摘要
本文提出了一种基于可变阈值的降秩子空间选择算法及改进维数估计的盲降秩多用户检测技术.采用可变阈值的降秩子空间选择算法,能较快地得到合适的降秩子空间,且计算结果具有可重用性.在子空间追踪中用一种改进的AIC准则进行维数估计,在不提高误差概率的基础上,降低了维数估计的计算量.在维数过高估计时,分析了采用降秩算法的检测性能.仿真结果表明,该算法能用较低的计算复杂度满足系统要求的检测性能.
A blind reduced-rank multi-user detector（MUD）based on a new variable threshold reduced-rank subspace selection and an improved dimension estimation is proposed. By using the new reduced-rank subspace selection, a proper reduced-rank subspace can be obtained quickly and the subspace can be reused. The improved Akaike Information Criterion（AIC） is adopted to estimate the dimension of the signal subspace in the subspace tracking. The computation of dimension estimation can be reduced by using the criterion in the same error probability. Because AIC has a risk of overestimating the dimension of the signal subspace, the performance of the blind reduced-rank multi-user detector is specially analyzed when the signal subspace dimension is overestimated. The simulation results show that the proposed reduced-rank subspace selection algorithm can achieve the desired system performancewith lower computational complexity.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2009年第1期180-184,共5页
Acta Electronica Sinica
基金
国家自然科学基金(No.60572074)
