; CDMA presentation
Documents
Resources
Learning Center
Upload
Plans & pricing Sign in
Sign Out

CDMA presentation

VIEWS: 34 PAGES: 19

This is the seminar on the Match Filter Detectors Comparison in CDMA system.

More Info
  • pg 1
									                  Submitted By
               Mr. Amit V. Jaiswal
                    Guided By
                 Dr.S.M. Gulhane
{Lect. Dept. electronics and telecommunication engg.}



DEPT. OF ELECTRONICS & TELECOMMUNICATION
                                    ENGG.
   JAWAHARLAL DARDA INSTITUTE OF ENGG. &
                     TECHNOLOGY,YAVATMAL
                                2010-2011
Overview
   Introduction To CDMA
   Multiple Access Interference (MAI)
   The conventional detector
   MUD algorithms
      Linear
      Non-Linear
      Optimal MLSE
   MUD Detectors
      Decorrelating Detector
      Minimum Mean Squared Error (MMSE)
      Successive Interference Cancellation
         1) SIC
         2) PIC
   Detector Performance
   Limitations of MUD
   Conclusion
Introduction to CDMA.

   CDMA - code division multiple access is a widely used
    technique for multiple access communication in wireless
    systems

   The user data is separated on the basis of signature
    waveform assigned to each user. This waveform must be
    mutually orthogonal in order to eliminate interference among
    the user
Multiple Access Interference (MAI)
 This MAI is responsible for degradation in the performance of
    the system.


   MAI is a function of:
     Number of Users
     Cross-Correlation between users
     Amplitude of Interfering Signals


   Factors contributes to MAI
        - Imperfect cross-correlation characteristics of the spreading
    codes.
       - Multi-path fading contributes to MAI.
       - Non orthogonality in signature waveform.
         The conventional detector(SUMF)
   The conventional detector follows the single user detecton strategy in which
    each user is detected separately without regard of other user

   It is designed for the case of orthogonal spreading.




                                                     fig: The conventional detector
 The conventional detector(SUMF)
Advantage:
  1) Is simple to implement
  2) Does not require knowledge of the channel
     or the user amplitudes.

Disadvantage:
   1) Does not take MAI into account and hence
    gives non-zero probability of error even with
    zero noise.
   2) Suffers from the Near-Far Problem.
MUD in CDMA systems

   The primary idea of Multi User Detection (MUD)
    techniques is to cancel the interference caused by
    other users. This is done by exploiting the
    available side information of the interfering users,
    rather than ignoring the presence of other users
    like in (SUD) techniques.

   The idea of MUD was proposed by Sergio Verd´u
    in the early 1980’s.
MUD Algorithms
Linear Algorithms
   Linear mapping algorithms are applied to the
    outputs of the matched filters

   Less complexity than optimal MLSE receiver

   Practical Linear Algorithms:
    - Decorrelating Detector
    - Minimum-mean squared error (MMSE)
Decorrelating Detector
          Match filter o/p in form 0f Matrix Representation:
                   y = RAd + z

 y1
        Matrix
 y2     Filter


yk           R-1

                                                               The matrix R is of
                                                               the form:
      – where y=[y1,y2,…,yK]T, R and W are KxK
        matrices
      – Components of R are given by cross-
        correlations between signature waveforms
        sk(t)
      – A is diagonal with component Ak,k given by
        the channel gain ck of the kth user
      – z is a colored Gaussian noise vector
Decorrelating Detector
 •   Thus the output of detector is




 •   The matrix representation method is analogous to zero-forcing (ZF)
     equalizers for ISI channels

 •   Advantages:
      – Does not require knowledge of users’ powers.
      – Completely eliminates MAI hence near far resistant.
 •   Disadvantages:
      – Noise enhancement
Minimum Mean Squared Error
(MMSE) Detector
- The MMSE detector takes the background noise in to account and
    utilizes the knowledge of the received signal powers

-It minimizes the mean squared error between the actual data and
   the soft outputs of the conventional detectors




      Thus, the soft estimate of the MMSE detector is simply



   Advantage: Better error probability performance, and no noise enhancement

  Disadvantage: Requires estimation of received amplitudes, and matrix inversion
Successive Interference Cancellers
   The SIC detectors start to subtract off
    the strongest remaining signals in a
    successive fashion from the rest of the
    signals .


   The other similar alternative is the PIC
    method. This starts to simultaneously
    subtract off all of the users’ signals
    from all of the others unlike the serial
    cancellation that starts with the
    strongest signal user .
     It works better than SIC when all of the
       users are received with equal strength
       since it is much easier to detect them
       and hence decreases the probability of
       error
Successive Interference Cancellers
- SIC
 Interference Cancellers
- PIC
Successive Interference Cancellers
           SIC                                 VS.              PIC
  The main disadvantages are:
  1) If the strongest estimate is not highly         1)   More vulnerable to near-far
  reliable it results on performance                      issues
  degradation                                        2)   Complicated circuitry
  2) As the power profile changes the
  signals must be reordered
  3) Every stage introduces a delay


  The main advantages are:
  1) The weakest user will see a                     1) Because of the parallel
        tremendous signal gain from the              nature no delays/stage
        MAI reduction since all of the               required!
        interfering channel will add up as           2) Simpler than other linear
        signals to the weakest user.                 detectors
        Hence every user is on a win-win
        situation.
  2) For severe conditions if we remove
        the strongest user the rest of
        weaker users will benefit hence
        the signal can be recovered
  3) Can recover from near-far effects
Limitations of MUD
 Limitations with implementation
     •Sensitivity and robustness
     •Processing delay
     •Processing complexity

 Limitations of MUD
     •Cost must be kept low in order to increase performance/cost
     tradeoff
     •Capacity improvements only in the uplink would be partly used in
     determining the overall system capacity
          - Need to use MUD in both uplink and downlink
          - Implementing MUD in mobiles is still a challenge
Conclusions
   MUD has many advantages over other communications techniques
    however they are limited by the complexity of their implementations and
    a simple implementation is needed. As the DSP field progresses further
    and more calculations can be performed with ease more of these
    advantages will be implemented in future work.

   Current investigations involve implementation and robustness issues

   MUD research is still in a phase that would not justify to make it a
    mandatory feature for 3G WCDMA standards

   Currently other techniques such as smart antenna seem to be more
    promising
References
   R. Lupas, S. Verdu, "Linear multi-user detectors for synchronous code-division multiple-access
    channels," IEEE Trans. Information Theory, vol. 35, no. 1, pp. 123-136, Jan. 1989.
   R. Lupas, S. Verdu, "Near-far resistance of multi-user detectors in asynchronous channels," IEEE
    Trans. Comm. Vol. 38, no. 4, pp. 496-508, April 1990.
   X. Wang, H. V. Poor, "Blind multi-user detection: a subspace approach," IEEE Transactions on
    Information Theory, vol. 44, no. 2, pp. 677-690, March 1998.
   http://wsl.stanford.edu/~ee360/mud_peter.ppt#4
   H. V. Poor, S. Verdu, "Single-user detectors for multi-user channels," IEEE Trans. Comm. Vol. 36,
    no. 1, pp. 50-60, Jan. 1988.
   Duel-Hallen, J. Holtzman, Z. Zvonar, "Multi-user detection for CDMA Systems," IEEE Personal
    Communications, pp. 46-58, April 1995. [Review]
   Yi Wang, Zhimin Du, Lu Gao and Weiling Wu, “Performance Analysis of MMSE Multiuser Detection”,
    Beijing University of Posts and Telecommunications
   Shimon Moshavi, “Multi-User Detection for DS-CDMA Communications”, Bellcore

								
To top
;