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MC-CDMA vs DS-CDMA M. des Noes and D.
Ktenas (presented by Sylvie Mayrargue)
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Outline

• Context of the comparison
• Simulation assumptions
• Asymptotic analysis
• DS and MC-CDMA system models.
• For each detector
• Linear filter description
• Simulation results
• Interpretation
• Conclusion and future work

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Context of the comparison

• Downlink Base station to mobile.
• No channel coding.
• No inter-cell interferences
• Perfect channel estimation and synchronization
• Linear detectors MRC, SU-MMSE and MU-MMSE

Comparison of BER based on simulations (Monte
Carlo) and asymptotic analysis (theory).
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Asymptotic analysis
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• Symbol estimated at the output of a linear
  detector for DS or MC-CDMA system

• ?k and ?k depend on the channel, spreading codes
  and code power matrices.
• ?k results from the filtering of the MAI plus
  the background noise.

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Asymptotic analysis
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• The main results of the asymptotic analysis are
  the followings
• As N,K ? ? and ?K/N is fixed, ?k converges to a
  limit ?.
• As N,K ? ? and ?K/N is fixed, ?k becomes
  gaussian and its variance converges to a limit V2
• An analytical expression of the asymptotic SINR
  is obtained. It is independent of the spreading
  codes.These demonstrations are based on the
  so-called free probability theory.
• Zhang, Chong, Tse  Output MAI distribution of
  linear MMSE multi-user receivers in CDMA
  systems  Information Theory March 2001

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Asymptotic analysis
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AWGN transmission !
Fixed
Gaussian noise
Signal to Interference plus Noise Ratio (SINR)
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References

• MC CDMA
• M.Debbah, W.Hachem, P.Loubaton, M.de Courville
   MMSE Analysis of Certain Large Isometric Random
  Precoded Systems 
• IEEE Trans on Information Theory Vol 49, n5, May
  2003
• DS CDMA
• J.M. Chaufray, W.Hachem, Ph.Loubaton
   Asymptotical Analysis of Optimum and Sub
  optimum CDMA Downlink MMSE Receivers 
• Can be downloaded at http//syscom.univmlv.fr/lou
  baton/index.html

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DS-CDMA system model
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• Channel
• C(c1 c2 cK), d(n) (d1(n), , dK(n))T, P
  diag(P1, , PK)
• Y(n) (Y1(n) , , YN(n))T
• N spreading factor , K number of codes
• W delay spread of the channel (Wlt N)

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DS-CDMA system model
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• Received signal

Noise N(0,?2I)
Useful MAI
ISIMAI
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MC CDMA System model
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MC CDMA System model
2/2
Received signal
Tap delay channel
where is the
channel impulse response.
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MRC Maximum Ratio Combining
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MRC Simulation vs. Asymptotic DS-CDMA
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MRC Simulation vs. Asymptotic MC-CDMA
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MRC Comparison MC-CDMA DS-CDMA
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SU-MMSE
DS-CDMA
MC-CDMA
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SU-MMSE simulation vs asymptotic MC CDMA
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SU-MMSE Comparison DS-CDMA MC CDMA
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MU-MMSE Multiple User MMSE (for DS-CDMA)
MU-MMSE equalize the global channel h(z) c(z)
Asymptotic SINR
Distribution of powers Kc classes of powers
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MU-MMSE Multiple User MMSE (for MC-CDMA)
Asymptotic SINR
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MU-MMSE simulation vs asymptotic DS CDMA
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MU-MMSE DS-CDMA MC CDMA
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Interpretation
?1(N,K)
DS-CDMA
?2(N,K)
DS-CDMA with Cyclic Prefix
Both systems have the same asymptotic SINR
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Interpretation

• Both matrices have the same eigenvalue
  distribution.
• When computing the asymptotic SINR, we only use
  the eigenvalue distribution.
• MC-CDMA and DS-CDMA have the same asymptotic
  SINR.

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Conclusion

• With our assumptions MC-CDMA DS-CDMA in an
  uncoded scenario.
• MC-CDMA receiver is less complex than a DS-CDMA
  receiver ?
• DS-CDMA possibility to perform frequency
  domain equalization (with the same performance),
  but needs one FFT and one IFFT at the receiver
  side.
• MC-CDMA gains one FFT on the complexity for a
  MS.
• Need to take into account the overall complexity
  (including channel estimation, synchronization
  ,, RF).
• Future work coding impact?
• .