doc.: ieee 15-04-0452-01-004a submission september 2004 chia-chin chong, samsung (sait)slide 1...

September 2004

Chia-Chin Chong, Samsung (SAIT)Slide 1

doc.: IEEE 15-04-0452-01-004a

Submission

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Submission Title: [UWB Channel Model for Indoor Residential Environment]Date Submitted: [16 September, 2004]Source: [Chia-Chin Chong, Youngeil Kim, SeongSoo Lee] Company [Samsung Advanced Institute of Technology (SAIT)]Address [RF Technology Group, Comm. & Networking Lab., P. O. Box 111, Suwon 440-600, Korea.]Voice:[+82-31-280-6865], FAX: [+82-31-280-9555], E-Mail: [[email protected]]

Re: [Response to Call for Contributions on IEEE 802.15.4a Channel Models]

Abstract: [This contribution describes the UWB channel measurement results in indoor residential environment based in several types of high-rise apartments. It consists of detailed characterization of both the large-scale and small-scale parameters of the channel such as frequency-domain parameters, temporal-domain parameters, small-scale amplitude statistics and S-V clustering multipath channel parameters of the UWB channel with bandwidth from 3 to 10 GHz.]

Purpose: [Contribution towards the IEEE 802.15.4a Channel Modeling Subgroup.]

Notice: This document has been prepared to assist the IEEE P802.15. 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 P802.15.

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

UWB Channel Model for Indoor Residential Environment

Chia-Chin Chong, Youngeil Kim, SeongSoo Lee

Samsung Advanced Institute of Technology (SAIT), Korea

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Outline

• Measurement Setup & Environment• Data Analysis & Post-Processing• Measurement Results• Large-Scale Parameters• Small-Scale Parameters• Conclusion

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Measurement Setup (1)

• Frequency domain technique using VNA– Center frequency, fc : 6.5GHz

– Bandwidth, B : 7GHz (i.e. 3-10GHz)– Delay resolution, : 142.9ps (i.e. =1/B)– No. frequency points, N : 1601– Frequency step, f : 4.375MHz (i.e. f=B/(N-1))

– Max. excess delay, max : 229.6ns (i.e. max=1/f)

– Sweeping time, tsw : 800ms

– Max. Doppler shift, fd,max : 1.25Hz (i.e. fd,max=1/tsw)

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission


• UWB planar dipole antennas• Measurement controlled by laptop with LabVIEW via

GPIB interface• Calibration performed in an anechoic chamber with

1m reference separation• Static environment during recording• Both large-scale & small-scale measurements

– Large-scale: different RX positions “local point”– Small-scale: 25 (5x5) grid-measurements around each local

point “spatial point”– At each spatial point, 30 time-snapshots of the channel

complex frequency responses are recorded

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Power Amplifier(Agilent 83020A)

Vector network analyzer(Agilent 8722ES) Low Noise Amplifier

(Miteq AFS5)


Attenuator(Agilent 8496B)

Propagation ChannelCoaxial Cables

Laptop with LabVIEW

GPIB Interface

TX antenna RX antenna

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

UWB Planar Dipole Antenna

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Measurement Environment

• Measurements in various types of high-rise apartments based on several cities in Korea typical types in Asia countries like Korea, Japan, Singapore, Hong Kong, etc.– 3-bedrooms (Apart1)– 4-bedrooms (Apart2)

• Both LOS and NLOS configurations• TX-RX antennas:

– Separations: up to 20m– Height: 1.25m (with ceiling height of 2.5m)– TX antenna: always fixed in the center of the living room– RX antenna: moved around the apartment (i.e. 8-10 locations)

• 12,000 channel complex frequency responses are collected (i.e. 2 apartments x 8 RX local points x 25 spatial points x 30 time snapshots 2x8x25x30=12,000)

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

3-Bedroom Apartment

Grid-Measurement

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

4-Bedroom Apartment

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Data Analysis & Post-Processing

• All measurement data are calibrated with the calibration data measured in anechoic chamber to remove effect of measurement system

