Autocorrelation Based Transmission Power Control in WBANs

Zhang, Hongyun; Safaei, Farzad; Tran, Le Chung

doi:10.1109/ismict.2018.8573719

Cited by 2 publications

(1 citation statement)

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“…In this paper, we focus on the adaptive transmission protocol in real daily life WBAN scenarios. Inspired by the autocorrelation analyses presented in the literature [4,42,43], we propose an Autocorrelation-based Adaptive Transmission (AAT) scheme that jointly considers TPC, Dynamic Slot Scheduling (DSS) and two-hop cooperation. Firstly, the slot scheduling results are taken into account to optimize the transmission power level on the sensor side.…”

Section: Introductionmentioning

confidence: 99%

Joint Transmission Power Control and Relay Cooperation for WBAN Systems

Zhang

Safaei

Tran

2018

Sensors

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Improving transmission reliability is a crucial challenge for Wireless Body Area Networks (WBANs) because of the instability of channel conditions and the stringent Packet Loss Ratio (PLR) requirement for many WBANs applications. On the other hand, limited by the size of WBAN nodes, the energy consumption of WBAN nodes should be minimized. In this paper, we jointly consider transmission power control, dynamic slot scheduling and two-hop cooperative mechanism and propose an Autocorrelation-based Adaptive Transmission (AAT) scheme that achieves a better trade-off between transmission reliability and energy consumption for WBAN systems. The new scheme is designed to be compatible with IEEE 802.15.6. We evaluated the performance of the newly proposed scheme by importing the real channel datasets into our simulation model. Simulation results demonstrate that the AAT method can effectively improve the transmission reliability while reducing the energy consumption. We also provide the performance evaluation from three perspectives, namely packet error ratio, energy consumption and energy efficiency, and provide recommendations on the application of the two-hop cooperative mechanism associated with the proposed AAT in the contexts of WBANs.

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Section: Introductionmentioning

confidence: 99%