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Digital Modulation. Better performance and more cost effective than analog modulation methods (AM, FM, etc.) Used in 2 nd generation (2G) cellular systems in U.S. from 1998 - present AT&T Wireless, Verizon Wireless, Sprint, T-mobile, Cingular (now AT&T), Nextel (now Sprint), etc.

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digital modulation
Digital Modulation
  • Better performance and more cost effective than analog modulation methods (AM, FM, etc.)
  • Used in 2nd generation (2G) cellular systems in U.S. from 1998 - present
    • AT&T Wireless, Verizon Wireless, Sprint, T-mobile, Cingular (now AT&T), Nextel (now Sprint), etc.
  • Advancements in VLSI, DSP, ASICs, etc. have made digital solutions practical and affordable

ECE 4730: Lecture #12

digital modulation1
Digital Modulation
  • Performance advantages:

1) Resistant to noise, fading, & interference

2) Combine multiple information types (voice, data, & video)

in single transmission channel

3) Improved security (e.g. encryption)  deters phone

cloning + eavesdropping

4) Error coding to detect/correct transmission errors

5) Signal conditioning to combat hostile MRC environment

6) Implement mod/dem functions using DSP software

ECE 4730: Lecture #12

digital modulation performance
Digital Modulation Performance
  • Many types of digital modulation methods  subtle differences
  • How to choose appropriate method??
  • Performance factors to consider

1) Low Bit Error Rate (BER) at low SNR  power efficiency

2) Resistance to interference (ACI & CCI) & fading

3) Occupies minimum amount of BW  spectral efficiency

4) Easy and cheap to implement  mobile unit

5) Efficient use of battery power  mobile unit

ECE 4730: Lecture #12

slide4

Digital Modulation Performance

  • Power Efficiency p
    • Ability of modulation technique to preserve quality of digital message at low power levels (low SNR)
  • Specified as Eb/No @ some BER (e.g. 10-5) where
    • Eb : energy/bit and No : noise energy/bit
  • Tradeoff between signal power vs. signal quality  BER  as Eb / No
  • **Note that this is NOT related to DC/RF efficiency of Tx power amplifier**

ECE 4730: Lecture #12

digital modulation performance1
Digital Modulation Performance
  • Bandwidth Efficiency B
    • Ability of modulation technique to accommodate data in a limited BW
  • Tradeoff between data rate (R) and occupied BW
    • BW  as R
  • Symbol Period = Ts
  • Signal BW = Bs1 / Ts R

ECE 4730: Lecture #12

digital modulation performance2

PSD

. . .

f

1 / Ts = FNBW

0

0

0

1

0

0

1

1

Symbol Period = Ts

Signal BW = Bs1 / Ts

Digital Modulation Performance
  • For a digital signal :
  • Each pulse or “symbol” having mfinite states represents n = log2m bits/symbol  e.g. m = 0 or 1 (2 states) n = 1 bit/symbol

ECE 4730: Lecture #12

digital modulation performance3
Digital Modulation Performance
  • Maximum BW efficiency  Shannon’s Theorem

C: channel capacity (bps)

B : RF BW

  • Note that CB (expected) but also C S/N unexpected??
    • Increase in signal power translates to increase in channel capacity!!
    • Large S/N easier to differentiate between multiple signal states (m) in one symbol n
  • is fundamental limit that cannot be achieved in practice  typically only 4060% is realizable

where

ECE 4730: Lecture #12

digital modulation performance4
Digital Modulation Performance
  • Fundamental tradeoff between pand B (in general)
    • If p then B (or vice versa)
  • Example: add error control bits to data stream and keep same data rate
    • Ts so Bs so B … but error bits will allow lower Eb / No for same BER so p
  • Is p vs. Btradeoff worth it??
    • Use other factors to evaluate  complexity, resistance to MRC impairments, etc.

ECE 4730: Lecture #12

signal bandwidth

1

B’

0.5

f

fc

B”

B”’

Signal Bandwidth
  • Many definitions depending on application
    • All use Power Spectral Density (PSD) of modulated bandpass signal
    • FCC definition of occupied BW  BW contains 99% of signal power

B’ : half-power (3 dB) BW

B” : null-to-null BW

B’” : absolute BW

range where PSD > 0

ECE 4730: Lecture #12

line coding

Tb

0

0

0

0

1

1

1

Tb

0

1

0

1

0

1

0

Line Coding
  • Different types of coding used for baseband digital signals
    • Choice depends on desired spectral properties
  • Unipolar  0 or V
  • Bipolar V or V
  • Non Return to Zero (NRZ)
  • Return to Zero (RZ)

ECE 4730: Lecture #12

line coding1

PSD

Tb

V

0

1

1

0

f

. . .

Rb = 1 / Tb

Line Coding
  • Unipolar NRZ
    • Advantage : narrow spectral width
    • Disadvantage : large DC component  data can’t be passed thru circuits that block DC (e.g. phone line!)
    • Disadvantage : no zero return  hard to synchronize (decoding errors)

ECE 4730: Lecture #12

line coding2

PSD

Tb

V

0

. . .

1

0

1

f

2Rb = 2 / Tb

Line Coding
  • Unipolar RZ
    • Disadvantage : wide spectral width
    • Advantage : smaller DC component
    • Advantage : better synchronization  easier to decode

ECE 4730: Lecture #12

line coding3

PSD

Tb

+V

0 V

V

f

1

0

1

0

Rb

0.7Rb

Line Coding
  • Manchester NRZ
    • Advantage : zero DC component
    • Advantage : zero crossing  excellent synchronization
    • Moderate spectral width

ECE 4730: Lecture #12

pulse shaping

MRC

Pulse Shaping
  • Rectangular pulses passed thru bandlimited channel (MRC)
    • Symbols smear into adjacent time slots
    • Inter-Symbol Interference (ISI)
    • Increases probability that symbol error will occur

0 1 0 1

0 1 0 1

ECE 4730: Lecture #12

pulse shaping1
Pulse Shaping
  • Spectral shaping of digital pulses done at baseband
    • Reduce ISI due to pulse smearing
    • Reduce spectral width of signal
      • Improve BW efficiency
      • Achieve better control of ACI!
  • Nyquist Criterion
    • Design overall response of system (Tx + MRC + Rx) so at every sampling instant in Rx (0/1 decision point) the response of all other symbols is zero
    • Leads to ideal “brick wall” filter in frequency domain

ECE 4730: Lecture #12

pulse shaping2

Heff (f)

f

Pulse Shaping
  • Ideal Brick Wall Filter
  • In Time Domain

-B +B

ECE 4730: Lecture #12

pulse shaping3
Pulse Shaping
  • Ideal brick wall filter in frequency domain and unlimited time domain pulse response cannot be achieved in practice
  • Other filters can satisfy the Nyquist criterion
    • Raised Cosine (RC) Filter
  • Other pulse shaping filters can also be used that do NOT satisfy Nyquist criterion
    • Gaussian Filter

ECE 4730: Lecture #12

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