Symbol timing estimation SISO systems

Research Problem:

    Symbol timing estimation in single carrier systems (linear and nonlinear modulations, SISO and MIMO)

Description:

   Traditionally, feedback loops are used to control the receiver clock to sample the signal at the optimal instants such that no ISI is introduced by the pulse shaping filter. However, in burst mode transmissions, feedforward schemes are more suitable since feedback loops may take a long time to converge. In feedforward schemes, the received signal is in general over-sampled (more than one sample per symbol) with a fixed clock. Then, a symbol timing estimator is used to estimate the timing offset of these unsynchronized samples. Finally, the signal samples at the optimum sampling instants are calculated from the unsynchronized samples using a fractional delay filter (e.g., the Farrow structure). In this study, I concentrated on the timing offset estimation part and its implementation issues. Specifically, for binary CPM, a new symbol timing estimator was proposed based on the Laurent’s expansion and the well-known square nonlinearity estimator. For linear modulations, a new symbol timing estimator based on the conditional maximum likelihood principle was proposed and its performance thoroughly analyzed both analytically and via Monte-Carlo simulations

    We also address the symbol timing estimation problem in MIMO systems, where signals from different antennas are superimposed together, and the symbol timing estimation algorithms commonly proposed for SISO systems do not work well in MIMO systems. In particular, we answered the following questions:

How to estimate the timing delay in MIMO system for the case i) when the transmitted data is assumed to be known, ii) if the data is unknown?
§How to design the optimal training sequences in data-aided case so that we can get the best estimation performances?
§What is the effect of increasing the number of transmit or receive antenna on the performances of estimators?
§How is the correlation between antenna affect the structure of estimators and the performances?
§How is the performances of the estimators compared to the theoretical performance bounds?

Representative Publications:

Yik-Chung Wu, S. C. Chan and E. Serpedin, ``Symbol-Timing Estimation in Space-Time Coding Systems based on Orthogonal Training Sequences," IEEE Trans. on Wireless Communications, vol. 4, no. 2, pp. 603-613, Mar. 2005. [PDF]
Yik-Chung Wu and E. Serpedin, ``Symbol Timing Estimation in MIMO Correlated Flat-Fading Channels," Wireless Communications and Mobile Computing (WCMC) Journal , Special Issue on "Multiple-Input Multiple-Output (MIMO) Communications", Wiley, vol. 4, Issue 7, pp. 773-790, Nov. 2004. [PDF]
Yik-Chung Wu and E. Serpedin, ``Unified analysis of a class of blind feedforward symbol timing estimators employing second-order statistics,'' IEEE Trans. on Wireless Communications, vol. 5, no. 4, pp.737-742, Apr. 2006. [PDF]
Yik-Chung Wu and E. Serpedin, ``Design and Analysis of Feedforward Symbol Timing Estimators Based on the Conditional Maximum Likelihood Principle," IEEE Trans. on Signal Processing, vol. 53, no. 5, pp. 1908-1918, May 2005. [PDF]
Yik-Chung Wu and E. Serpedin, ``Low-complexity feedforward symbol timing estimator using Conditional Maximum Likelihood principle," IEEE Communications Letters, vol. 8, no. 3, pp.168-170, Mar. 2004. [PDF]
Yik-Chung Wu and Tung-Sang Ng, “Symbol Timing Recovery for GMSK Modulation Based on Squaring Algorithm,” IEEE Communications Letters, vol. 5, no. 5, pp.221-223, May 2001. [PDF]