Center for Satellite and Hybrid Communication Networks
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Authors Featured on this Page:

J.S. Baras

Y. Jiang

F.W. Sun

Recent Technical Reports Authored or Co-Authored by Dr. Yimin Jiang (Ph.D. 2000)

Papers resulting from CSHCN-related research are periodically added to the Institute for Systems Research Technical Report Database where they can be browsed by year or searched by author or keywords.


On the True Cramer-Rao Lower Bound for the DA Joint Estimation of Carrier Phase and Timing Offsets (CSHCN TR 2000-14) by Y. Jiang, F.W. Sun, John S. Baras

The Cramer-Rao lower bound (CRB) plays a pivotal role in
parameter estimation theory, such as timing, frequency and
phase synchronization. Therefore, it receives considerable
attention in the literature. This paper concerns the CRB for
data-aided (DA) timing and/or phase recovery, i.e. the
parameter synchronization is aided by a training sequence
known to the receiver.

For DA parameter synchronization, the CRB typically varies
with the training sequence. This indicates that different training
sequences offer fundamental different performance.
Therefore, it is very important to be able to compute the
CRB for any particular training sequence to understand the
fundamental limit that a particular training sequence has.
However, in the literature, the closed-form CRB for an
arbitrary training sequence is not available. In principle, it is
possible to use brute-force numerical approach to compute
CRB for any given training sequence. Such brute-force
computation involves evaluation of derivatives numerically
and matrix inversion. Besides the computational complexity,
brute-force approach does not provide any insight on the
interaction between training sequence and the resultant CRB.

In the literature, the widely cited close-form data-aided CRB for timing and phase recovering was derived under the assumption that the training sequence is independently identical distributed (i.i.d.) and the length of the training sequence is sufficiently long. We found that the CRB for a particular training sequence can be significantly lower than that with the long i.i.d. assumption. Therefore, the widely cited data-aided CRB actually does not give the fundamental limit for a particular training sequence.

In this manuscript, we derive a closed-form formula for data-aided CRB for timing and phase synchronization with respect to arbitrary training sequence. The bound illustrates the close relation between the training sequence and the fundamental limit on timing and phase synchronization. This bound provides additional insights on the sequence design.

2000 IEEE International Conference on Communications

Maximum Likelihood Slow Frequency-Selective Fading Channel Estimation Using Frequency Domain Approach (CSHCN TR 2000-13) by Y. Jiang, John S. Baras

This paper addresses the channel estimation problem for slow frequency-selective fading channel using training sequence and maximum likelihood (ML) approach.

Traditional works assumed symbol period spaced delay-tapped line model and additive white Gaussian noise (AWGN). Because of pre-filtering in the receiver front end, if the sampling rate is larger than one sample per symbol or sampling epoch is unknown (i.e., timing information is not available), AWGN model is not valid anymore.

A more general ML channel estimation method using discrete Fourier transform (DFT) is derived with the assumption of colored Gaussian noise and over sampling. Similar idea can be adopted to derive the ML joint timing and phase estimation algorithm.

Globecom 2000


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