基于高阶统计特征的空时分组码盲识别方法

闫文君; 张立民; 凌青; 洪丹枫

doi:10.11999/JEIT150739

基于高阶统计特征的空时分组码盲识别方法

doi: 10.11999/JEIT150739

1.
(海军航空工程学院电子信息工程系烟台 264001) ②(海军航空工程学院信息融合所烟台 264001) ③(青岛大学信息工程学院青岛 266071)

基金项目:

国家自然科学基金(61102167)

计量
- 文章访问数: 1210
- HTML全文浏览量: 117
- PDF下载量: 378
- 被引次数: 0
出版历程
- 收稿日期: 2015-06-18
- 修回日期: 2015-10-15
- 刊出日期: 2016-03-19

An Algorithm for Blind Classification of Space-time Block Code Based on Higher-order Statistics

1.
(Department of Electronic and Information Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China)
2.
(Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China)

Funds:

The National Natural Science Foundation of China (61102167), Taishan Scholar Special Foundation

摘要

摘要: 空时分组码的盲识别是认知无线电领域一个新的重要问题。多数现有算法在多接收天线下进行识别，然而这些算法并不完全适用于单接收天线条件。针对上述问题，该文提出一种同时适用于单接收天线和多接收天线的空时分组码盲识别方法。利用空时分组码矩阵内元素的相关性，提出四阶统计量作为盲识别的特征参数，并通过最小欧氏距离的方式检验四阶统计量的差异，达到识别的目的。蒙特卡洛仿真表明，算法识别性能较好，且不需要预先知道信道信息、噪声信息和调制信息，对多普勒频移和相位噪声具有一定的适应性。
- 认知无线电 /
- 信号盲识别 /
- 空时分组码
Abstract: Blind recognition of Space-Time Block Code (STBC) is a new important task in cognitive radio system. Most of the previous researches require multiple receive antennas, however, in many practical applications, size and power on the receivers may favor single receive antenna solution. To solve the problem above, an algorithm for blind classification of STBC is proposed. Using the correlation of the symbols in STBC block, fourth-order statistics are used as feature, and Euclidean metric between two statistics is used to classify different STBCs. It does not require estimation of the channel, signal-to-noise, and modulation of the transmitted signals. Monte Carlo simulations show the validity of the algorithm with low sensitivity to phase noise and Doppler shift.
- Cognitive radio /
- Blind signal classification /
- Space-Time Block Code (STBC)

HTML全文

参考文献(17)

DOBRE O A, ABDI A, BAR-NESS Y, et al. A survey of automatic modulation classification techniques: Classical approaches and new developments[J]. IET Communications, 2007, 1(2): 137-156.

YUCEK T and ARSLAN H. A survey of spectrum sensing algorithms for cognitive radio applications[J]. IEEE Communications Surveys and Tutorials, 2009, 11(1): 116-130.

钱国兵, 李立萍, 郭亨艺. 多入单出正交空时分组码系统的调制识别[J]. 电子与信息学报, 2015, 37(4): 863-867. doi: 10.11999/JEIT140644.

QIAN Guobing, LI Liping, and GUO Hengyi. Modulation identification for orthogonal space-time block code in multiple input single output systems[J]. Journal of Electronics Information Technology, 2015, 37(4): 863-867. doi: 10.11999/JEIT140644.

AOUADA S, ZOUBIR A M, and SEE C M. A comparative study on source number detection[C]. International Symposium on Signal Processing and its applications, Paris, France, 2003, 1: 173-176.

ELDEMERDASH Y A, MAREY M, DOBRE O A, et al. Fourth-order statistics for blind classification of spatial multiplexing and Alamouti space-time block code signals[J]. IEEE Transactions on Communications, 2013, 61(6): 2420-2431.

ELDEMERDASH Y A, DOBRE O A, MAREY M, et al. An efficient algorithm for space-time block code classification[C]. IEEE Global Communications Conference, Atlanta, GA, USA, 2013: 3329-3334.

MAREY M, DOBRE O A, and INKOL R. Classification of space time block codes based on second-order cyclostationarity with transmission impairments[J]. IEEE Transactions on Wireless Communications, 2012, 11(7): 2574-2584.

KARAMI E and DOBRE O A. Identification of SM-OFDM and AL-OFDM signals based on their second-order cyclostationarity[J]. IEEE Transaction on Vehicular Technology, 2015, 64(3): 942-953.

MOHAMMADKARIMI M and DOBRE O A. Blind identification of spatial multiplexing and Alamouti space-time block code via Kolmogorov-Smirnov(K-S) test[J]. IEEE Communications Letters, 2014, 18(10): 1711-1714.

DEMIR A, MEHROTRA, and ROYCHOWDHURY A. Phase noise in oscillators: a unifying theory and numerical methods for characterization[J]. IEEE Transactions on Circuits and Systems, 2000, 47(5): 655-674.

SWAMI A and SADLER B M. Hierarchical digital modulation classification using cumulants[J]. IEEE Transactions on Communications, 2000, 48(3): 416-429.

付卫红, 杨小牛, 刘乃安. 基于四阶累积量的稳健的通信信号盲分离算法[J]. 电子与信息学报, 2008, 30(8): 1853-1856.

FU Weihong, YANG Xiaoniu, and LIU Naian. Robust algorithm for communication signal blind separation fourth-ordercumulant-based[J]. Journal of Electronics Information Technology, 2008, 30(8): 1853-1856.

BEAULIEU N and CHENG C. Efficient Nakagami-m fading channel simulation[J]. IEEE Transactions on Vehicular Technology, 2005, 54(2): 413-424.

CHOQUEUSE V, MARAZIN M, COLLIN L, et al. Blind recognition of linear space time block codes: a likelihood-based approach[J]. IEEE Transactions on Signal Processing, 2010, 58(3): 1290-1299.

ELDEMERDASH Y A, DOBRE O A, and LIAO B J. Blind identification of SM and Alamouti STBC-OFDM signals[J]. IEEE Transactions on Wireless Communications, 2015 14(2): 972-982.

施引文献

资源附件(0)

访问统计