interference effects of multi-user ultra-wideband systems

Interference Effects of Multi-User Ultra-wideband Systems

Anup DoshiCarnegie Mellon University July 31, 2003

Outline

Intro

Models

Observations

Summary

What is an Ultra-wideband Signal? Short impulses in

succession

FCC Definition – Bandwidth > 25% of

center frequency 0 200 400 600 800 1000-1

-0.5

0

0.5

1

ns

Impulse Signal

0 2000 4000 6000 8000 10000-100

-80

-60

-40

-20

0

MHzPow

er S

pect

rum

Mag

nitu

de (d

B)

PSD

-0.5

0

0.5

1

Advantages of UWB

Low power levels spread over large spectrum Operates below noise floor of narrowband devices

Possibility of >500Mbps short range

GP

S

Frequency (Ghz)1.6 1.9 5

802.11a

-41 dBm/Mhz“Part 15 Limit”

UWB Spectrum 10.63.1

Source: Intel

PC

S

Potential Applications are Numerous

Personal Area Network Interconnect Computers, Devices, PDAs, Printers Entertainment...TV, Camcorder, DVD Music…MP3, Audio Systems, etc

Safety Through-wall Imaging Sensor Network

Lots of other exciting applicationsBroadband

UWBUWB

LAN/WLAN

UWB

UWB

UWB

Image Sources: Intel, AetherWire

Why Only Now?

Started as impulse radar, 1960’s Primitive forms, simple communication Studied & used by military

New technology enables digital comm., 1990’s Commercial applications seen by several companies 1998 - Petitioned FCC to review potential uses 2003 - FCC approves development of conservative

applications

Problem…

What happens when lots of UWB devices are transmitting in close proximity?

Will the combined noise level be too much for a victim narrowband receiver?

Existing studies claim minimal effects Done by various agencies and companies

Those studies do not examine all cases…

This is my job!

VICTIM

Constant-Distance DistributionMultiple UWB devices located three meters from a victim

Units turn on and off in a 2-state Markov Process

Switching times are Exponential Random Variables Time until on ~ Exponential(λ) => mean 1/λ sec Time until off ~ Exponential(µ) => mean 1/µ sec

Rho=ρ= λ/µ

Characterizing the Transmitters

UnitOff

UnitOn

λ

µ

Characterizing the Transmitters

Total Number on modeled as a Markov Chain

Steady-state probabilities:

0 1 2 N-1 N

Nλ (N-1)λ … λ

µ … Nµ2µ

N

n

n n

Np

)1(

1

2

3

4

5

6

7

8

9

10

0 0.5 1 1.5 2 2.5 3 3.5 4

How Does the System Act Over Time?

λ =1, µ=2

1

2

3

4

5

6

7

8

9

10

0 0.5 1 1.5 2 2.5 3 3.5 4

How Does the System Act Over Time?

Total Number of Units Onλ =1, µ=2

Noise Level in Victim Receiver

Each UWB signal modeled as White Noise Total Noise= N0+M(t)*N1

Ambient Noise Floor(=kTw)

Number of Transmitters On(Markov Chain)

Power Received at Victim from UWB Signal

Some Properties of This Model

Autocorrelation Spectral Density

-100 -50 0 50 1000

1

2

3

4

5

6

7

8

Hz

Ma

gn

itu

de

PSD = fft(Rx(t))

-5 0 50

0.5

1

1.5

2

2.5

tau (sec)

Ma

gn

itu

de

Rx(tau) = E(M(t)M(t+tau))

Probability of Error in Receiver

On Average:

101 *

2*))((

NiN

EQitMPP

bk

ierr

0 0.5 1 1.5 2 2.5 30

0.05

0.1

0.15

0.2

0.25

0.3

0.35Average Probabilty of Error

rho

Pe

rr

20 units

10 units

(µ=1)

Other Ways to Describe Model

Probability of Outage P(outage)=Probability( Perr > Pe* )

Pe*=.1, .01

Perr=

Expected Time of Outage E(T10) = T1+aN,1E(T20)

E(T20)=T2+aN,2E(T10)+bN,2E(T30) … E(TN0)=TN+E(T(N-1)0)

10 )(

2

NtMN

EQ

b

P(outage), Expected Time of Outage

0 0.5 1 1.5 2 2.5 30

2

4

6

8

10

12E(outage)

t (s

ec

)

rho

12 units

10 units

3m radius

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

rho

P(o

uta

ge

)

P(outage)

10 units

12 units

3m radius(µ=1) (µ=10)

VICTIM

Random-Distance DistributionUWB devices distributed uniformly in a circular area around victim

Properties of Random-Distance Model

Moved to a computer simulation

Experimentally calculated: P(outage), Expected Time of Outage, Max and mean power levels over time

Done on Matlab – Monte Carlo simulation

Example Simulation Run

0 0.5 1 1.5 2 2.5 3 3.5 4-52

-50

-48

-46

-44

-42

-40

-38

-36

-34

time

dB

m

Interference Level

0 1 2 3 4 5 6 7 8 9

-120

-110

-100

-90

-80

-70

-60

-50

-40

-30

time

dB

m

Interference Level

Example Simulation Run

Example Simulation Run

0 5 10 15 20-120

-110

-100

-90

-80

-70

-60

-50

-40

-30

time

dB

m

Interference Level

0 5 10 15 20 25 30 35 40

-120

-110

-100

-90

-80

-70

-60

-50

-40

-30

time

dB

m

Interference Level

Example Simulation Run

P(outage) & Expected Time of Outage

0 0.5 1 1.5 2 2.5 30

0.2

0.4

0.6

0.8

1

Probability of Outage

rho

Po

uta

ge

Random-distanceradius=3m

Constant-distanceradius=3m

10 units

0 0.5 1 1.5 2 2.5 30

1

2

3

4

5

6

7

8

9Expected Time of Outage

tim

e (s

ec)

rho

Random-distanceradius=3m

Constant-distanceradius=3m

10 units(µ=1) (µ=10)

Max/Mean Power Levels

0 5 10 15 20 25 30 35 40-90

-80

-70

-60

-50

-40

-30

-20

Number of Transmitters in 10m radius

dB

m

Average Max and Mean Power Levels over 500 simulations

Average Max Power

Average Mean Power

Allowed Interference Level

Observations

Multiple transmitters will cause major problems in worst cases

Such situations may soon arise in real-life situations

Important to consider every possible case in testing

Broadband

Future Work

Need to consider many more variables Receiver type Frequency, PRR Different distributions

Once 802 Standard comes out, incorporate into model Possibly Multi-Band OFDM (TI, Intel) Possibly Dual-Band (Time Domain, Motorola)

Summary

Characterized an aggregate of UWB transmitters

Realized various methods of measuring effect on victim receiver

Concluded that as number of UWB transmitters increase, performance of victim receiver attenuates

Acknowledgments

Prof Baum

Prof Noneaker, Prof Xu

ECE Faculty and Grads

NSF