Blind channel identification for sparse multipath channels

Insung Kang, Purdue University

Abstract

Blind identification of a digital wireless communication channel is an important issue of communication system design especially in a frequency selective multipath fading channel environment. The essential parameters to be identified include the multipath delays and gains, the number of multipath propagations, the frequency offset between the carrier frequency and the reference frequency of the receiver, and the sampling phase. The problem of blindly identifying the unknown parameters is separated into two parts: identifying the multipath channel parameters including the sampling phase and identifying the frequency offset. First I present a novel approach based on the mode estimation algorithm to efficiently estimate the multipath channel parameters under the assumption that the frequency offset is exactly known. Then I present a joint blind estimation algorithm of the frequency offset and the multipath channel parameters. These algorithms are particularly useful in sparse multipath channels. Conventional methods do not fully exploit inherent structure present in the combined channel response; the excess number of parameters to be estimated by conventional methods makes the identification difficult. By utilizing a priori knowledge of the transmission data pulse, parameters directly related to the multipath propagations are extracted, and hence the number of estimation parameters are significantly reduced. The channel identification problem is then posed in the standard modal analysis framework to enable the use of well-established high-resolution harmonic retrieval techniques. The mode parameters are unraveled to obtain the multipath channel parameters. Simulation results show significant improvement over existing approaches.

Degree

Ph.D.

Advisors

Gelfand, Purdue University.

Subject Area

Electrical engineering

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