Threshold setting for the evaluation of the aggregate interference in ISM band in hospital environments

This paper gives an overview of the European level standard proposal for smart wireless body area networks (WBAN). Under the mandate of European Telecommunication Standards Institute ETSI, a technical committee TC SmartBAN was formed in 2013. The goal of the TC SmartBAN is to define a standard for low power devices and networks to be used in short range links supporting, e.g., healthcare, wellness and sport relating applications operating around a human body. The main focus areas were in physical and medium access control layers' specifications as well as efficient data presentation format for information delivery. Moreover, experimental measurement campaigns to characterize radio channel occupancy in the specified SmartBAN frequency range have been carried out. The actual work is divided into several, parallel Work Items (WI). Within this paper, a short overview of the ETSI TC SmartBAN work is given. The components of the SmartBAN standard are described in their own dedicated papers.

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“…The channel occupancy results based on the work carried out by TC SmartBAN are presented, e.g., in [10][11][12][13]. …”

Section: Coexistence and Channel Occupancymentioning

confidence: 99%

ETSI TC SmartBAN: Overview of the wireless body area network standard

Hämäläinen¹,

Paso²,

Mucchi³

et al. 2015

2015 9th International Symposium on Medical Information and Communication Technology (ISMICT)

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A cuckoo search optimization-based forward consecutive mean excision model for threshold adaptation in cognitive radio

et al. 2019

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The forward consecutive mean excision (FCME) algorithm is one of the most effective adaptive threshold estimation algorithms presently deployed for threshold adaptation in cognitive radio (CR) systems. However, its effectiveness is often limited by the manual parameter tuning process and by the lack of prior knowledge pertaining to the actual noise distribution considered during the parameter modelling process of the algorithm. In this paper, we propose a new model that can automatically and accurately tune the parameters of the FCME algorithm based on a novel integration with the cuckoo search optimization (CSO) algorithm. Our model uses the between-class variance function of the Otsu's algorithm as the objective function in the CSO algorithm in order to auto-tune the parameters of the FCME algorithm. We compared and selected the CSO algorithm based on its relatively better timing and accuracy performance compared to some other notable metaheuristics such as the particle swarm optimization (PSO), artificial bee colony (ABC), genetic algorithm (GA), and the differential evolution (DE) algorithms. Following close performance values, our findings suggest that both the DE and ABC algorithms can be adopted as favourable substitutes for the CSO algorithm in our model. Further simulation results show that our model achieves reasonably lower probability of false alarm and higher probability of detection as compared to the baseline FCME algorithm under different noise-only and signal-plus-noise conditions. In addition, we compared our model with some other known autonomous methods with results demonstrating improved performance. Thus, based on our new model, users are relieved from the cumbersome process involved in manually tuning the parameters of the FCME algorithm; instead, this can be done accurately and automatically for the user by our model. Essentially, our model presents a fully blind signal detection system for use in CR and a generic platform deployable to convert other parameterized adaptive threshold algorithms into fully autonomous algorithms.

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