Energy Consumption Analysis of Digital Wireless Communication in Nakagami Fading for IoT Applications

This paper has investigated the impact on energy in point to point wireless communication when varying bit per symbol and optimizing bandwidth to find the way to reduce energy consumption in wireless communication. Nakagami-m fading channel model, pathloss and M-QAM modulation is considered in this work. The numerical result states that located sensors under 10 meters between each sensor can save energy consumption in every fading parameter and bit per symbol. Bandwidth selection is a significant factor that can improve energy-efficient in wireless system, increasing bandwidth from 20kHz to 2MHz can reduce energy consumption up to 80% in severe fading. In addition, optimization bandwidth can save energy, transmitting signal should be sent with appropriate bandwidth for saving energy.

[1]  Jean-Yves Baudais,et al.  Rate optimization for energy efficient system with M-QAM , 2017, 2017 International Conference on Computing, Networking and Communications (ICNC).

[2]  Kok Lay Teo,et al.  Forest fire monitoring, detection and decision making systems by wireless sensor network , 2018, 2018 Chinese Control And Decision Conference (CCDC).

[3]  Andreas Pitsillides,et al.  Mobile Phone Computing and the Internet of Things: A Survey , 2016, IEEE Internet of Things Journal.

[4]  George K. Karagiannidis,et al.  Exact Error Analysis and Energy Efficiency Optimization of Regenerative Relay Systems Under Spatial Correlation , 2016, IEEE Transactions on Vehicular Technology.

[5]  Ali Kashif Bashir,et al.  A Survey on Resource Management in IoT Operating Systems , 2018, IEEE Access.

[6]  Wen-Jun Lu,et al.  A Closed-Form and Stochastic Wall Insertion Loss Model for Dense Small Cell Networks , 2018, IEEE Access.

[7]  Mani B. Srivastava,et al.  Modulation scaling for Energy Aware Communication Systems , 2001, ISLPED '01.

[8]  Andrea J. Goldsmith,et al.  Modulation optimization under energy constraints , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[9]  Aggelos Bletsas,et al.  Multistatic Scatter Radio Sensor Networks for Extended Coverage , 2017, IEEE Transactions on Wireless Communications.

[10]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization for coded systems , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).