Cross Layer Interference Management in Wireless Biomedical Networks

Vangelis Sakkalis,Kostas Marias,Apostolos Traganitis,Emmanouil Spanakis

doi:10.3390/e16042085

Vangelis Sakkalis, Kostas Marias + Show 2 more

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https://doi.org/10.3390/e16042085

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Abstract

Interference, in wireless networks, is a central phenomenon when multiple uncoordinated links share a common communication medium. The study of the interference channel was initiated by Shannon in 1961 and since then this problem has been thoroughly elaborated at the Information theoretic level but its characterization still remains an open issue. When multiple uncoordinated links share a common medium the effect of interference is a crucial limiting factor for network performance. In this work, using cross layer cooperative communication techniques, we study how to compensate interference in the context of wireless biomedical networks, where many links transferring biomedical or other health related data may be formed and suffer from all other interfering transmissions, to allow successful receptions and improve the overall network performance. We define the interference limited communication range to be the critical communication region around a receiver, with a number of surrounding interfering nodes, within which a successful communication link can be formed. Our results indicate that we can achieve more successful transmissions by adapting the transmission rate and power, to the path loss exponent, and the selected mode of the underline communication technique allowing interference mitigation and when possible lower power consumption and increase achievable transmission rates.

Highlights

Recent advances in Information and Communications Technology (ICT) enable the acquisition, transmission and interpretation of different bio-signals, from fixed or mobile locations
In addition we present how interference levels and the interference limited communication range values are affected by the number of the surrounding interfering transmitters, the path loss exponent and most importantly on the selected mode and rate of operation
The parameters for our simulation are chosen to reflect the description of our system model (Figure 1) for a general-purpose wireless biomedical network used as the medium to transfer different bio-signals

Summary

Introduction

Recent advances in Information and Communications Technology (ICT) enable the acquisition, transmission and interpretation of different bio-signals, from fixed or mobile locations. Important trends in healthcare include citizen mobility and the consequent shift towards shared or integrated care where the single doctor-patient relationship has evolved to one in which each individual’s healthcare is the responsibility of a team of professionals in a geographically extended healthcare system In such a new setting, the possibility of collecting clinical information from different points is becoming a common need for citizens and physicians. Biomedical body/personal wireless sensor networks have been extensively applied in remote health monitoring and patient care [5,6] allowing wireless, wearable or implanted vital sign sensors to be continuously sampled, such as EEG [7], ECG, SpO2, weight, blood pressure, heart rate[8], etc Such kinds of networks share many similar properties with general-purpose wireless networks, many domain specific challenges (related to power consumption, transmission range, high degree of reliability, security, etc.) have emerged with respect to specific application domain requirements [9]. These services use a wide range of wireless medical devices and sensors and wireless telecommunication infrastructures to allow ubiquitous remote biomedical monitoring [17,18,19,20]

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