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

MC-CDMA vs DS-CDMA M. des Noes and D. Ktenas (presented by Sylvie Mayrargue). Outline. Context of the comparison : Simulation assumptions Asymptotic analysis DS and MC-CDMA system models. For each detector : Linear filter description Simulation results Interpretation

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

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

  2. 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

  3. 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).

  4. Asymptotic analysis 1/3 • 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.

  5. Asymptotic analysis 2/3 • 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

  6. Asymptotic analysis 3/3 AWGN transmission ! Fixed Gaussian noise Signal to Interference plus Noise Ratio (SINR) :

  7. 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, n°5, 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/~loubaton/index.html

  8. d1(n) N c1(z) v[n] X[n] h(z) Y[n] dK(n) N cK(z) DS-CDMA system model 1/2 • 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 (W< N)

  9. DS-CDMA system model 2/2 Received signal : Useful + MAI Noise N(0,2I) ISI+MAI

  10. IFFT N: N x1(n) d1(n) s1 P/S S/P Spreading GI Insertion z[i] xN(n) 1: N sN N:1 dK(n) MC CDMA System model 1/2

  11. MC CDMA System model 2/2 Received signal : Tap delay channel : where is the channel impulse response.

  12. DS-CDMA MC-CDMA MRC: Maximum Ratio Combining

  13. MRC: Simulation vs. Asymptotic DS-CDMA

  14. MRC: Simulation vs. Asymptotic MC-CDMA

  15. MRC: Comparison MC-CDMA DS-CDMA

  16. SU-MMSE DS-CDMA MC-CDMA

  17. SU-MMSE : simulation vs asymptotic – MC CDMA

  18. SU-MMSE : Comparison DS-CDMA – MC CDMA

  19. 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

  20. MU-MMSE Multiple User MMSE (for MC-CDMA) Asymptotic SINR

  21. MU-MMSE : simulation vs asymptotic – DS CDMA

  22. MU-MMSE : DS-CDMA – MC CDMA

  23. 2(N,K)- 1(N,K)2 0 N,K Interpretation 1(N,K) DS-CDMA 2(N,K) DS-CDMA with Cyclic Prefix Both systems have the same asymptotic SINR

  24. 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.

  25. 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? • .

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