UWB SPATIAL FADING AND SMALL SCALE CHARACTERIZATION IN

UNDERGROUND MINES

Abdellah Chehri1, 2, Paul Fortier1, Hasnaa Aniss2, Pierre-Martin Tardif2

1 Department of Electrical and Computer Engineering, Laval University, Quebec, Canada 2 LRCS laboratory, 450, 3e Avenue, Val-d’Or, Quebec, Canada

ABSTRACT This paper reports on experimental results of UWB channel propagation in underground mines. Because the mine architecture and topology is often irregular and composed of interconnected corridors, two cases were treated, namely LOS and NLOS. The goal of this work is not to formulate a channel model for UWB systems or to provide a universal model for all environments in which UWB devices will be operating, but rather to provide a set of tools that can be used to fairly evaluate the performance of different UWB physical layer proposals in real channels such as underground mines. This work was carried out by the Underground Communications Research Laboratory, LRCS(∗), in the MMSL-CANMET experimental mine (Mining and Mineral Sciences Laboratories - Canadian Center for Minerals and Energy Technology) in Val-d’Or, Canada.

1. INTRODUCTION

Ultra wideband radios have relative bandwidths larger than 20% or absolute bandwidths of more than 500 MHz. UWB is a wireless technology that can operate at very low-power density to communicate at high data rates over short distances. It was initially developed for military applications and has started moving into civilian use [1], [2].

Low power, low cost, high data rates, precise positioning capability and no interference, UWB seems to have it all. Ultra wideband has been described as one of the most promising technologies of our times. UWB can be integrated into a large variety of applications, in particular into anti-collision radars, imagery systems (for example ground penetrating radar), and short range indoor communications, primarily for the next generation high bit rate Wireless Personal Area Networks (WPANs), WSN (Wireless Sensor Networks), logistics (package tracking), (*) The LRCS laboratory aims to develop research programs related to wireless communications in underground mines. Research is conducted in the MMSL-CANMET experimental mine in Val-d'Or, Quebec, Canada.

security applications (localizing workers in their workspace) and search and rescue [3].

UWB technology used for WPANs will constitute a key application. The UWB technology industry is currently developing, through the Institute of Electrical and Electronics Engineers (IEEE), the standards relating to wireless UWB networks. Availability of industry standards relative to UWB systems will facilitate regulations and rule drafting. It will also facilitate the introduction of UWB devices in the market [4].

Some channel propagation measurements in underground mines have been published. Nerguizian et al [5] made measurements and analysis for narrowband and wideband channels in an underground mine; other narrowband channel measurements are reported in [6]. UHF radio wave propagation in underground environments was analyzed in [7].

This work gives the first UWB measurement set in a confined environment such as an underground mine. However, other UWB channel measurement research has been reported for several environments such as residential, commercial, industrial, and open air. All these measurements are summarized in the IEEE 802.15.4a final report [8].

Our goal being to look further into the UWB channel knowledge in mine and underground environments, we chose an approach resting on a series of measurements.

The remainder of the paper is organized as follow: details about the environment, the measurement campaign and the methodology used in data acquisition are given in the next section. Section 3 deals with post-processing analysis. The measurements and the small scale analysis results are given in Section 4. Section 5 concludes the paper.

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2. MEASUREMENT CAMPAIGN

Measurements were carried out in an underground gallery on the 70 m level of the MMSL-CANMET laboratory mine located 16 km from Val-d’Or, Canada [9]. The dimensions of the gallery varied between 2.5 m and 3 m in width and the height was about 3 m, typical of a conventional mine (Fig. 1). Two cases, LOS and NLOS were analyzed (Fig. 2).

Fig. 1: MMSL-CANMET gallery.

Fig. 2: Map of MMSL-CANMET (70 m level).

Fig. 3 illustrates the transceiver configuration for the channel sounder. A vector networks analyzer (VNA) was used for measuring the channel frequency response. VNAs are popular measuring devices for UWB channels [10]-[13] as frequency-domain measurements are easier to carry out than time-domain measurements [14].

The VNA recorded the variations of 1601 complex tones across the 2-5 GHz frequency band. The resulting frequency resolution of 1.875 MHz implied a maximum resolvable delay of 533 ns.

