@conference {
	title = {Maximum Likelihood Slow Frequency-Selective Fading Channel Estimation Using Frequency Domain approach},
	author = {Jiang, Yimin., Sun, Feng-Wen., Baras, John S.},
	year = {2000},
	month = {11/2000},
	abstract = {This paper addresses the channel estimation problem for slow frequency-selective fading channels using training sequences and the maximum likelihood (ML) approach. In the literature people usually assume a symbol period spaced delay-tapped-line model and additive white Gaussian noise (AWGN). Due to the pre-filtering in the receiver front end, if the sampling rate is larger than one sample per symbol or sampling epoch is unknown (Le., the timing information is unavailable), the AWGN model is not valid anymore. A more general ML channel estimation method using the discrete Fourier transform (DFT) is derived for colored Gaussian noise and over-sampling. A similar idea can be adopted to derive the ML joint carrier phase and timing offsets estimation algorithm.},
	address = {San Francisco, CA},
	booktitle = {IEEE Globecom2000, Communications:The Global Bridge},
	pages = {pp. 955-959}
}
@conference {
	title = {On the True Cramer-Rao lower Bound for Data{\textendash}Aided Joint Estimation of Carrier phase and Timing Offsets},
	author = {Jiang, Yimin., Sun, Feng-Wen., Baras, John S.},
	year = {2000},
	month = {06/2000},
	abstract = {This paper concerns the Cramer-Rao lower bound (CRB) for the data-aided (DA) timing and/or phase recovery, i.e., the synchronization parameter acquisition is aided by a training sequence known to the receiver. For the DA parameter estimation, the CRB typically varies with the training sequence. This indicates that different training sequences offer fundamental different performance. In this manuscript, we derive a closed-form formula of the CRB for timing and phase recovery with respect to any particular training sequence. The bound illustrates the close relation between the training sequence and the fundamental limit on timing and phase synchronization. It provides additional insights on the training sequence design.},
	address = {New Orleans},
	booktitle = {IEEE International Conference on Communication (ICC\&rsquo;00)}
}
