Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/220212
Title: Anatomical Region-Specific In Vivo Wireless Communication Channel Characterization
Authors: Ali Fatih Demir;Qammer H. Abbasi;Z. Esat Ankarali;Akram Alomainy;Khalid Qaraqe;Erchin Serpedin;Huseyin Arslan
Year: 2017
Publisher: IEEE
Abstract: In vivo wireless body area networks and their associated technologies are shaping the future of healthcare by providing continuous health monitoring and noninvasive surgical capabilities, in addition to remote diagnostic and treatment of diseases. To fully exploit the potential of such devices, it is necessary to characterize the communication channel, which will help to build reliable and high-performance communication systems. This paper presents an in vivo wireless communication channel characterization for male torso both numerically and experimentally (on a human cadaver) considering various organs at 915 MHz and 2.4 GHz. A statistical path loss (PL) model is introduced, and the anatomical region-specific parameters are provided. It is found that the mean PL in decibel scale exhibits a linear decaying characteristic rather than an exponential decaying profile inside the body, and the power decay rate is approximately twice at 2.4 GHz as compared to 915 MHz. Moreover, the variance of shadowing increases significantly as the in vivo antenna is placed deeper inside the body since the main scatterers are present in the vicinity of the antenna. Multipath propagation characteristics are also investigated to facilitate proper waveform designs in the future wireless healthcare systems, and a root-mean-square delay spread of 2.76 ns is observed at 5 cm depth. Results show that the in vivo channel exhibit different characteristics than the classical communication channels, and location dependence is very critical for accurate, reliable, and energy-efficient link budget calculations.
URI: http://localhost/handle/Hannan/220212
volume: 21
issue: 5
More Information: 1254,
1262
Appears in Collections:2017

Files in This Item:
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Title: Anatomical Region-Specific In Vivo Wireless Communication Channel Characterization
Authors: Ali Fatih Demir;Qammer H. Abbasi;Z. Esat Ankarali;Akram Alomainy;Khalid Qaraqe;Erchin Serpedin;Huseyin Arslan
Year: 2017
Publisher: IEEE
Abstract: In vivo wireless body area networks and their associated technologies are shaping the future of healthcare by providing continuous health monitoring and noninvasive surgical capabilities, in addition to remote diagnostic and treatment of diseases. To fully exploit the potential of such devices, it is necessary to characterize the communication channel, which will help to build reliable and high-performance communication systems. This paper presents an in vivo wireless communication channel characterization for male torso both numerically and experimentally (on a human cadaver) considering various organs at 915 MHz and 2.4 GHz. A statistical path loss (PL) model is introduced, and the anatomical region-specific parameters are provided. It is found that the mean PL in decibel scale exhibits a linear decaying characteristic rather than an exponential decaying profile inside the body, and the power decay rate is approximately twice at 2.4 GHz as compared to 915 MHz. Moreover, the variance of shadowing increases significantly as the in vivo antenna is placed deeper inside the body since the main scatterers are present in the vicinity of the antenna. Multipath propagation characteristics are also investigated to facilitate proper waveform designs in the future wireless healthcare systems, and a root-mean-square delay spread of 2.76 ns is observed at 5 cm depth. Results show that the in vivo channel exhibit different characteristics than the classical communication channels, and location dependence is very critical for accurate, reliable, and energy-efficient link budget calculations.
URI: http://localhost/handle/Hannan/220212
volume: 21
issue: 5
More Information: 1254,
1262
Appears in Collections:2017

Files in This Item:
File Description SizeFormat 
7593228.pdf3.28 MBAdobe PDFThumbnail
Preview File
Title: Anatomical Region-Specific In Vivo Wireless Communication Channel Characterization
Authors: Ali Fatih Demir;Qammer H. Abbasi;Z. Esat Ankarali;Akram Alomainy;Khalid Qaraqe;Erchin Serpedin;Huseyin Arslan
Year: 2017
Publisher: IEEE
Abstract: In vivo wireless body area networks and their associated technologies are shaping the future of healthcare by providing continuous health monitoring and noninvasive surgical capabilities, in addition to remote diagnostic and treatment of diseases. To fully exploit the potential of such devices, it is necessary to characterize the communication channel, which will help to build reliable and high-performance communication systems. This paper presents an in vivo wireless communication channel characterization for male torso both numerically and experimentally (on a human cadaver) considering various organs at 915 MHz and 2.4 GHz. A statistical path loss (PL) model is introduced, and the anatomical region-specific parameters are provided. It is found that the mean PL in decibel scale exhibits a linear decaying characteristic rather than an exponential decaying profile inside the body, and the power decay rate is approximately twice at 2.4 GHz as compared to 915 MHz. Moreover, the variance of shadowing increases significantly as the in vivo antenna is placed deeper inside the body since the main scatterers are present in the vicinity of the antenna. Multipath propagation characteristics are also investigated to facilitate proper waveform designs in the future wireless healthcare systems, and a root-mean-square delay spread of 2.76 ns is observed at 5 cm depth. Results show that the in vivo channel exhibit different characteristics than the classical communication channels, and location dependence is very critical for accurate, reliable, and energy-efficient link budget calculations.
URI: http://localhost/handle/Hannan/220212
volume: 21
issue: 5
More Information: 1254,
1262
Appears in Collections:2017

Files in This Item:
File Description SizeFormat 
7593228.pdf3.28 MBAdobe PDFThumbnail
Preview File