Browsing by Author "Wu, W. -R."

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Adaptive channel aided decision feedback equalisation for SISO and MIMO systems
(2006-10-01)
Lee, Y.
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Wu, W. -R.
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電信工程研究所
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Institute of Communications Engineering
Error propagation can seriously affect the performance of an adaptive decision feedback equaliser (DFE), especially when operated in time-varying channel environments. Error propagation not only affects DFE decisions, but also disturbs the DFE adaptation. The paper focuses on improving the robustness against error propagation for the least-mean-square (LMS) based minimum mean-squared-error DFE (MMSE-DFE). A specifically designed channel estimator is introduced to help the DFE adaptation in the decision-directed (DD) mode. Unlike the conventional DFE, the proposed adaptive channel-aided DFE (ACA-DFE) only adapts the feedforward filter with the LMS algorithm. The feedback filter, however, is obtained from the postcursors of the estimated channel convolved with the feedforward filter. As a result, the proposed ACA-DFE can reduce the error propagation effect and perform better than the conventional adaptive DFE. We also demonstrate that the ACA-DFE can be extended to multiple-input multiple-out (MIMO) systems improving the performance of the conventional MIMO DFE.
Adaptive parallel interference cancellation for CDMA systems - A weight selection and filtering scheme
(2011-01-01)
Hsieh, Y. -T.
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Wu, W. -R.
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電機工程學系
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Department of Electrical and Computer Engineering
Parallel interference cancellation (PIC) is a well-known multiuser detection algorithm in direct-sequence code-division multiple-access (DS-CDMA) systems. It is typically implemented with a multi-stage architecture. One problem associated with the PIC is that unreliable interference cancellation may occur in the early stages and the system performance may be degraded. Thus, the partial PIC detector was developed to control the cancellation level by use of interference cancellation factors. Partial PIC can be implemented with an adaptive form, in which optimal weights are derived using the least mean square (LMS) algorithm. In this paper, we propose an algorithm improving the conventional adaptive partial PIC. The main idea is to reduce the number of active weights in the LMS algorithm, and to perform weight post-filtering such that the resultant excess mean square error can be reduced. We also analyze the performance of the proposed algorithm and derive the bit error rate of the second stage output. Simulation results verify that the proposed algorithm outperforms the conventional partial PIC, and derived analytical results are accurate. (C) 2010 Elsevier B.V. All rights reserved.