• Perform frequency domain windowing to reduce the leakage problem

• Complex passband IFFT is deployed to transform the complex frequency response to complex impulse response

• Perform temporal domain binning before extract channel parameters

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Channel Model Description

• Large-Scale Parameters:– Path loss and Shadowing– Frequency Decaying Factor

• Small-Scale Parameters:– Temporal Domain Parameters – S-V Multipath Channel Parameters– Small-Scale Amplitude Statistics

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Path Loss and Shadowing

• Path loss (PL) vs. Distance (d):

– d0 = 1m

– PL0 : intercept

– n : path loss exponent– S : Shadowing fading parameter

• Perform linear regression to the above equation with measured data to extract the required parameters

( ) 0 10 00

10 log ;d

PL d PL n S d dd

æ ö÷ç ÷= + × × + ³ç ÷ç ÷çè ø

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Path Loss vs. Distance – LOS

0 1 2 3 4 5 6 7 848

50

52

54

56

58

60

10log10

(Distance) (m)

Pat

h L

oss

(d

B)

Path Loss under LOS Scenario in 3-Bedroom Apartment

DataLinear Regression

0 1 2 3 4 5 6 7 845

50

55

60

65

70Path Loss under LOS Scenario in 4-Bedroom Apartment

10log10

(Distance) (m)

Pa

th L

os

s (

dB

)


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Path Loss vs. Distance – NLOS

0 1 2 3 4 5 6 7 8 940

45

50

55

60

65

10log10

(Distance) (m)

Pa

th L

os

s (

dB

)

Path Loss under NLOS Scenario in 3-Bedroom Apartment


0 1 2 3 4 5 6 7 8 945

50

55

60

65

70

75

80

10log10

(Distance) (m)

Pa

th L

os

s (

dB

)

Path Loss under NLOS Scenario in 4-Bedroom Apartment


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Frequency Decaying Factor

• Path loss (PL) vs. Frequency (f):

or

( ) ( )1expPL ff dµ - ×

( ) 2PL ff d-µ

(Method 1)

(Method 2)

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Frequency Decaying Factor – LOS

3 4 5 6 7 8 9 10-60

-50

-40

-30

-20

-10

0Frequency Dependence Path Loss under LOS Scenario (3-Bedroom Apartment)

Frequency [GHz]

Pa

th L

oss

[dB

]

Measurement DataMethod 1Method 2

3 4 5 6 7 8 9 10-45

-40

-35

-30

-25

-20

-15

-10

-5

0Frequency Dependence Path Loss under LOS Scenario (4-Bedroom Apartment)

Frequency [GHz]

Pa

th L

oss

[dB

]


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Frequency Decaying Factor – NLOS

3 4 5 6 7 8 9 10-60

-50

-40

-30

-20

-10

0Frequency Dependence Path Loss under NLOS Scenario - (3-Bedroom Apartment)

Frequency [GHz]

Pa

th L

oss

[dB

]


3 4 5 6 7 8 9 10-50

-45

-40

-35

-30

-25

-20

-15

-10

-5

0Frequency Dependence Path Loss under NLOS Scenario (4-Bedroom Apartment)

Frequency [GHz]

Pa

th L

oss

[dB

]


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Large-Scale Parameters

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Temporal Domain Parameters

• These parameters were obtained after taking frequency domain Hamming windowing, passband IFFT & temporal domain binning

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

S-V Multipath Channel (1)

• Saleh-Valenzuela (S-V) channel model is given by

– L : number of clusters lth cluster– Kl : number of MPCs within the – ak,l : multipath gain coefficent of the kth component in lth

cluster– Tl : delay of the lth cluster k,l : delay of the kth MPC relative to the to the lth cluster

arrival time

( ) ( ), ,0 0

lL K

k l l k ll k

h t a t Td t= =

= - -å å

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission


• Cluster arrival times Poisson distribution

• Ray arrival times Poisson distribution

: mean cluster arrival rate : mean ray arrival rate

( ) ( )[ ]1 1| exp , 0l l l lp l- -T T = L - L T - T >

( ) ( )[ ], ( 1), , ( 1),| exp , 0k l k l k l k lp kt t l l t t- -= - - >

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission


• Average power of a MPC at a given delay, Tl + k,l

– : expected value of the power of the first arriving MPC : cluster decay factor : ray decay factor

