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| A Linearly Constrained LSCM Algorithm Based on Subspace |
| Meng Yan; Wang Jin-kuan; Zhu Jun |
| School of Information Science and Engineering, Northeastern University, Shenyang 110004, China |
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Abstract Linearly constrained Least Square Constant Modulus Algorithm (LSCMA) is an effective solution to the problem of interference capture in Constant Modulus Algorithm (CMA). But the performance will degrade when it is affected by the noise subspace in practical situations. In order to overcome this shortage, a subspace-based linearly constrained LSCMA multiuser detection algorithm is proposed. The proposed algorithm offers fast convergence rate, has good channel tracking ability and provides excellent output Signal-to-Interference-plus- Noise-Ratio (SINR) and Bit Error Rate (BER) performance. Theory analysis and simulation results demonstrate the effectiveness and superiority of the proposed algorithm.
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Received: 25 July 2007
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2009, Vol. 31 
