1. 1 Data-carrier Aided Frequency Offset Estimation for OFDM Systems

2. 2 Outline Motivations Background knowledge Conventional CFO estimation strategies Modified CFO estimation strategies Simulation results Conclusions

3. 3 Outline Motivations Background knowledge Conventional CFO estimation strategies Modified CFO estimation strategies Simulation results Conclusions

4. 4 Motivations  The conventional carrier frequency offset estimation methods: pilot, cyclic prefix, training symbol  Our proposed schemes: adopting the received signal on data-carriers  Providing more accurate frequency synchronization, or reducing the pilot numbers to raise transmitted data rate.

5. 5 Outline Motivations Background knowledge Conventional CFO estimation strategies Modified CFO estimation strategies Simulation results Conclusions

6. 6 Carrier Frequency Offset What result in carrier frequency offset (CFO)?  Mismatch between the oscillators at the TX and RX  Doppler frequency Carrier frequency offset can be divided into:  Integral part  Fractional part

7. 7 OFDM System Model  C is pilot sequence  h is time domain channel impulse response  w is additive white Gaussian noise.  N data information {S(n)} which have been modulated with N modulation values {X(n)} on every sub-carrier x ( t ) Channel h ( t) S ( n ) r (t ) S/P P/S X ( n ) x ( k ) Adding Pilots C(n) & IFFT Adding Cyclic Prefix & P/S DAC Signal Mapper z (t ) FFT Remove Cyclic Prefix & S/P ADC Signal Demapper AWGN w ( t)  The OFDM system model:

8. 8 OFDM System Model  The k sample of an OFDM block generated by IFFT : N: number of subcarriers Ng: length of cyclic prefix

9. 9 UWB Channel Model  Four environments in this UWB channel model:  CM1 model is based on LOS (0-4m) channel measurements in [2]  CM2 model is based on NLOS (0-4m) channel measurements in [2]  CM3 model is based on NLOS (4-10m) channel measurements in [2], and NLOS in [3]  CM4 the model generated to fit a 25nsec RMS delay spread. Time Signal strength : cluster decay factor : path decay factor : cluster arrival rate : the arrival rate of path within each cluster

10. 10 Outline Motivations Background knowledge Conventional CFO estimation strategies Modified CFO estimation strategies Simulation results Conclusions

11. 11 Sensitivity for Carrier Frequency Offset  The OFDM system model with CFO: x ( t ) Channel h ( t) S ( n ) S/P X ( n ) x ( k ) Adding Pilots C(n)& IFFT Adding Cyclic Prefix & P/S DAC Signal Mapper z (t ) r (t ) P/S FFT Remove Cyclic Prefix & S/P ADC Signal Demapper AWGN w ( t)  is the ratio of the actual frquency offset to the sub-carrier spacing

12. 12 Sensitivity for Carrier Frequency Offset  The k-th received sample of the m-th symbol is given by FFT

13. 13 Pilot tone - aided CFO Estimation  PTA CFO estimation: R1R1 R2R2 Pilot1 (n 1 ) Pilot2 (n 2 ) Pilot3 (n 3 ) f t RmRm R m+D  Let P denote the set of indexes of the Np pilot carriers I Q

14. 14 Pilot tone - aided CFO Estimation  PTA with weighting (PTAW) CFO estimation: f  Let P denote the set of indexes of the Np pilot carriers I Q R1R1 R2R2 Pilot1 (n 1 ) Pilot2 (n 2 ) Pilot3 (n 3 ) t RmRm R m+D

15. 15 CP (N g ) Symbol 1 Symbol 2 (N+N g ) (CL-1 ) (L) Cyclic Prefix - based CFO Estimation  CL is the channel length

16. 16 Outline Motivations Background knowledge Conventional CFO estimation strategies Modified CFO estimation strategies Simulation results Conclusions

17. 17 Modified PTAW R1R1 R2R2 t RmRm R m+D f Step1 :

18. 18 Modified PTAW Step2 : f R1R1 R2R2 Pilot1 (n 1 ) Pilot2 (n 2 ) Pilot3 (n 3 ) t RmRm R m+D

19. 19 Modified PTAW Step4 : Step3 : Each data-subcarrier d(n) has M candicates,i=1…M

20. 20 Modified CPB Step2 :Step1 :

21. 21 Modified CPB Step4 : Step3 : Each data-subcarrier d(n) has M candicates,i=1…M

22. 22 Outline Motivations Background knowledge Conventional CFO estimation strategies Modified CFO estimation strategies Simulation results Conclusions

23. 23 Optimum L for CPB Method CM1

24. 24 Optimum L for CPB Method CM3

25. 25 Discussion of Pilot Numbers CM1

26. 26 Discussion of Pilot Numbers CM3

27. 27 Performance Comparison CM1 BPSK

28. 28 Performance Comparison CM1 QPSK

29. 29 Performance Comparison CM1 8PSK

30. 30 Performance Comparison CM3 BPSK

31. 31 Performance Comparison CM3 QPSK

32. 32 Performance Comparison CM3 8PSK

33. 33 Outline Motivations Background knowledge Conventional CFO estimation strategies Modified CFO estimation strategies Simulation results Conclusions

34. 34 Conclusions  Advantages:  The key advantages of our proposed algorithms is to provide more accurate frequency synchronization and reduce pilot numbers to raise bandwidth efficiency.  Comparison with conventional methods:  The MCPB performs better than CPB (lower MSE).  The MPTAW performs better than two traditional pilot tone- aided methods, and we can achieve the same performance as PTAW by less pilot numbers.  The best choices:  If there is acceptable ISI, the MCPB will be the most suitable method to estimate CFO because it can provide excellent MSE with its superior resistance of ICI and constellation size.  If there is serious ISI, the MPTAW is the best choice under this condition since it is robust to time domain interference.

35. 35 Thank you ~

36. 36 Reference [1] J. R. Foerster, Ed., “Channel Modeling Sub-committee Report Final,” IEEE P802.15 SG3a contribution. [2] H. Chen and G.J. Pottie, "A Comparison of Frequency Offset Tracking Algorithms for OFDM", GLOBECOM '03, vol.2, pp. 1069-1073, Dec. 2003. [3] K. Shi, E. Serpedin, and P. Ciblat, “Decision-directed fine synchronization for coded OFDM systems,” in Proc. IEEE International Conf. on Acoustics, Speech, and Signal Processing. (ICASSP’04), vol. 4, pp. 365-368, 17-21 May 2004.