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A Kalman-PDA approach to soft-decision equalization for frequency selective MIMO channels

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2 Author(s)
Shoumin Liu ; Dept. of Electr. & Comput. Eng., Michigan Technol. Univ., Houghton, MI, USA ; Zhi Tian

We propose A low-complexity, near-optimal soft-decision equalization approach for frequency selective multiinput multioutput (MIMO) communication systems. With the help of iterative processing, two detection and estimation schemes based on second-order statistics are harmoniously put together to yield a two-part receiver structure: local multiuser detection (MUD) using soft-decision probabilistic data association (PDA) detection, and dynamic noise-interference tracking using Kalman filtering. The proposed Kalman-PDA approach performs local MUD to reduce the computational load, while all the interference affecting the local subblock is dynamically tracked by Kalman filtering, to maintain near-optimum detection performance. Two types of Kalman filters are designed, both of which are able to track a finite impulse response (FIR) MIMO channel of any memory length. The overall algorithms enjoy low complexity that is only polynomial in the number of information-bearing bits to be detected, regardless of the data block size. The near-optimum detection performance is testified via simulations.

Published in:

Signal Processing Advances in Wireless Communications, 2004 IEEE 5th Workshop on

Date of Conference:

11-14 July 2004

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