,2 2, 0,0 e el k lk la a

t g- T G -= × ×

20,0a

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Cluster Decay Factor, – LOS

0 10 20 30 40 5010

-3

10-2

10-1

100

101

Normalized Cluster Relative Power vs. Cluster Relative Delay (Apart1-LOS)

Cluster Relative Delay, [ns]

No

rma

lize

d C

lust

er

Re

lativ

e A

mp

litu

de

= 22.10 ns

Cluster amplitudeLinear least-squares fit

0 10 20 30 40 50 6010

-4

10-3

10-2

10-1

100Normalized Cluster Relative Power vs. Cluster Relative Delay (Apart2-LOS)


No

rma

lize

d C

lust

er

Re

lativ

e A

mp

litu

de

= 23.95 ns

Cluster amplitudeLinear least-squares fit

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Cluster Decay Factor, – NLOS

0 20 40 60 80 100 12010

-6

10-4

10-2

100

102Normalized Cluster Relative Power vs. Cluster Relative Delay (Apart1-NLOS)


No

rma

lize

d C

lust

er

Re

lativ

e P

ow

er

= 51.47 ns

Cluster powerLinear least-squares fit

0 10 20 30 40 50 60 7010

-5

10-4

10-3

10-2

10-1

100

101Normalized Cluster Relative Power vs. Cluster Relative Delay (Apart2-NLOS)


No

rma

lize

d C

lust

er

Re

lativ

e P

ow

er

= 36.86 ns

Cluster powerLinear least-squares fit

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Ray Decay Factor, – LOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Ray Decay Factor, – NLOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Cluster Arrival Rate, – LOS

0 5 10 15 20-6

-5

-4

-3

-2

-1

0Cluster Inter-Arrival Times CCDF (Apart1-LOS)

Clsuter Inter-Arrival Times, T [ns]

ln(C

CD

F)

1/ = 8.69 ns

Cluster inter-arrival timesLinear least-squares fit

0 10 20 30 40 50 60-6

-5

-4

-3

-2

-1

0Cluster Inter-Arrival Times CCDF (Apart2-LOS)


ln(C

CD

F)

1/ = 11.79 ns


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Cluster Arrival Rate, – NLOS

0 10 20 30 40 50 60 70 80-7

-6

-5

-4

-3

-2

-1

0Cluster Inter-Arrival Times CCDF (Apart1-NLOS)


ln(C

CD

F)

1/ = 21.45 ns


0 5 10 15 20 25 30 35 40-6

-5

-4

-3

-2

-1

0Cluster Inter-Arrival Times CCDF (Apart2-NLOS)


ln(C

CD

F)

1/ = 15.65 ns


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Ray Arrival Rate, – LOS

0 5 10 15-18

-16

-14

-12

-10

-8

-6

-4

-2

0Ray Intra-Arrival Times CCDF (Apart2-LOS)

Ray Intra-Arrival Times, [ns]

ln(C

CD

F)

1/ = 0.86 ns

Ray intra-arrival timesLinear least-squares fit

0 2 4 6 8 10 12-25

-20

-15

-10

-5

0Ray Intra-Arrival Times CCDF (Apart1-LOS)


ln(C

CD

F)

1/ = 0.51 ns


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Ray Arrival Rate, – NLOS

0 5 10 15 20 25 30 35-50

-45

-40

-35

-30

-25

-20

-15

-10

-5

0Ray Intra-Arrival Times CCDF (Apart1-NLOS)


ln(C

CD

F)

1/ = 0.72 ns


0 2 4 6 8 10 12 14 16-30

-25

-20

-15

-10

-5

0Ray Intra-Arrival Times CCDF (Apart2-NLOS)


ln(C

CD

F)

1/ = 0.56 ns


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Mixture Poisson Distribution

• Fitting the ray arrival times to a mixture of 2 Poisson distributions similar to [1]:

