Integrating device to device network with internet of health things: Towards minimum power allocation

Author:

Mahmoud Mahmoud Shuker,Hammood Dalal Abdulmohsin,Alkhayyat Ahmed

Abstract

Among the crucial invention of the 5G is the device to device (D2D) system, whereby cellular gadgets correspond via immediate transfer or by multihop transfer excluding the ground-terminal. It is probable that D2D users are concurrent with human body network. Due to this, we suggested an internet of health things (IoHT) system which enables collaboration work among D2D users and human body indicators. We may regard the power as the most unique source in the wireless body area network (WBAN). The least needed transferring capacity may accomplish a particular degree of function, and minimum capacity for transfer holds a crucial responsibility in decreasing power usage. In this study, we discovered the needed transfer energy of four transferring modes: the straight transferring system, the double-hop transferring system, as well as double increasing coordinated transferring system with Rayleigh medium vanishing in its layout. Besides that, we suggested an energy-competent system named as efficient-power transmission mode selection-based (EPTMS) system. The suggested system chooses suitable transferring system whereby it offers the least needed transferring energy that assures a particular transfer duration. The statistical as well as simulation results shows that the two-master node cooperative protocols (TMNCP), EPTMS may enhance system conduction within the main criteria.

Publisher

Institute of Advanced Engineering and Science

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Instrumentation,Information Systems,Control and Systems Engineering,Computer Science (miscellaneous)

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2. Resource Allocation Optimization of NOMA Network via Metaheuristic Algorithms;2022 5th International Conference on Engineering Technology and its Applications (IICETA);2022-05-31

3. Review of Intrusion Detection Systems Based on Machine Learning;2021 4th International Iraqi Conference on Engineering Technology and Their Applications (IICETA);2021-09-21

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