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Full-Text Articles in Engineering
A Low-Complexity Iterative Channel Estimation And Detection Technique For Doubly Selective Channels, Qinghua Guo, Li Ping, Defeng (David) Huang
A Low-Complexity Iterative Channel Estimation And Detection Technique For Doubly Selective Channels, Qinghua Guo, Li Ping, Defeng (David) Huang
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, we propose a low-complexity iterative joint channel estimation, detection and decoding technique for doubly selective channels. The key to the proposed technique is a segment-by-segment processing strategy under the assumption that the channel is approximately static within a short segment of a data block. Through a virtual zero-padding technique, the proposed segment-by-segment equalization approach inherits the low-complexity advantage of the conventional frequency domain equalization (FDE), but does not need the assistance of guard interval (for cyclic-prefixing or zero-padding), thereby avoiding the spectral and power overheads. Furthermore, we develop a low-complexity bidirectional channel estimator, where the Gaussian message …
Pavement Scene Interpretation And Obstacle Detection By Large Margin Image Labeling, Ke Jia, Nianjun Liu, Lei Wang, Li Cheng
Pavement Scene Interpretation And Obstacle Detection By Large Margin Image Labeling, Ke Jia, Nianjun Liu, Lei Wang, Li Cheng
Faculty of Engineering and Information Sciences - Papers: Part A
This paper presents a novel discriminative approach for pave-ment scene understanding and obstacle detection in real-world images. It overcomes the heavy constraints in previous systems such as a simple background, a specic obstacle, etc. The approach we exploited extends the bundle method to incorporate pairwise correlations among neighboring pixels, and adopts graph-cuts as the inference engine to attain the approximation efficiently. A set of robust features on both local and multi-scale level is also introduced that captures the general statistical properties of pavements and obstacles. The proposed approach is validated on real-world image database, and outperforms the current state-of-the-art visioned-based …
Superposition Coded Modulation And Iterative Linear Mmse Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Superposition Coded Modulation And Iterative Linear Mmse Detection, Li Ping, Jun Tong, Xiaojun Yuan, Qinghua Guo
Faculty of Engineering and Information Sciences - Papers: Part A
We study superposition coded modulation (SCM) with iterative linear minimum-mean-square-error (LMMSE) detection. We show that SCM offers an attractive solution for highly complicated transmission environments with severe interference. We analyze the impact of signaling schemes on the performance of iterative LMMSE detection. We prove that among all possible signaling methods, SCM maximizes the output signal-tonoise/interference ratio (SNIR) in the LMMSE estimates during iterative detection. Numerical examples are used to demonstrate that SCM outperforms other signaling methods when iterative LMMSE detection is applied to multi-user/multi-antenna/multipath channels. © 2009 IEEE.