Both transmitter and receiver were equipped with an Electro-Metrics EM-6116 antenna. At the transmitter side,

we mounted the antenna on a positioning table 1 m above the floor. The receiving antenna was also fixed at the same height. We made sure that there were no movements of people or equipment between the two antennas. We conducted the UWB channel measurement campaigns to characterize the small scale fading behaviour of channels for wireless access point scenarios, and short-range peer-to peer systems; other applications with mobile terminals should take the variability of the channel over space into account. The Tx/Rx distance was fixed at 9 m (typical distance for short communication systems such as wireless sensor networks and localization systems). Impulse responses collected in a same local area are very similar due to channel variations over short distances. Therefore, small scale fading is interesting to analyze in the time domain. In order to accomplish that, impulse response measurements were made at 40 locations, arranged in an 8×5 square grid with 7 cm spacing, slightly smaller than half the wavelength at the lowest measured frequency (2 GHz), to obtain approximately independent samples. For both LOS and NLOS cases, we took three measurements points, separated by 10 cm at the receiver locations. This is illustrated in Fig. 3.

Fig. 3: Measurement setup.

3. MEASUREMENT DATA PROCESSING

3.1. Spatial fading The first step of the measurement data processing consists in establishing a prediction model [15], [16] of the attenuation starting from the basic parameters, such as distance between Tx and Rx, visibility, antenna heights, antenna characteristics, etc. Many approaches to the channel modeling exist. A description of these approaches can be found in [15]. Hashemi [16] has also done extensive propagation modeling for the indoor channel. The IEEE 802.15 working group for wireless personal area networks is considering UWB systems for its physical layer standard. Based on many measurement campaigns, a modified version of the Saleh-Valenzuela model has been adopted to allow fair performance comparisons for specific UWB implementation simulations [17]. We will describe several parameters, usually used for modeling such channels. All these parameters are obtained from our measurements by

TX

LOS NLOS

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7 cm

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using a complex baseband IFFT transform. The channel impulse response is computed from complex vectors recovered from the VNA. Figures 4 and 5 show the impulse responses for the LOS and NLOS cases.

25 30 35 40 45 50 55 600

1

2

x 10-4 LOS

Time in ns

Mag

nitu

de

Fig. 4: Magnitude of the complex impulse response in the

LOS case.

25 30 35 40 45 50 55 60

1

2

3

4

5

6

7

8

x 10-5 NLOS

Time in ns

Mag

nitu

de

Fig. 5: Magnitude of the complex impulse response in

the NLOS case.

The average received power is estimated from the measured frequency response using the following equation:

2

101 1

( ) 10 log ( , ; )N M

i ji j

P d H f t d= =

= −

∑∑ (1)

where N is the number of observed frequencies and M is the number of frequency response snap shots over time at d meters.

Figures 6 and 7 present, for the LOS and NLOS cases, the received signal and the cumulative distribution function of the received signal energy, respectively. These figures show that the variation of received signal is small (less than 3 dB for LOS, and 4 dB for NLOS). This result confirms the robustness of UWB communication systems, insofar as

multipath is concerned, which is manifested by small variations of the received signal at various grid locations.

0 5 10 15 20 25 30 35 40-74

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-70

-68

-66

-64

-62

Number of point

Rec

eive

d si

gnal

in d

B

LOS

NLOS

Fig. 6: Received signal for the LOS and NLOS cases.

Fig. 7: Cumulative distribution functions of the received

signal for the LOS and NLOS cases. 3.2. Frequency dependence path loss The path loss (PL) defines the relationship between transmitted power ( TXP ) and received power ( RXP ) in a far-field RF link. This relation was first given by Harald Friis:

222

2

)(1

4)4(),(

kdGG

dGG

PPdfP RXTXRXTX

TX

RX ===π

λ (2)

In this formula, RXG and TXG are the receive and transmit antenna gains, respectively, d is the distance between the antennas, λ is wavelength, and λπ /2=k is the wave number. The reason for writing Friiss law in a non-standard way (using wave number) will become clear momentarily. The main idea of Friiss Law is that the far-field power rolls off as the inverse square of the distance ( 2/1 d ). Near-field links do not obey this relationship. Near-field power rolls

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0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Power (dB)

Pro

b (P

<ab

scis

sa)

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off as powers higher than inverse square, typically inverse fourth ( 4/1 d ) or higher. For UWB systems the path loss modeling can be simplified by assuming that the frequency dependence and the distance dependence can be treated independently of each other:

)()(),( fPLfPLdfP ⋅= (3) The distance is assumed to be constant, and the frequency dependence of the path loss is given as:

δ−∝ ffPL )( (4) Equation (4) is adopted in the IEEE 802.15.4a standard channel model [8]. δ is called the frequency decaying factor. To calculate this parameter, we use the least square curve fitting of (4), on the measured data for LOS and NLOS setting (Fig. 8). The corresponding values of δ is estimated to 1.1 for LOS and 1.4 for NLOS.

