Digital modulation
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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

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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


Digital modulation

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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