guo D., “A Fault Tolerant Routing Based on Gaussian Network for Wireless Sensor Networks,” Journal of Communications and Networks, vol. 24, no. 1, A Novel Energy Efficient Harvesting Technique for SDWSN using RF Transmitters with ... 133 pp. 37-46, 2021.

[25] Singh P., Kumar P., and Singh J., “A Survey on Successors of LEACH Protocol,” IEEE Access, vol. 5, pp. 4298-4328, 2017.

[26] Shi Q., Liu L., Xu W., and Zhang R., “Joint Transmit Beamforming and Receive Power Splitting for MISO SWIPT Systems,” IEEE Transactions on Wireless Communications, vol. 13, no. 6, pp. 3269-3280, 2014.

[27] Timotheou S., Krikidis I., Zheng G., and Ottersten B., “Beamforming for MISO Interference Channels with QoS and RF Energy Transfer,” IEEE Transactions on Wireless Communications, vol. 13, no. 5, pp. 2646-2658, 2014.

[28] Vanamoorthy M., Chinnaiah V., and Sekar H., “A Hybrid Approach for Providing Improved Link Connectivity in SDN,” The International Arab Journal of Information Technology, vol. 17, no. 2, pp. 250-256, 2020.

[29] Wang J., Miao Y., Zhou P., Hossain S., and Rahman M., “A Software Defined Network Routing in Wireless Multihop Network,” Journal of Network and Computer Applications, vol. 85, pp. 76-83, 2017.

[30] Younis O. and Fahmy S., “HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks,” IEEE Transactions on Mobile Computing, vol. 3, no. 4, pp. 366-379, 2004.