Sequence Set Design With Good Correlation Properties Via Majorization-Minimization
Sequence Set Design With Good Correlation Properties Via Majorization-Minimization
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DOI：
10.1109/tsp.2016.2535312
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发表时间：
2016-06-01
影响因子：
5.4
通讯作者：
Palomar, Daniel P.
中科院分区：
文献类型：
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作者：
Song, Junxiao;Babu, Prabhu;Palomar, Daniel P.
在许多主动感测和通信系统（例如，多输入多输出（MIMO）雷达系统和码分多址（CDMA）蜂窝系统。在本文中，我们考虑的问题，设计互补序列集（CSS），也具有良好的自相关和互相关特性的序列集。基于广义优化-极小化方法，提出了求解序列集设计问题的优化算法。所有提出的算法都可以通过快速傅立叶变换（FFT）来实现，因此计算效率高，能够设计非常长的序列集。一些数值例子来证明所提出的算法的性能。
Sets of sequences with good correlation properties are desired in many active sensing and communication systems, e.g., multiple-input-multiple-output (MIMO) radar systems and code-division multiple-access (CDMA) cellular systems. In this paper, we consider the problems of designing complementary sets of sequences (CSS) and also sequence sets with both good auto- and cross-correlation properties. Algorithms based on the general majorization-minimization method are developed to tackle the optimization problems arising from the sequence set design problems. All the proposed algorithms can be implemented by means of the fast Fourier transform (FFT) and thus are computationally efficient and capable of designing sets of very long sequences. A number of numerical examples are provided to demonstrate the performance of the proposed algorithms.