Fig. 8: Path loss as a function of frequency under (a) LOS and (b) NLOS cases.

4. SMALL SCALE ANALYSIS

The mine galleries constitute a channel with multiple paths. Many obstacles are present (walls, electric wires, ventilation systems, cables and pipes located near the ceiling, etc.) and they more or less act as reflective surfaces for the radio waves. Small scale variations in the channels response are caused by the recombination of the multiple paths. Large scale variations are caused by the losses in open space and the shadowing due to static obstacles or walls. To determine the amplitude variations on a small scale, it is necessary to refer to the average level of the received signal. The small scale effects of the wireless channel are commonly described by a linear filter where the received signal is given by:

)()(*)()( tnthtstr += (5)

where )(ts is the transmitted signal, )(th is the channel impulse response, and )(tn is complex-valued additive white Gaussian noise. The channel impulse response can change as a function of time (or as a spatial variation function) due to the motion of the transmitter or receiver and/or changes in the physical channel itself. If the channel is assumed to be static over the interval of interest, a time-invariant model for the channel can be used:

∑−

=

−=1

0

)()(N

k

jkk

keah θττδτ (6)

where δ is the Dirac delta function, N is the number of resolvable multipaths, kτ are the arrival times of the

multipaths and ka are the path amplitudes. The distributions used to describe arrival times are: standard Poisson, modified 2-state Poisson and double Poisson (Saleh-Valenzuela [18]). This last model is often used to characterize the UWB channel.

For all measurement values (120 locations), we made 40 averaged measurements , ( 1,..., 40)ih i = . We then fitted the data to a Nakagami-m distribution using the inverse normalized variance estimator (INV) [12], [19] for m:

224

22ˆµµ

µ−

=INVm (7)

where

∑=

−=N

i

kik hN

1

1 ||µ (8)

For most measurements, the best fit for the distribution seemed to have a value of m = 1, which corresponds to a Rayleigh distribution (figures 9 and 10). The only exception is for the first components (before 20 ns) in each cluster which can show a strong specular contribution. For the NLOS scenario the value is assumed to be m = 1 (Fig. 11). Fading is observed in wireless communication channels due to multipath. As it accurately models the fading effects for short distance communications, the Rayleigh fading model is frequently used for simulating signal propagations. However, the Rayleigh fading model falls short in describing long distance fading effect with sufficient accuracy. This fact was first observed by Nakagami, who formulated a parametric gamma distribution-based density function to describe the experimental data he obtained [20].

It was show by many researchers using real-life data that the model proposed by Nakagami provides a better explanation for different conditions than the Rayleigh model and provides a better fit to the mobile commu-nication channel data.

2 2.5 3 3.5 4 4.5 5-120

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Frequency (GHz)

Pat

h Lo

ss (

dB)

(a)

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0 20 40 60 80 100 120 140 1600

1

2

3

4

5

Time (ns)

Est

imat

ed m

-par

amet

ers

Fig. 9: m-parameter estimates for each delay bin (LOS

case).

0 0.5 1 1.5 2 2.5 3 3.5 40

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

Estimated m-parameters

PD

F

Fig. 10: Probability density function for the m-

parameter estimated for each delay bin (LOS case).

0 20 40 60 80 100 120 140 1600

1

2

3

4

5

Time (ns)

Est

imat

ed m

-par

amet

ers

Fig. 11: m-parameter estimates for each delay bin

(NLOS case).

5. CONCULSION

In this paper, we performed a small scale analysis for UWB channel propagation in an underground mine. The results showed that the Rayleigh distribution can be used to model

small scale fading for this particular channel. We also found that this result is valid for all delays. This can be explained by the high density of scatterers caused by the walls in the underground mine (this remark is also mentioned by Karedal et al in the case of industrial environment). Finally, it should be noted that our model is markedly different from the 801.15.3a channel model (designed for office environments) where a log-normal distribution is used to model the multipath components. Future works will involve UWB channel characterization for wireless personal area networks where the terminals are typically static, and variations in the channel are mainly caused by moving scatterers, e.g., moving persons.

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