Top Banner
#7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence, Kansas 66045 Phone: (785) 864-4833 FAX:(785) 864-7789 e-mail: [email protected] http://www.ittc.ku.edu/ How to cope with last hop impairments? Part 4 Fading #7 All material copyright 2006 Victor S. Frost, All Rights Reserved
17

#7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

Dec 21, 2015

Download

Documents

Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 1

Victor S. FrostDan F. Servey Distinguished Professor Electrical Engineering and Computer

ScienceUniversity of Kansas2335 Irving Hill Dr.

Lawrence, Kansas 66045Phone: (785) 864-4833 FAX:(785) 864-

7789 e-mail: [email protected]

http://www.ittc.ku.edu/

How to cope with last hop impairments?

Part 4Fading

#7

All material copyright 2006Victor S. Frost, All Rights Reserved

Page 2: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 2

How to cope with last hop impairments?

• Techniques for coping with noise– Forward error detection/correction coding– Automatic Repeat reQuest (ARQ)– Co-existance or modifications to end-to-end protocols

•Techniques for coping with multipath fading fading mitigation techniques, e.g., – Equalizers– Diversity– RAKE receivers– OFDM

Page 3: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 3

Equalizers

• Fading can be viewed as transmission through a linear time varying system.

• An equalizer estimates the channel response as a function of time and compensates for the pulse spreading and thus reduces ISI

Channel

Channel changes as a function of time

Equalizer

Channel estimate

Page 4: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 4

Equalizers

• Equalizers are– Common

• Dial-up modems• Cellular systems

– Often use training signals• A known signal is transmitted• At the receiver the known transmitted signal and the

corresponding distorted waveform are used to estimate the expected channel characteristics

• Assume the channel is “constant” between transmissions of training signals

• Training signals add overhead and reduce efficiency– Can be non-linear

• Equalizers differ in the computational complexity and performance

Page 5: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 5

Equalizers Diversity

• Equalizers rely on one received waveform

• That maybe in a deep fade• Diversity can provide significant

performance when one of the independent paths are in a deep fade.

Page 6: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 6

Diversity

Channel 1

Channel i

Channel N

Processing

Detected Bits

Page 7: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 7

Diversity

• Obtain multiple independent samples of the received signal

• Process the multiple independent samples to reduce the BER

• Independent samples maybe obtained via spatial diversity,– Multiple receive antennas

• Separated on the order of ½ wavelength• MIMO (multiple in/multiple out) uses more

multiple transmit and receive antennas

Page 8: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 8

Diversity

• Independent samples maybe obtained via frequency diversity,– Same information over different frequency channels– Expands the required bandwidth

• Independent samples maybe obtained via time diversity,– Same information transmitted at different times– For fixed rate this also increases the bandwidth

requirements

• Diversity can provide significant performance inprovement

Page 9: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 9

RAKE receiver

• With CSMA a bit, lasting Tb sec is divided into N chips of length Tc

• The sequence of the N chips are selected to have a low autocorrelation

• Thus for CDMA the delay profile of the channel provides multiple versions of the transmitted signal at the receiver.

-30 dB

-20 dB

-10 dB

0 dB

0 1 2 5

Pr()

(µs)

Power Delay Profile

Page 10: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 10

RAKE receiver

• A RAKE receiver estimates the delay and amplitude of the delay profile

• Obtains independent samples • Thus providing a form of time diversity.• Only a few 2-3 samples provide

significant performance improvement• IS-95 cell systems use a RAKE receive in

both the base stations and hand sets

Page 11: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 11

Rake Receiver

From: W. Stallings, Data and Computer Communications, Pearson, 2006

Page 12: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 12

Orthogonal Frequency-division Multiplexing-OFDM

• Multicarrier Modulation• Uses a large number of parallel narrow-

band channels, each on a unique sub carrier

• Combats– Multipath– Narrow-band interference

• Problems– Sensitive of frequence and phase noise– Has large Peak-to-average ratio resulting is

inefficient use of power amplifiers

Page 13: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 13

• Assume for a a base system – Bit rate = R– Channel bandwidth = Nfb @ fc

– Using all the channel bandwidth the bit duration would be 1/R=Tb

• Process the R b/s stream into N streams each at a rate of R/N, now for each stream the symbol time is N/T.

• Note because the symbol time has increased its susceptibility to multi-path induces ISI is decreased

Orthogonal Frequency-division Multiplexing-OFDM

Page 14: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 14

Orthogonal Frequency-division Multiplexing-OFDM

• The data is “distributed” over the N sub-carriers in a special way, specifically, the frequencies are selected to be orthogonal

• Different types of modulation can be used, e.g., QPSK

• Equalizers may not be needed when using OFDM

From: W. Stallings, Wireless Communications & Networks, Pearson 2005

Page 15: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 15

Orthogonal Frequency-division Multiplexing-OFDM

• Examples:– IEEE 802.11a uses 52 subcarriers– MMDS uses 512 subcarriers– Powerline systems

Page 16: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 16

References #7

• W. Stallings, Data and Computer Communications, Pearson, 2006

• W. Stallings, Wireless Communications & Networks, Pearson 2005

Page 17: #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence,

#7 17

References