Presentation is loading. Please wait.

Presentation is loading. Please wait.

Channel Estimation in OFDM Systems Zhibin Wu Yan Liu Xiangpeng Jing.

Similar presentations


Presentation on theme: "Channel Estimation in OFDM Systems Zhibin Wu Yan Liu Xiangpeng Jing."— Presentation transcript:

1 Channel Estimation in OFDM Systems Zhibin Wu Yan Liu Xiangpeng Jing

2 OUTLINE  OFDM System Introduction  Channel Estimation Techniques  Performance Evaluation  Conclusion

3 OFDM Overview  Divides high-speed serial information signal into multiple lower-speed sub-signals: Transmits simultaneously at different frequencies in parallel.  Modulation ( BPSK, PSK,QPSK,16QAM, …).  Pilot sub-carriers used to prevent frequency and phase shift errors.  Usage of cyclic prefix for lower multi-path distortion  Controlled overlapping of bands in one channel  Max spectral efficiency (Nyquist rate)  Easy implementation using inverse FFTs  Easy time-freq. Synchronization  Modulate by switching between time and frequency domain

4 Introduction to OFDM Systems

5 Time-Frequency View

6 Some Assumptions  Usage of cyclic Prefix  Impulse response of the channel shorter than Cyclic Prefix  Slow fading effects so that the channel is time-invariant over the symbol interval  Rectangular Windowing of the transmitted pulses  Perfect Synchronization of transmitter and receiver  Additive, white, Gaussian channel noise

7 System Architecture

8 System Architecture (cont’d) 1. Input to time domain 2. Guard Interval 3. Channel 4. Guard Removal 5. Output to frequency domain 6. Output 7. Channel Estimation ICIAWGNChannel Estimated Channel

9 Pilot for Channel Estimation Time Carriers Time Carriers  Comb Type: Part of the sub- carriers are always reserved as pilot for each symbol  Block Type: All sub-carriers is used as pilot in a specific period

10 Block-type Channel Estimation  LS: Least Square Estimation

11 Comb-type Estimation N p pilot signals uniformly inserted in X(k) L=Number of Carriers/N p x p (m) is the m th pilot carrier value {Hp(k) k=0,1,…,Np}, channel at pilot sub-carriers Xp input at the kth pilot sub-carrier Yp output at the kth pilot sub-carrier LS EstimateLMS Estimate Xp(k) LMS + e(k)- Yp(k)

12 Interpolation for Comb-type  Linear Interpolation  Second Order Interpolation

13 Simulation Parameters ParameterSpecifications FFT Size64 Number of Carriers64 Pilot Ratio1/16 Guard Length16 Guard TypeCyclic Extension data rate of OFDM signal1Mbps/sub-carrier Signal Constellation16QAM

14 System structure in MATLAB Simulation

15 OFDM Transmitter OFDM Receiver

16 Received and Recovered Signals Received signal phases are distorted by multi-path fading

17 Comb-LS Estimation  Combating multipath rayleigh fading with RLS adaptive equalization  A detail simulation with MATLAB  20 multipath, random phase, and weibull distribution of amplitutde Symbol Error Rate

18 Comb-LS Estimation

19 Filter length.vs. Sample Rate 1.Keep the ratio of F/S, increase S 2.Keep S, increase F. Observed Symbol error rate with F ( filter length ) and S ( samples per symbol)

20 Conclusion  OFDM System Introduction  Block Type Direct or Decision Feedback  Comb Type LS or LMS estimation at pilot frequencies  Interpolation Techniques Linear Second Order Time Domain  Modulation BPSK,QPSK,16QAM,DQPSK  Some Results: Comb Type performs better since it tracks fast fading channels. RLS algorithm vs. LMS algorithm


Download ppt "Channel Estimation in OFDM Systems Zhibin Wu Yan Liu Xiangpeng Jing."

Similar presentations


Ads by Google