Performance analysis of RLS linearly constrained constant modulus algorithm for multiuser detection
| Autor: | Xin Wang, Guangzeng Feng |
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| Rok vydání: | 2009 |
| Předmět: |
Mean squared error
Code division multiple access Multiuser detection Adaptive filter Stochastic gradient descent Rate of convergence Control and Systems Engineering Signal Processing Convergence (routing) Computer Vision and Pattern Recognition Electrical and Electronic Engineering Algorithm Gradient method Software Computer Science::Information Theory Mathematics |
| Zdroj: | Signal Processing. 89:181-186 |
| ISSN: | 0165-1684 |
| DOI: | 10.1016/j.sigpro.2008.08.007 |
| Popis: | The linearly constrained constant modulus algorithm (LCCMA) is a blind multiuser detector (MUD) solution to multiple access interference (MAI) suppression that is widely investigated in direct-sequence code division (DS-CDMA) systems. However, the conventional CMA based on the stochastic gradient descent (SGD) has slow convergence speed. Our research introduces an approximation of recursive least square (RLS) into LCCMA for better convergence speed in DS-CDMA system and quantifies the performance of blind adaptive filter based on RLS-LCCMA in both a static and a time-varying channel. In this investigation, we derive the expressions for the excess mean-square error (EMSE) of the MUD with a framework called feedback approach, and further obtain a relationship between the step size of SGD-LCCMA and the forgetting factor of RLS-LCCMA. Eventually, simulation results show the advantage of RLS-LCCMA and verify the performance analysis of the algorithm. |
| Databáze: | OpenAIRE |
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