: mixture probability 1 & 2: ray arrival rates

( ) ( )[ ]( ) ( )[ ]

, ( 1), 1 1 , ( 1),

2 2 , ( 1),

| exp

1 exp

k l k l k l k l

k l k l

p t t bl l t t

b l l t t

- -

-

= - -

+ - - -

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Mixture Poisson Distributions – LOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Mixture Poisson Distributions – NLOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Number of Clusters

1 2 3 4 5 60

0.1

0.2

0.3

0.4Apart1-LOS

No. of Clusters

Pro

ba

bili

ty

2 3 4 5 6 7 80

0.1

0.2

0.3

0.4Apart1-NLOS

No. of Clusters

Pro

ba

bili

ty

1 2 3 40

0.2

0.4

0.6

0.8Apart2-LOS

No. of Clusters

Pro

ba

bili

ty

1 2 3 4 50

0.2

0.4

0.6

0.8Apart2-NLOS

No. of Clusters

Pro

ba

bili

ty

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Number of MPCs per Cluster

0 50 100 150 2000

0.5

1

No. of MPCs per Cluster

CD

F

Apart1-LOS

0 500 10000

0.5

1


CD

F

Apart1-NLOS

0 100 200 3000

0.5

1


CD

F

Apart2-LOS

0 500 1000 15000

0.5

1


CD

F

Apart2-NLOS

Empirical Data

Exponential Fit

Empirical Data

Exponential Fit

Empirical Data

Exponential Fit

Empirical Data

Exponential Fit

Kl

= 24.10Kl

= 24.10Kl

= 24.10 Kl

= 87.19

Kl

= 30.47 Kl

= 117.36

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

S-V Multipath Channel Parameters

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Small-Scale Amplitude Statistics

• Comparison of empirical path amplitude distribution with the following five commonly used theoretical distributions:– Lognormal– Nakagami– Rayleigh– Ricean– Weibull

• The goodness-of-fit of the received signal amplitudes is evaluated using Kolmogorov-Smirnov (K-S) test & Chi-Square (2) test with 5% and 10% significance level, respectively.

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Goodness-of-Test: LOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Goodness-of-Test: NLOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

CDF of Path Amplitude – LOS

-120 -100 -80 -60 -40 -20 00

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Amplitude in dB

CD

F

Small-scale amplitude CDFs at different exces delays (3-bedroom apartment, LOS)

EmpiricalLognormalNakagamiRayleighWeibull

Excess delay 5ns

Excess delay 50ns

Excess delay 100ns

-120 -100 -80 -60 -40 -20 00

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Amplitude in dB

CD

F

Small-scale amplitude CDFs at different exces delays (4-bedroom apartment, LOS)


Excess delay 100ns

Excess delay 5ns

Excess delay 50ns

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

CDF of Path Amplitude – NLOS

-120 -100 -80 -60 -40 -20 0 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Amplitude in dB

CD

F

Small-scale amplitude CDFs at different exces delays (3-bedroom apartment, NLOS)


Excess delay 100ns

Excess delay 5ns

Excess delay 50ns

-140 -120 -100 -80 -60 -40 -20 0 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Amplitude in dB

CD

F

Small-scale amplitude CDFs at different exces delays (4-bedroom apartment, NLOS)


Excess delay 100ns

Excess delay 5ns

Excess delay 50ns

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Small-Scale Amplitude Statistics Parameters

• The results demonstrate that lognormal, Nakagami and Weibull fit the measurement data well.

• Parameters of these distributions (i.e. standard deviation of lognormal PDF, m-parameter of Nakagami PDF and b-shape parameter of Weibull PDF) can be modeled by a lognormal distribution, respectively

• These parameters are almost constant across the excess delay

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Standard Deviation of Lognormal PDF – LOS

0 0.5 1 1.5 2 2.50

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Lognormal Standard Deviation

CD

F

Lognormal Standard Deviation CDF (Apart1-LOS)

Empirical CDFLognormal CDF

0 0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


CD

F

Lognormal Standard Deviation CDF (Apart2-LOS)


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Standard Deviation of Lognormal PDF – NLOS

