Students: AMPLIATO, Miguel BEAURIN, Bastien GUILLEMIN, Matthieu POVEDA, Hector SOULIER, Bruno Supervisor: GROLLEAU, Julie GRIVEL, Eric Project S5: OFDMA Synch. Techniques

0) Introduction Context Mobile Telephony (EU) OFDMA I) Working Principles Prefix Cyclic Frequency Synchronisation Experimental Work II) Frequency offset estimation Maximum Likelihood (ML) Linear Least Squares (LS) Extended Kalman Filter (EKF) III) Conclusion & Further Work 1/17

OFDMA Synch. Techniques 0) Introduction Context Mobile Telephony (EU) OFDMA I) Working Principles Prefix Cyclic Frequency Synchronisation Experimental Work II) Frequency offset estimation Maximum Likelihood (ML) Least Squares (LS) Extended Kalman Filter (EKF) III) Conclusion & Further Work 1/17

Introduction OFDMA Synch. Techniques AIMS:  High-speed data transmission in mobile communications with multiple users 2/17

Introduction: Context OFDMA Synch. Techniques 3/17 Original Signal Restrictions: Multipath Signal Fading Doopler effect Desynchronisation

Introduction: Mobile Telephony (EU) OFDMA Synch. Techniques 1G - Analogue Technology [1981]: FDMA 2G - Digital Technology [1991]: TDMA 3G - Digital Technology [2001]: W-CDMA 4/17

Introduction: OFDMA OFDMA Synch. Techniques Orthogonal Frequency Division Multiplexing: /T 1/T T is the Symbol time Property that keep a secure distance Orthogonality 5/17 Orthogonal Frequency Division Multiplexing Frequency Division Multiplexing Access Orthogonal Frequency Division Multiple Access Orthogonal Frequency Division Multiple Access:

OFDMA Synch. Techniques Introduction: OFDMA (II) 6/22

OFDMA Synch. Techniques Introduction: OFDMA (III) Advantages: Disadvantages Sub-carriers attenuated  Frequency Selectivity Fading = Frequency Offset 7/17 Synchronisation:

OFDMA Synch. Techniques 0) Introduction Context Mobile Telephony (EU) OFDMA I) Working Principles Prefix Cyclic Frequency Synchronisation Experimental Work II) Frequency offset estimation Maximum Likelihood (ML) Least Squares (LS) Extended Kalman Filter (EKF) III) Conclusion & Further Work

 Why a cyclic prefixe is used? OFDMA Synch. Techniques Without timing offset With timing offset, IBI avoided 8/17

 The canal has 2 effects: ◦ Time offset ◦ Frequency offset  The frequency synchronisation has been performed for downlink transmission using: ◦ Maximum of Likelihood ◦ Linear Least Square ◦ Extended Kalman Filter OFDMA Synch. Techniques 9/17

OFDMA Synch. Techniques Y(1) Y(2) Y(3) Y(4) Y(5)… …Y(N) Frequency offset + Noise w ML and Linear LS estimation methods -> 2 identical symbol blocks transmitted r(1) r(2) r(3) r(4) r(5)… …r(N) 10/17

OFDMA Synch. Techniques 0) Introduction Context Mobile Telephony (EU) OFDMA I) Working Principles Prefix Cyclic Frequency Synchronisation Experimental Work II) Frequency offset estimation Maximum Likelihood (ML) Linear Least Squares (LS) Extended Kalman Filter (EKF) III) Conclusion & Further Work

r= yH(ℇ)+w AWGN w=r-yH(ℇ) white gaussian noise ML maxp w (r/ℇ) OFDMA Synch. Techniques * Based on Mr. Moose paper 11/17

OFDMA Synch. Techniques Criteria Definition AWGN Solution 12/17

2 identical and successive Frames constant linearisation nonlinearity Taylor Series OFDMA Synch. Techniques Mean Squared Error MSE 13/17

 Carrier Frequency Offset (CFO) estimation :  Criteria : Minimum Mean Squared Error,  Hypothesis on state equation :  is constant   n  n-1   Non linear measurement equation  Extended Kalman Filter (EKF)  We linearize around   Advantage  1 data block (length : 32 bits) used for CFO estimation. Mean Squared Error MSE * Based on Mr. P.Zaho, Mr. L.Kuang and J.Lu paper 14/17

OFDMA Synch. Techniques 0) Introduction Context Mobile Telephony (EU) OFDMA I) Working Principles Prefix Cyclic Frequency Synchronisation Experimental Work II) Frequency offset estimation Maximum Likelihood (ML) Least Squares (LS) Extended Kalman Filter (EKF) III) Conclusion & Further Work

 Achievements : Downlink Synchronization ◦ Carrier Frequency Offset :  Maximum likelihood (ML) method,  Least Squares (LS),  Extended Kalman Filter (EKF).  Results :  ML & LS estimation methods : 2 data blocks required,  EKF : only 1 data block needed.  lower performance in terms of MSE.  We are currently working on this method to remedy this issue 15/17

 Channel modelling  Timing offset estimation  LMS filter  RLS filter  EKF improvement  Model on    higher  MSE expected.  Implement the complete transmission chain :  Receiver 16/17

Project S5: OFDMA Synch. Techniques Any question ? 17/17