Abstract

We address the features channel characterization and performance evaluation for wireless body-area networks (WBANs) in medical applications during a walk scenario using optical wireless transmission. More specifically, we focus on optical extra-WBAN uplink communication between a central coordinator node (CN) placed on the patient’s body and an access point (AP) in a typical hospital room. To characterize the optical wireless channel, we use a Monte Carlo ray tracing-based method and take into account the effects of body shadowing and mobility based on realistic models, in contrast to the previous simplistic models considered in the literature. Using this approach, we derive the dynamic behavior of the channel DC gain for different configurations of the CNs and APs. Furthermore, based on the obtained results, we develop a statistical channel model based on kernel density estimation, which we use to investigate the impact of CN and AP placement on the communication link parameters. Also, based on the outage probability criterion, we discuss the link performance and further analyze the improvement in performance achieved through spatial diversity, i.e., by using multiple APs in the room, for different photodetector types, under different background noise conditions. The presented results show that CN placement and user’s local and global mobility significantly impact the performance of extra-WBAN links, which can nevertheless be reduced using spatial diversity. Finally, the presented performance analysis shows that a single AP equipped with an avalanche photodiode photodetector allows an acceptable link performance for low-to-moderate background noise conditions, whereas multiple APs equipped with PIN photodetectors should be used in the case of moderate-to-strong background noise.

Highlights

  • E-health solutions are attracting increasing attention in many application scenarios as efficient systems for improving the quality of life and reducing health-care expenditures.[1]

  • This work investigated channel characterization and performance study for medical optical extra-wireless body-area networks (WBANs) links, taking into account user mobility using a dynamic model based on a 3D animation of the user walk cycle and a modified random waypoint (RWP) model

  • The presented results and analysis are quite insightful in the design of medical WBANs by taking into account practical and realistic system parameters and channel characteristics

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Summary

Introduction

E-health solutions are attracting increasing attention in many application scenarios as efficient systems for improving the quality of life and reducing health-care expenditures.[1]. The transmit power level is restricted to satisfy the specific absorption rate to avoid damaging the patients’ tissues.[11] These considerations have motivated the investigation of optical wireless communications (OWC) as an alternative or complementary solution to RF data transmission for medical WBANs. The main advantages of OWC are their immunity to external interference, their inherent security due to the confinement of light in indoor environments, and the negligible impact of multipath (small scale) fading.[12]. Ref. 13 studied the optical intra-WBAN channel using a simplified model for the patient’s body and mobility. Neglecting the effect of mobility, Ref. proposed a site-specific ray tracing approach that considers the skin tissue for the channel modeling of WBAN communication links in hospital scenarios. Neglecting the user’s body modeling, Ref. studied the performance of optical code-division multiple access (O-CDMA) for uplink extra-WBANs considering the orientation-based random waypoint (RWP) model for user mobility.

Channel Characterization
X Nray hðtÞ
User Mobility Modeling
Signal Transmission Formulation
Statistical channel modeling
Bit-error rate calculation
Parameter Specification
Single AP Configurations
Multiple AP Configurations
Statistical Model of Channel Gain
Performance Comparison of Single and Multiple AP Configurations
Performance Comparison of PIN- and APD-based Rxs
Findings
Conclusions
Full Text
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