1. Submission Title: [Empirical channel model for wearable BAN]
May 2008
Project: IEEE P Working Group for Wireless Personal Area Networks (WPANs)
Submission Title: [Empirical channel model for wearable BAN]
Date Submitted: [12 May 2008]
Source: [Noh-Gyoung Kang, Seung-Hoon Park, Daniel Kim, Chihong Cho and Eun Tae Won]
Company: [Samsung Electronics Co. Ltd.]
Address: [416, Maetan-3dong, Yeongtong-gu, Suwon-si, Gyeonggi-do, , Korea]
Voice: [ ]
FAX: [ ]
Re: [ ]
Abstract: [This document presents the information about the empirical channel model for wearable BAN systems]
Purpose: [To provide some channel model for wearable BAN]
Notice: This document has been prepared to assist the IEEE P It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein.
Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P
N.-G. Kang et al.

2. Empirical channel model for wearable BAN
<month year>
doc.: IEEE <doc#>
May 2008
Empirical channel model for wearable BAN
Noh-Gyoung Kang, Seung-Hoon Park,
Daniel Kim, Chihong Cho and Eun Tae Won
Samsung Electronics Co. Ltd.
In this presentation, I'd like to present the plan to get empirical channel models in wearable BAN
N.-G. Kang et al.
<author>, <company>

3. doc.: IEEE 802.15-<doc#>
<month year>
doc.: IEEE <doc#>
May 2008
Introduction
Implant BAN
Inside body or on-body device (sensor)
Low data rate
MICS : 402~405 MHz
Wearable BAN
On-body and air
High data rate
Frequency bands
ISM : 902~928 MHz, 2.4~2.5 GHz, 5.725~5.875 GHz
UWB : 3.1~10.6GHz
BAN is consist of two categories.
One is implant BAN and the other is wearable BAN.
- Implant BAN is for the inside body or on-body devices.
It needs low data rate and generally using MICS band.
- Wearable BAN is for the on-body device and air.
Generally, it needs high data rate and Available frequency bands are ISM band and UWB band.
N.-G. Kang et al.
<author>, <company>

4. Wearable BAN Channel Modeling
<month year>
doc.: IEEE <doc#>
May 2008
Wearable BAN Channel Modeling
Scenario 1
From on-body to air
Scenario 2
From one man to another
Scenario 3
From on-body to on-body
Scenario 4
Body in motion
Measurement Places
Anechoic chamber
Office Environment
We would like to make wearable BAN channel models.
There are four possible scenarios in wearable BAN applications.
Scenario 1 is channel from on-body to air
Scenario 2 is channel from one man to another
Scenario 3 is on-body to on-body
And Scenario 4 is channel of Body in motion
In following pages, Scenarios are explained in detail.
Measurement places are Anechoic chamber and Office Environment
N.-G. Kang et al.
<author>, <company>

5. Wearable BAN Channel Modeling
<month year>
doc.: IEEE <doc#>
May 2008
Wearable BAN Channel Modeling
Scenario 1
From on body to air
Measurement Places
Anechoic chamber
Offices
Goals
Anechoic chamber : basic properties
Offices : channel models in real environments
Body-shadowing effects
In this page, Scenario 1 is illustrated.
This is the channel from on-body to air.
This scenario defines the channel between wearable devices and gateway in out body.
Basic properties are measured in anechoic chamber and realistic model in office.
Body-shadowing effects are investigated also.
N.-G. Kang et al.
<author>, <company>

6. Wearable BAN Channel Modeling
<month year>
doc.: IEEE <doc#>
May 2008
Wearable BAN Channel Modeling
Scenario 2
From one man to another
Measurement Places
Anechoic chamber
Offices
Goals
Reliable channel model for ad-hoc gaming or interference
Body-shadowing effects
Next page is Scenario 2.
The channel from one man to another.
This scenario corresponds to the case between gateways on body.
It is the case that people have hand-held devices in his pocket.
This is reliable channel model for ad-hoc gaming applications or interference modeling.
N.-G. Kang et al.
<author>, <company>

7. Wearable BAN Channel Modeling
<month year>
doc.: IEEE <doc#>
May 2008
Wearable BAN Channel Modeling
Scenario 3
From on body to on body
Measurement Places
Anechoic chamber
Offices
Goals
Reliable channel model for body motion recognition
Accurate channel model
With various antenna positions
This scenario is the channel from on-body to on-body.
Communications between on-body devices
It is the case that one has multiple devices on his body.
This is realistic channel model for body motion recognition.
It will be an accurate channel model using multiple antenna
N.-G. Kang et al.
<author>, <company>

8. Wearable BAN Channel Modeling
<month year>
doc.: IEEE <doc#>
May 2008
Wearable BAN Channel Modeling
Scenario 4
Body in motion
Measurement Places
Anechoic chamber
Offices
Goals
Robust channel model for body motion game
Analyze motion effects in time interval
Split time interval to measure time-varying channel properties using network Analyzer
Last scenario is the channel of body in motion
It is for the channel from gateway in out of body to body in motion.
It is the case that one moves his limbs and communicates with gateway apart.
This is robust channel model for body motion game.
It is carried out by analyzing motion effects in time interval
N.-G. Kang et al.
<author>, <company>

9. Channel Measurement Systems
<month year>
doc.: IEEE <doc#>
May 2008
Channel Measurement Systems
Measure S21 channel parameter using Network Analyzer
Channel transfer function with channel gain and phase difference
System block diagram
Measurement example
Left figure shows the schematic diagram of measurements systems.
Right one illustrates measured channel transfer function examples from 5GHz to 6.6GHz
Systems measure S21 channel parameter using Network Analyzer.
Channel transfer function has its gain and phase difference.
N.-G. Kang et al.
<author>, <company>

10. Channel Measurement Systems
<month year>
doc.: IEEE <doc#>
May 2008
Channel Measurement Systems
Post process
Define channel impulse response using IFFT in Post Processor
Analyze channel characteristics using channel impulse response
Path loss, maximum excess delay, delay time distribution, etc.
Antenna, Cable and Calibration
Use patch antenna to limit body absorption
Use low-loss cable to control other effects
Calculate noise margin
Determine which level of received signals is valid
In post processing, following actions are performed.
It defines channel impulse response using IFFT in Post Processor,
And analyzes channel characteristics using channel impulse response.
Channel characterizations are path loss, maximum excess delay, delay time distribution, and so on.
We use patch antenna to limit body absorption and use low-loss cable to control other effects.
Then, we calculate noise margin using step attenuator and determine which level of received signals is valid
N.-G. Kang et al.
<author>, <company>

11. doc.: IEEE 802.15-<doc#>
<month year>
doc.: IEEE <doc#>
May 2008
Conclusion
Perform wearable BAN channel measurements
Frequency bands : some ISM bands and UWB bands
Two environments and four scenarios
Future Schedule
Channel measurements : by July 2008
Analysis and modeling : by September 2008
The results and models will be reported to TG6
We perform wearable BAN channel measurements
Frequency bands are some ISM bands and UWB bands
We consider two environments and four scenarios
Channel measurements will be done by July
And Analysis and modeling will be done by September
The results and models will be reported to TG6
N.-G. Kang et al.
<author>, <company>

12. doc.: IEEE 802.15-<doc#>
<month year>
doc.: IEEE <doc#>
May 2008
Thank You !!!
Q & A
N.-G. Kang et al.
<author>, <company>