1. APRIL 2002, PARISIPCN02 M. Ergen A Survey on Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems by Mustafa Ergen Authors: Sinem Coleri, Mustafa Ergen {csinem,ergen}@eecs.berkeley.edu Berkeley Web Over Wireless Group University of California Berkeley

2. APRIL 2002, PARISIPCN02 M. Ergen Outline Motivation for OFDM OFDM System Architecture Channel Estimation Techniques Performance Analysis Conclusion

3. APRIL 2002, PARISIPCN02 M. Ergen Motivation for OFDM Disadvantages of FDMA –Bad Spectrum Usage Disadvantages of TDMA –Multipath Delay spread problem

4. APRIL 2002, PARISIPCN02 M. Ergen OFDM: Use of Frequency Spectrum Efficient use of spectrum –Overlap in frequency spectrum of subcarriers Null point of all other subcarriers at the center frequency of any particular subcarrier Frequency spectrum of the subcarriers

5. APRIL 2002, PARISIPCN02 M. Ergen Multipath Delay Spread Multi-path delay spread definition –Time spread between the arrival of the first and last multipath signal, seen by the receiver. Received radio signal consisting of a direct signal, plus reflections from objects Multi-path delay spread effect –Inter-Symbol Interference (ISI) when the delayed multipath signal overlaps with the symbols following it

6. APRIL 2002, PARISIPCN02 M. Ergen OFDM: Eliminating ISI Cyclic Prefix –Prepend the last part of the signal to the beginning of the signal Duration of the CP larger than multipath delay spread Orthogonality of the carriers not affected.

7. APRIL 2002, PARISIPCN02 M. Ergen 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 subcarriers used to prevent frequency and phase shift errors.

8. APRIL 2002, PARISIPCN02 M. Ergen Benefits of OFDM Higher data rates –Overlap of subcarriers Lower bandwidth than spread spectrum. –High spectral efficiency Lower multi-path distortion –Usage of cyclic prefix

9. APRIL 2002, PARISIPCN02 M. Ergen Our OFDM System 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

10. APRIL 2002, PARISIPCN02 M. Ergen System Architecture-1

11. APRIL 2002, PARISIPCN02 M. Ergen 1 76 54 32 System Architecture-2 Input to Time Domain Guard IntervalChannel Guard RemovalOutput to Frequency Domain OutputChannel EstimationICIAWGNChannelEstimated Channel

12. APRIL 2002, PARISIPCN02 M. Ergen Pilot Arrangement Block Type – All sub-carriers reserved for pilots wit a specific period Comb Type –Some sub-carriers are reserved for pilots for each symbol

13. APRIL 2002, PARISIPCN02 M. Ergen Channel Estimation @Block-Type LS estimateMMSE estimate

14. APRIL 2002, PARISIPCN02 M. Ergen Channel Estimation @ Block-Type Block TypeDecision Feedback Interpolation H e -k th sub-carrier Channel Response Estimated X e (k) -> signal demapper -> signal mapper -> X pure (k) Use same channel estimation for the whole symbol duration

15. APRIL 2002, PARISIPCN02 M. Ergen Channel Estimation @ Comb-Type Pilot N p pilot signals uniformly inserted in X(k) L=Number of Carriers/N p {H p (k) k=0,1,…,N p }, channel at pilot sub-carriers X p input at the k th pilot sub-carrier Y p output at the k th pilot sub-carrier LMS EstimateLS Estimate

16. APRIL 2002, PARISIPCN02 M. Ergen Interpolation @ Comb-Type Linear Interpolation Second Order Interpolation Low pass Interpolation Spline Cubic Interpolation Time Domain Interpolation

17. APRIL 2002, PARISIPCN02 M. Ergen Linear InterpolationSecond Order Interpolation Low Pass Interpolation (interp in MATLAB) Interpolation @ Comb-Type Time Domain Interpolation Spline Cubic Interpolation (spline in MATLAB) Insert zeros into the original sequence Low-pass filter while passing original data unchanged Interpolation such that mean-square error between ideal and interpolated values min.

18. APRIL 2002, PARISIPCN02 M. Ergen OFDM Setup ParameterSpecifications FFT Size1024 Number of Carriers128 Pilot Ratio1/8 Guard Length256 Guard TypeCyclic Extension Sample rate of OFDM signal 44.1kHz Bandwidth17.5kHz Signal ConstellationBPSK, QPSK, DQPSK, 16QAM

19. APRIL 2002, PARISIPCN02 M. Ergen Channels Delay (OFDM samples)GainPhase(rad) 00.2478-2.5649 10.1287-2.1208 30.30880.3548 40.42520.4187 50.492.7201 70.0365-1.4375 80.11971.1302 120.1948-0.8092 170.4187-0.1545 240.317-2.2159 290.20552.8372 490.18462.8641 DelayAmplitude 01 20.3162 170.1995 360.1296 750.1 1370.1 Channel 1 Channel 2 Time Varying Channel (AR Model) ATTC (Advanced Television Technology Center) and the Grande Alliance DTV laboratory`s ensemble E model Simplified version of (Digital Video Broadcasting) DVB-T channel model

20. APRIL 2002, PARISIPCN02 M. Ergen Simulation-1 ModulationBPSK ChannelRayleigh Fading H(n)Channel 1 Doppler Frequency 70Hz

21. APRIL 2002, PARISIPCN02 M. Ergen ModulationQPSK ChannelRayleigh Fading H(n)Channel 1 Doppler Frequency 70Hz Simulation-2

22. APRIL 2002, PARISIPCN02 M. Ergen Modulation16QAM ChannelRayleigh Fading H(n)Channel 1 Doppler Frequency 70Hz Simulation-3

23. APRIL 2002, PARISIPCN02 M. Ergen ModulationDQPSK ChannelRayleigh Fading H(n)Channel 1 Doppler Frequency 70Hz Simulation-4

24. APRIL 2002, PARISIPCN02 M. Ergen Simulation-5 Modulation16QAM ChannelAR Fading H(n)Channel 1 Doppler Frequency 70Hz

25. APRIL 2002, PARISIPCN02 M. Ergen Modulation16QAM ChannelRayleigh Fading H(n)Channel 2 Doppler Frequency 70Hz Simulation-6

26. APRIL 2002, PARISIPCN02 M. Ergen Modulation16QAM ChannelRayleigh Fading H(n)Channel 1 SNR40dB Simulation-7

27. APRIL 2002, PARISIPCN02 M. Ergen Conclusion OFDM System Block Type Direct or Decision Feedback Comb Type LS or LMS estimation at pilot frequencies Interpolation Techniques Linear Second Order Low Pass Spline Time Domain Modulation BPSK,QPSK,16QAM,DQPSK Results: Comb Type performs better since it tracks fast fading channels. Low-pass interpolation performs better since mean square error between the interpolated points and their ideal values is minimized.