#7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer...

17
#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
  • date post

    21-Dec-2015
  • Category

    Documents

  • view

    214
  • download

    0

Transcript of #7 1 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer...

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