Project: IEEE P82.15 Working Group for Wireless Personal Area Networks N (WPANs( WPANs) Title: [UWB Channel Measurement Results in Indoor Residential Environment High-Rise Apartments] Date Submitted: [19 May, 24] Source: [Chia-Chin Chong, Youngeil Kim, SeongSoo Lee] Company [Samsung Advanced Institute of Technology (SAIT)] Address [RF Technology Group, i-networking Lab, P. O. Box 111, Suwon 44-6, Korea.] Voice:[+82-31-28-6865], FAX: [+82-31-28-9555], E-Mail: [chiachin.chong@samsung.com] Re: [Response to Call for Contributions on IEEE 82.15.4a Channel Models] Abstract: [This contribution describes the UWB channel measurement results in indoor residential environment. Measurements were conducted in several types of high-rise apartments based in several cities in Korea. It consists of detailed characterization of the path loss and temporal-domain parameters of the UWB channel with bandwidth from 3 to 1 GHz.] Purpose: [Contribution towards the IEEE 82.15.4a Channel Modeling Subgroup.] Notice: This document has been prepared to assist the IEEE P82.15. 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 P82.15. Slide 1
UWB Channel Measurement Results in Indoor Residential Environment High-Rise Apartments Chia-Chin Chong, Youngeil Kim, SeongSoo Lee Samsung Advanced Institute of Technology (SAIT), Korea Slide 2
Outline Motivation Measurement Setup & Environment Data Analysis & Post-Processing Channel Measurement Description Measurement Results Conclusion Future Work Slide 3
Motivation Study the UWB wave propagation characteristics in indoor residential environment Develop a channel model suitable for UWB applications in high-rise apartments Submit contributions to the IEEE82.15.4a channel modeling subgroup standardization activities Slide 4
Measurement Setup (1) Frequency domain technique using VNA Center frequency, f c : 6.5GHz Bandwidth, B : 7GHz (i.e. 3-1GHz) Delay resolution, τ : 142.9ps (i.e. τ=1/b) No. frequency points, N : 161 Frequency step, f : 4.375MHz (i.e. f=b/(n-1)) Max. excess delay, τ max : 229.6ns (i.e. τ max =1/ f) Sweeping time, t sw : 8ms Max. Doppler shift, f d,max : 1.25Hz (i.e. f d,max =1/t sw ) Slide 5
Measurement Setup (2) UWB wideband 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, 3 time-snapshots of the channel complex frequency responses are recorded Slide 6
TX antenna Measurement Setup (3) RX antenna Propagation Channel Coaxial Cables Vector network analyzer (Agilent 8722ES) Low Noise Amplifier (Miteq AFS5) Power Amplifier (Agilent 832A) Laptop with LabVIEW GPIB Interface Attenuator (Agilent 8496B) Slide 7
UWB Planar Dipole Antenna Slide 8
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 4-bedrooms 5-bedrooms (to be done!) Both LOS and NLOS configurations TX-RX antennas: Separations: up to 2m 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. 8-1 locations) To date, in total of 12, channel complex frequency responses are collected (i.e. 2 apartments x 8 RX local points x 25 spatial points x 3 time snapshots 2x8x25x3=12,) Slide 9
3-Bedroom Apartment Grid-Measurement Slide 1
4-Bedroom Apartment (1) Slide 11
4-Bedroom Apartment (2) Living Room Bedroom 4 Bedroom 3 Kitchen Slide 12
Measurement Results (1) Channel Frequency Response -5 Normalized amplitude [db] -1-15 -2-25 -3 3 4 5 6 7 8 9 1 Frequency [GHz] Slide 13
Measurement Results (2) Slide 14
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 Slide 15
Complex Passband IFFT Slide 16
Channel Model Description Path loss Temporal-domain parameters: RMS delay spread, τ rms Mean excess delay, τ m No. of paths within 1dB of peak, NP1dB No. of paths within 2dB of peak, NP2dB No. of paths within 3dB of peak, NP3dB Slide 17
Path Loss Path loss (PL) vs. Distance (d): d PLdB ( d ) = PL + 1n log1 d d = 1m PL : intercept n : path loss exponent Perform linear regression to the above equation with measured data to extract the required parameters Slide 18
Path Loss vs. Distance LOS 6 Path Loss under LOS Scenario in 3-Bedroom Apartment Data Linear Regression 58 56 Path Loss (db) 54 52 68 66 Path Loss under LOS Scenario in 4-Bedroom Apartment Data Linear Regression 5 64 48 1 2 3 4 5 6 7 8 1log (Distance) (m) 1 Path Loss (db) 62 6 58 56 54 52 5 Slide 19 48 1 2 3 4 5 6 7 8 1log (Distance) (m) 1
62 May 24 Path Loss vs. Distance NLOS Path Loss under NLOS Scenario in 3-Bedroom Apartment Data Linear Regression 6 58 Path Loss (db) 56 54 8 Path Loss under NLOS Scenario in 4-Bedroom Apartment Data Linear Regression 52 75 5 5 5.5 6 6.5 7 7.5 8 8.5 9 1log (Distance) (m) 1 Path Loss (db) 7 65 6 55 Slide 2 5 2 3 4 5 6 7 8 9 1log (Distance) (m) 1
