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Fast Computation of ChannelEstimate Based Equalizers in Packet Data Transmission

Summary: Fast Computation of Channel­Estimate Based Equalizers in
Packet Data Transmission
Naofal M. W. Al­Dhahir \Lambda , Member, IEEE, and John M. Cioffi, Senior Member, IEEE
Information Systems Laboratory
Stanford University, Stanford CA 94305 y
Computationally--efficient procedures are introduced for the real--time calculation of Finite Impulse
Response (FIR) equalizers for packet--based data transmission applications, such as wireless data net­
works. In such packet data applications, the FIR equalizer filters are computed indirectly, by first
estimating the channel pulse response from a known training pattern embedded in each packet, and
then computing the equalizer for use in the recovery of the remaining unknown data in the packet. We
find that a minimum mean--square--error decision feedback equalizer (MMSE--DFE) with a finite--length
constraint on its feedforward and feedback filters can be very efficiently computed from this pulse re­
sponse. We combine a recent theory of finite--spectral factorization for the MMSE--DFE with the theory
of structured matrices to derive these efficient procedures for computing the equalizer settings. The
introduced method is much more computationally efficient than direct computation by matrix inversion
or than the use of popular gradient or least--squares algorithms over the duration of the packet.
1 Introduction
In an increasing number of data transmission applications, including many of the new wireless data trans­
mission networks [1, 2], data is organized, transmitted, and received in finite--length packets.


Source: Al-Dhahir, Naofal - Department of Electrical Engineering, University of Texas at Dallas


Collections: Engineering