1. Doppler Spread Estimation in Frequency Selective Rayleigh Channels for OFDM Systems Athanasios Doukas, Grigorios Kalivas University of Patras Department of Electrical & Computer Engineering Applied Electronics Laboratory

2. Doppler Spread Estimation 219/07/2006 Conclusions Simulation Results Doppler Spread Estimator Fading Channel and OFDM System Introduction Contents

3. Doppler Spread Estimation 319/07/2006 Introduction  Orthogonal Frequency Division Multiplexing (OFDM) has been widely applied in the last years for various wireless communication systems such as Digital Video Broadcasting (DVB) and wireless local area networks (WLANs) ensuing great success.  These systems however, should be capable of working efficiently in wide range of operating conditions, such as large range of mobile unit (MU) speeds, different carrier frequencies in licensed and un-licensed bands, various delay spreads, and wide dynamic signal to-noise ratio (SNR) ranges.  This way assessing the channel quality and its rate of change is of great importance in adapting the system parameters to continuously changing channel conditions.

4. Doppler Spread Estimation 419/07/2006 Necessity of Doppler Spread Estimation 1 It provides information about the fading rate of the channel. Knowledge of Doppler spread can improve detection and aid into transmission optimization in both physical layer and higher levels. 2 Doppler information can help in selection of appropriate transmission characteristics to combat ICI including proper channel estimators to enhance reception. 3 Specifically designed channel estimators can be applied and the rate of appliance can be chosen to improve throughput and an increase in the estimation rate can help to lower BER.

5. Doppler Spread Estimation 519/07/2006 Switching rate of diversity branches is used for the velocity estimation but its sensitivity to the fading channel is shown. Another type of estimators are the covariance-based estimators, which estimate the Doppler frequency from the auto- covariance of powers of the received signal envelope or from sums of the I/Q components. Other methods, highly associated to LCR, are the Zero Crossing Rate (ZCR), which uses the in-phase or quadrature phase (I/Q) signal part, and some other higher order crossings of the signal envelope. Previous Work 41 Doppler Estimation Level Crossing Rate (LCR) of the received signal envelope is proportional to the Doppler frequency and thus used in Doppler estimation. However, the fading nature of the wireless channel decreases the estimator’s accuracy in low Doppler values. 23

6. Doppler Spread Estimation 619/07/2006 Doppler Estimator Novelty Wide Sense Stationary (WSS) Channel with a few samples Novel Points Of Estimator Low Mobility Of Systems that divide the state of the system in two operational modes a) Moving b) Still

7. Doppler Spread Estimation 719/07/2006 Conclusions Simulation Results Doppler Spread Estimator Fading Channel and OFDM System Introduction Contents

8. Doppler Spread Estimation 819/07/2006 Wireless Fading Channel (1/4) Channel Impulse Response where γ ℓ (t)’s are wide-sense stationary (WSS) narrowband complex Gaussian processes, which are independent for different paths. Correlation Function r τ (Δt)

9. Doppler Spread Estimation 919/07/2006 Wireless Fading Channel (2/4) The frequency response of the time-varying radio channel at time t is

10. Doppler Spread Estimation 1019/07/2006 Wireless Fading Channel (3/4)  The correlation function of H(t,ƒ) can be separated into the multiplication of a time domain correlation r t (Δt) and a frequency domain correlation r ƒ (Δƒ).  r t (Δt) is dependent on the vehicle speed or, equivalently, the Doppler frequency, while r ƒ (Δƒ) depends on the multipath delay spread.  With the separation property, we are able to propose our Doppler estimator described in the next section.

11. Doppler Spread Estimation 1119/07/2006 Wireless Fading Channel (4/4) For an OFDM system with block length T ƒ and tone spacing (subchannel spacing) Δƒ, the correlation function for different blocks and tones can be written as where Jake’s Model Time Correlation Frequency Correlation

12. Doppler Spread Estimation 1219/07/2006 OFDM Physical Layer

13. Doppler Spread Estimation 1319/07/2006 Transmitted/Received Signal Transmitted Signal Received Signal

14. Doppler Spread Estimation 1419/07/2006 Conclusions Simulation Results Fading Channel and OFDM System Introduction Contents Doppler Spread Estimator

15. Doppler Spread Estimation 1519/07/2006 Equations Used Time Correlation Time Correlation using Received Data

16. Doppler Spread Estimation 1619/07/2006 Doppler Estimation Procedure Nr=2, ρ=0 Nr=2, ρ=1 Combination of previous results DopplerEstimation 1 23

17. Doppler Spread Estimation 1719/07/2006 1 Estimation Procedure Step 1/3

18. Doppler Spread Estimation 1819/07/2006 2 Estimation Procedure Step 2/3

19. Doppler Spread Estimation 1919/07/2006 3 Estimation Procedure Step 3/3 Doppler Estimation Formula

20. Doppler Spread Estimation 2019/07/2006 Conclusions Fading Channel and OFDM System Introduction Contents Doppler Spread Estimator Simulation Results

21. Doppler Spread Estimation 2119/07/2006 Simulation Results (1/4)

22. Doppler Spread Estimation 2219/07/2006 Simulation Results (2/4)

23. Doppler Spread Estimation 2319/07/2006 Simulation Results (3/4)

24. Doppler Spread Estimation 2419/07/2006 Simulation Results (4/4)

25. Doppler Spread Estimation 2519/07/2006 Simulation Results Fading Channel and OFDM System Introduction Contents Doppler Spread Estimator Conclusions

26. Doppler Spread Estimation 2619/07/2006  We have presented a Doppler estimator for low mobility OFDM systems in Frequency Selective Rayleigh Fading Channels, using only two OFDM symbols for the time correlation in wireless OFDM systems.  The estimator instead of trying to estimate the accurate value of the Doppler frequency divides the mobility into a still and a moving mode, which for the case of WLANs is the most important. We have examined its performance in wireless channels with different power delay profiles, including sparse channels.  The estimator, in most of the cases, manages to clearly distinguish the two modes of mobility, still or moving. Conclusions