Path Loss Results Slide 21
Temporal-domain Parameters These parameters were obtained after taking frequency domain Hamming windowing, passband IFFT & temporal domain binning with bin size 1ps Slide 22
Local Mean Excess Delay, τ mean,local [ns] 8 6 4 2 May 24 Mean Excess Delay vs. Distance LOS Local Mean Excess Delay vs. Distance - LOS (3-Bedroom Apartment) 12 Local mean excess delay Local mean excess delay + Std 1 Local mean excess delay - Std Average mean excess delay = 5.88ns Standard deviation mean excess delay = 2.6ns -2 1 1.5 2 2.5 3 3.5 4 4.5 5 Distance, d [m] Local Mean Excess Delay, τ mean,local [ns] 8 6 4 2 Local Mean Excess Delay vs. Distance - LOS (4-Bedroom Apartment) 12 Local mean excess delay Local mean excess delay + Std 1 Local mean excess delay - Std Average mean excess delay = 5.1ns Standard deviation mean excess delay = 3.8ns Slide 23-2 1.5 2 2.5 3 3.5 4 4.5 5 5.5 Distance, d [m]
Local Mean Excess Delay, τ mean,local [ns] 5 4 3 2 1 May 24 Mean Excess Delay vs. Distance NLOS Local Mean Excess Delay vs. Distance - NLOS (3-Bedroom Apartment) 7 Local mean excess delay Local mean excess delay + Std 6 Local mean excess delay - Std Average mean excess delay = 36.9ns Standard deviation mean excess delay = 14.6ns 3.5 4 4.5 5 5.5 6 6.5 7 Distance, d [m] Local Mean Excess Delay, τ mean,local [ns] 5 4 3 2 1 Local Mean Excess Delay vs. Distance - NLOS (4-Bedroom Apartment) 7 Local mean excess delay Local mean excess delay + Std 6 Local mean excess delay - Std Average mean excess delay = 14.97ns Standard deviation mean excess delay = 6.15ns Slide 24 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 Distance, d [m]
Local RMS Delay Spread, τ rms,local [ns] 16 14 12 1 8 May 24 RMS Delay Spread vs. Distance LOS Local RMS Delay Spread vs. Distance - LOS (3-Bedroom Apartment) 2 Local RMS delay spread Local RMS delay spread + Std 18 Local RMS delay spread - Std Average RMS delay spread = 14.1ns Standard deviation RMS delay spread = 2.42ns 6 1 1.5 2 2.5 3 3.5 4 4.5 5 Distance, d [m] Local Local RMS delay spread, τ rms,local [ns] Local Local RMS delay spread vs. Distance - LOS (4-Bedroom Apartment) 17 16 15 14 13 12 11 1 9 Local RMS delay spread Local RMS delay spread + Std Local RMS delay spread - Std Average RMS delay spread = 12.48ns Standard deviation RMS delay spread = 1.95ns Slide 25 8 1.5 2 2.5 3 3.5 4 4.5 5 5.5 Distance, d [m]
Local Local RMS delay spread, τ rms,local [ns] 44 42 4 38 36 34 32 3 May 24 RMS Delay Spread vs. Distance NLOS Local Local RMS delay spread vs. Distance - NLOS (3-Bedroom Apartment) 48 Local RMS delay spread 46 Local RMS delay spread + Std Local RMS delay spread - Std 28 3.5 4 4.5 5 5.5 6 6.5 7 Distance, d [m] Local Local RMS delay spread vs. Distance - NLOS (4-Bedroom Apartment) Average RMS delay spread = 38.61ns 6 Standard deviation RMS delay spread = 4.16ns Local RMS delay spread Local RMS delay spread + Std Local RMS delay spread Average - Std RMS delay spread = 21.91ns 5 Standard deviation RMS delay spread = 8.85ns Local Local RMS delay spread, τ rms,local [ns] 4 3 2 1 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 Distance, d [m] Slide 26
1 May 24 Distribution of No. of Paths LOS Distribution of the number of paths - LOS (3-bedroom apartment) Probability Probability Probability.5 2 4 6 8 1 12 14 16.4 NP1dB.2 2 4 6 8 1 12 14.2 NP2dB.1 5 1 15 2 25 3 35 4 45 NP3dB Probability Probability.4.2 Distribution of the number of paths - LOS (4-bedroom apartment) 2 4 6 8 1 12 14 16 18.2 NP1dB.1 2 4 6 8 1.2 NP2dB Probability.1 Slide 27 5 1 15 2 25 3 35 NP3dB
.2 May 24 Distribution of No. of Paths NLOS Distribution of the number of paths - NLOS (3-bedroom apartment) Probability Probability Probability.1 1 2 3 4 5 6.2 NP1dB.1 5 1 15 2 25 3 35 4.2 NP2dB.1 1 2 3 4 5 6 7 8 9 NP3dB Probability Probability.4.2 Distribution of the number of paths - NLOS (4-bedroom apartment) 1 2 3 4 5 6 7 8 9.2 NP1dB.1 5 1 15 2 25 3 35 4.2 NP2dB Probability.1 1 2 3 4 5 6 7 8 9 NP3dB Slide 28
Conclusion Frequency domain technique UWB measurement campaign has been carried out in various types of high-rise apartments covering frequencies from 3 to 1 GHz. Measurement covered both LOS & NLOS scenarios. Channel measurement results for path loss and temporal-domain parameters (e.g. mean excess delay, RMS delay spread, number of paths) are.presented Slide 29
Future Work Extract S-V channel parameters Extract small-scale amplitude statistics Propose a suitable statistical channel model Slide 3