Investigation of Energy Consumption in WSNs within Enclosed Spaces using Beamforming and LMS (BF-LMS)

• Published in: IEEE access Vol. 12; p. 1
• Main Author: Iskandarani, Mahmoud Z.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna arrays; Array signal processing; Beamforming; Collaboration; Communication; Data communication; Data Transmission; Energy; Energy consumption; Heuristic methods; LMS; Mathematical analysis; Mathematical models; Nodes; Path Loss; Power consumption; Sensors; Signal processing algorithms; Simulation; Transmitters; Transmitting antennas; Wireless sensor networks; WSN
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3395932

In Wireless Sensor Networks (WSNs), Collaborative Beamforming (CBF) is a crucial instrument for extending the transmission range. Because WSNs are unpredictable and complicated, it is crucial to develop and apply better metaheuristic algorithms in CBF. This paper presents mathematical models as a result of MATLAB simulation of the consumed energy in a wireless sensor network (WSN) using beamforming with least mean square algorithm (LMS). The objective is to model effect of transmitter power (PowerTX), Number of cycles or iterations, and weights on the energy function. The simulation showed that the relationship between energy and transmitter power is an adaptive, power relationship, while the relationship between energy function and cycles, and weights is an exponential relationship. Correlation between the two functions proved to be possible through the developed mathematical model, which also emphasizes effect of number of sensor nodes on the overall energy consumption and weight changing. The presented work requires further development and more analysis, which involves, inclusion of other parameters that affect energy consumption and range coverage, inside and outside buildings and enclosures. The main objectives and contribution of this work is establishing mathematical models based on simulation of real life scenarios. Such models enabled correlation of energy, weights, number of nodes, cycles, and transmitter power in a manner that highlighted the effect of each on energy and power consumption. In addition, the work enabled the focus on the importance of number of cycles and LMS weights on additional energy consumption per antenna transmitter power.