0 0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


CD

F

Lognormal Standard Deviation CDF (Apart1-NLOS)


0 0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


CD

F

Lognormal Standard Deviation CDF (Apart2-NLOS)


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

m-Nakagami Parameter – LOS

0 0.5 1 1.5 20

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Nakagami-m Values

CD

F

Nakagami-m Values CDF (Apart1-LOS)


0 0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Nakagami-m Values

CD

F

Nakagami-m Values CDF (Apart2-LOS)


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

m-Nakagami Parameter – NLOS

0 1 2 3 4 5 6 70

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Nakagami-m Values

CD

F

Nakagami-m Values CDF (Apart1-NLOS)


0 0.5 1 1.5 20

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Nakagami-m Values

CD

F

Nakagami-m Values CDF (Apart2-NLOS)


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

b-Weibull Parameter – LOS

0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Weibull-b Values

CD

F

Weibull-b Values CDF (Apart1-LOS)


0.5 1 1.5 2 2.5 3 3.5 40

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Weibull-b Values

CD

F

Weibull-b Values CDF (Apart2-LOS)


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

b-Weibull Parameter – NLOS

0 1 2 3 4 5 6 7 80

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Weibull-b Values

CD

F

Weibull-b Values CDF (Apart1-NLOS)


0.5 1 1.5 2 2.5 30

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Weibull-b Values

CD

F

Weibull-b Values CDF (Apart2-NLOS)


September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Variations of Lognormal- with Delay – LOS

0 10 20 30 40 50 600

0.5

1

1.5

2

2.5Lognormal Standard Deviation vs. Excess Delay (Apart1-LOS)

Excess Delay, [ns]

Lo

gn

orm

al S

tan

da

rd D

evi

atio

n

0 10 20 30 40 50 60 70 800

0.5

1

1.5

2

2.5Lognormal Standard Deviation vs. Excess Delay (Apart2-LOS)

Excess Delay, [ns]

Lo

gn

orm

al S

tan

da

rd D

evi

atio

n

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Variations of Lognormal- with Delay – NLOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Variations of Nakagami-m with Delay – LOS

0 10 20 30 40 50 600.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2Nakagami-m Values vs. Excess Delay (Apart1-LOS)

Excess Delay, [ns]

Na

kag

am

i-m

Va

lue

s

0 10 20 30 40 50 60 70 800

0.5

1

1.5

2

2.5

3Nakagami-m Values vs. Excess Delay (Apart2-LOS)

Excess Delay, [ns]

Na

kag

am

i-m

Va

lue

s

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Variations of Nakagami-m with Delay – NLOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Variations of Weibull-b with Delay – LOS

0 10 20 30 40 50 600.5

1

1.5

2

2.5

3Weibull-b Values vs. Excess Delay (Apart1-LOS)

Excess Delay, [ns]

We

ibu

ll-b

Va

lue

s

0 10 20 30 40 50 60 70 800.5

1

1.5

2

2.5

3

3.5

4Weibull-b Values vs. Excess Delay (Apart2-LOS)

Excess Delay, [ns]

We

ibu

ll-b

Va

lue

s

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Variations of Weibull-b with Delay – NLOS

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Small-Scale Amplitude Statistics Parameters

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Conclusion

• Frequency domain technique UWB measurement campaign has been carried out in indoor residential environment (high-rise apartments) covering frequencies from 3-10 GHz.

• Measurement covered both LOS & NLOS scenarios.• Channel measurement results and parameters which

characterize both the large-scale and small-scale parameters of the channel are reported.

September 2004


doc.: IEEE 15-04-0452-01-004a

Submission

Reference

1. B. Kannan et. al., “Characterization of UWB Channels: Small-Scale Parameters for Indoor and Outdoor Office Environment,” IEEE 802.15-04-0385-00-04a, July 2004.

doc.: ieee 15-04-0452-01-004a submission september 2004 chia-chin chong, samsung (sait)slide 1...

Documents

samsung saitslide

ieee p802

property of ieee

measurement data

korea slide

frequencydomain parameters

uwb channel model

channel models