1 / 26

Toward MIMO MC-CDMA

Toward MIMO MC-CDMA. Speaker : Pei-Yun Tsai Advisor : Tzi-Dar Chiueh 2004/10/25. Outline. Motivation MIMO MC-CDMA transmitter Allocation of system resource STBC+MC-CDMA V-BLAST+MC-CDMA MIMO MC-CDMA receiver Synchronization Channel estimation MIMO decoding Conclusion. Motivation.

Download Presentation

Toward MIMO MC-CDMA

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Toward MIMO MC-CDMA Speaker : Pei-Yun Tsai Advisor : Tzi-Dar Chiueh 2004/10/25

  2. Outline • Motivation • MIMO MC-CDMA transmitter • Allocation of system resource • STBC+MC-CDMA • V-BLAST+MC-CDMA • MIMO MC-CDMA receiver • Synchronization • Channel estimation • MIMO decoding • Conclusion

  3. Motivation • MC-CDMA • A promising solution for future wireless cellular communication systems. • MIMO • One technique to improve capacity and diversity gain. • MIMO MC-CDMA • To be investigated and evaluated as a trend. [1][2]

  4. Considerations in Transmitter

  5. Requirement for Channel Estimation(1/2) Antenna 0 Antenna 1 • For some subcarrier k, • Tx antenna 0, S0[n] • Tx antenna 1, S1[n] • At the Rx, S0[0] S1[0] S0[1] S1[1] H10 H00 H11 H01 Antenna 0 Antenna 1 R0[0] R1[0] R0[1] R1[1]

  6. Requirement for Channel Estimation(2/2) • MMSE Channel estimation [3] subject to S, known training symbols or pilot subcarriers, should be an unitary matrix to achieve minimum MSE.

  7. System Resources • Training symbol and pilot subcarriers 800 sub-carriers 800 sub-carriers 24 24 time 9 18 pilot subcarrier training symbol

  8. Pattern • Training symbol • Pilot subcarriers Antenna 0 Antenna 1 -1-j differentially encoded by one PN sequence 1+j -1-j 1+j Antenna 0 Antenna 1 1+j -1-j

  9. Problem • Channel estimation in mobile MIMO systems • Time-invariant requirement of channel response. • Impossible in fast-fading channel. • Decrease the supported highest mobility

  10. Pilot Pilot OFDM OFDM Insertion Insertion Modulation Modulation STBC + MC-CDMA User u Spreading User 0 Antenna 0 output Spreading Time i Training Symbol C0 Time i+1 Insertion Constellation STBC Mapping C0 Time i Antenna 1 output Spreading Time i+1 Training Symbol Insertion Alamouti ABBA form

  11. Pilot Pilot OFDM OFDM Insertion Insertion Modulation Modulation V-BLAST + MC-CDMA User u Spreading User 0 Antenna 0 output Spreading Time i Training Symbol C0 Time i+1 Insertion Constellation V-BLAST Mapping C0 Time i Antenna 1 output Spreading Time i+1 Training Symbol Insertion V-BLAST

  12. Considerations in Receiver

  13. Synchronization Tasks (1/2) • Coarse symbol boundary detection • Training symbol 0 still has two repetitions in the time domain. • Fractional CFO acquisition • Using training symbol 0 • Integer CFO acquisition • Using training symbol 1 • Equivalent channel response H00,k-H01,k • Fine symbol boundary detection • Using training symbol 0 • Equivalent channel response H00,k+H01,k Antenna 0 Antenna 1 Training symbol 0 Training symbol 1 Normal symbol 0 Normal symbol 1

  14. Synchronization Tasks (2/2) • Estimation for residual CFO and TFO • Using pilot subcarriers. • Using phase difference of consecutive symbols in the frequency domain. • Problem arises due to alternative pilot data transmitted by antenna 1. • Simple solution: using pilot data separated by 2 symbols Antenna 0 Antenna 1 Training symbol 0 Training symbol 1 Data symbol 0 Data symbol 1 Data symbol 2

