Iterative soft-kalman filter-based data detection and channel estimation for turbo coded MIMO-OFDM systems

被引:1
作者
Kim K.J. [1 ]
Iltis R.A. [2 ]
机构
[1] Nokia Inc., Irving, TX 75039
[2] Department of Electrical and Computer Engineering, University of California, Santa Barbara
基金
美国国家科学基金会;
关键词
Kalman filtering; MIMO; OFDM; Turbo Codes;
D O I
10.1007/s10776-007-0059-0
中图分类号
学科分类号
摘要
MIMO channels are often assumed to be constant over a block or packet. This assumption of block stationarity is valid for many fixed wireless scenarios. However, for communications in a mobile environment, the stationarity assumption will result in considerable performance degradation. In this paper, we focus on a new channel estimation technique for Turbo coded MIMO systems using OFDM. In the proposed MIMO-OFDM system, pilots are placed on selected subcarriers and used by a pair of Kalman filter (KF) channel estimators at the receiver. The KF channel estimates are then utilized by a MIMO-OFDM soft data detector based on the computationally efficient QRD-M algorithm. The soft detector output is fed back to the Kalman filters to iteratively improve the channel estimates. The extrinsic information generated by the Turbo decoder is also used as a priori information for the soft data detector. The overall receiver thus combines MIMO data detection, KF-based channel estimation, and Turbo decoding in a joint iterative structure yielding computational efficiency and improved bit-error rate (BER) performance. © 2007 Springer Science+Business Media, LLC.
引用
收藏
页码:175 / 189
页数:14
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