NDLI: Energy-efficient adaptive modulation in wireless communication for implanted medical devices

Content Provider	IEEE Xplore Digital Library
Author	Yinyue Qiu Haley, D. Ying Chen
Copyright Year	2014
Description	Author affiliation: Inst. for Telecommun. Res., Univ. of South Australia, Adelaide, SA, Australia (Yinyue Qiu; Haley, D.; Ying Chen)
Abstract	In contrast to conventional wireless communication which takes place over the air, Radio Frequency (RF) communication through the human body poses unique challenges. Studies on RF propagation through human body indicate that the heterogeneous body tissues with different dielectric properties constitute a complicated and lossy environment for signal propagation. This environment also varies with different implant positions, individuals, body shapes and postures. As a result, there is a large variation in the path loss value of the in-body communication channel. In this paper, we first examine the energy efficiency of different digital modulation schemes in a basic wireless implant system. We point out that using a fixed type of modulation does not help to achieve the best energy efficiency in the implant system that has varying channel conditions. We then propose an adaptive communication system model which is suitable for wireless medical implant. Simulations results show that adopting adaptive modulation can provide a considerable amount of energy saving.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	918
Ending Page	921
File Size	733010
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6943741
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Implants Wireless communication Energy consumption Adaptive systems Propagation losses Binary phase shift keying
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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