  15. Channel Estimation (1/2) • Static channels • Matrix inverse • Linear interpolation • Channel estimates apply to the following normal symbols Antenna 0 Antenna 1 Training symbol 0 Training symbol 1

  16. Channel Estimation (2/2) • Dynamic channels • Two data symbols grouped together • Getting channel estimates in pilot subcarriers • Raised-Cosine frequency-domain channel interpolator Antenna 0 Antenna 1 Data symbol 0 Data symbol 1

  17. Channel Estimation Combining and Despreading - STBC (1/3) • STBC[1] De-Mapping Antenna 0 input STBC Decoding FFT Despreading MRC Algorithm MMSE Algorithm Antenna 1 input FFT EM-based Detection PIC Algorithm

  18. Combining and Despreading - STBC (2/3) • Received signal after DFT • b : Multi-users’ signal in two time slots (2LUx1) • C : Spreading matrix (NxLU) • H00, H01 : Channel complex gain (NxN) • MRC • Can’t reduce MAI • MMSE • Minimize the mean squared error per user data [1]

  19. Combining and Despreading - STBC (3/3) • EM (Expectation-Maximization)-based detection[4] • Arbitrary positive real scalar • E-step • M-step • PIC (Parallel-Interference Cancellation) detector • Iterative [1]

  20. Performance • Simulation parameters [1] • Carrier frequency : 2.56 GHz • Bandwidth : 5 MHz • N: 512 • U=32 (full loaded) • PIC and EM detection • Initial : MRC • Iteration 2 times.

  21. Channel Channel Estimation Estimation Combining and Despreading - V-BLAST (1/3) • V-BLAST[5] De-Mapping Antenna 0 input V-BLAST Decoding FFT Despreading ZF Algorithm MMSE Algorithm Antenna 1 input FFT IC-ZF Algorithm IC-MMSE Algorithm

  22. Combining and Despreading - V-BLAST (2/3) • Received signal after DFT • bu,k: data of the user u at the subcarrier k of two transmit antenna (2x1) • Hk : Channel complex gain (2x2) • rk : received signal at the subcarrier k (2x1) • ZF (Zero-Forcing) • Using channel estimates to solve the two linear equations. • MMSE • MMSE per subcarrier [5]

  23. Combining and Despreading - V-BLAST (3/3) • Interference cancellation (IC) – ZF algorithm • Initial : • Recursion : • IC-MMSE algorithm • Change the pseudo-inverse to MMSE coefficient Maximize SNR Nulling the column [5]

  24. Performance • Simulation parameters [5] • N: 64 • Spreading factor : 8 • U=4 (half-loaded) • Antenna diversity : 4x4 • Iterative detection before despreading suffers MAI and error propagation

  25. Conclusion • MIMO techniques incorporated into MC-CDMA systems are considered. • Transmitter modification includes • Pattern of training symbol and pilot subcarriers (done) • MIMO encoding block (done) • Receiver modification includes • Joint estimation of residual CFO and TFO (done) • MIMO decoding block • Performance of MIMO decoding in the MC-CDMA systems does not have the same trend as in the OFDM systems due to MAI.

  26. Reference [1] S. Iraji and J. Lilleberg, “ Interference cancellation for space-time block-coded MC-CDMA systems over multipath fading channels,” in Proceeding of IEEE VTC’03, pp.1104-1108. [2] V. Nangia and K. L. Baum, “Experimental broadband OFDM systems field results for OFDM and OFDM with frequency domain spreading,” in Proceeding of IEEE VTC’02, pp. 223-227. [3] D. Wang, G. Zhu and Z. Hu, “Optimal pilots in frequency domain for channel estimation in MIMO-OFDM systems in mobile wireless channesl”, in Proceeding of IEEE VTC’04 Spring. [4] M. Feder and E. Weinstein, “Parameter estimation of superimposed signals using the EM algorithm”, IEEE Trans. on Acoustics, Speech and Signal Processing, vol. 36, pp. 477-489, Apr. 1988. [5] Z. Lei, X. Peng and F. P. S. Chin, “V-BLAST receiver for downlink MC-CDMA systems,” in Proceeding of IEEE VTC’03, pp.866-870.

More Related