The Non-data-aided Channel Order and Noise VarianceEstimation in the Low SNR Region of OFDM Signals

WANG Dong; ZHAO Jiaxiang; YU Lihong

doi:10.11999/JEIT150599

Volume 38 Issue 2

Feb. 2016

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(2): 276-281

WANG Dong, ZHAO Jiaxiang, YU Lihong. The Non-data-aided Channel Order and Noise VarianceEstimation in the Low SNR Region of OFDM Signals[J]. Journal of Electronics & Information Technology, 2016, 38(2): 276-281. doi: 10.11999/JEIT150599

Citation:

WANG Dong, ZHAO Jiaxiang, YU Lihong. The Non-data-aided Channel Order and Noise VarianceEstimation in the Low SNR Region of OFDM Signals[J]. Journal of Electronics & Information Technology, 2016, 38(2): 276-281. doi: 10.11999/JEIT150599

Citation:

PDF( 813 KB)

The Non-data-aided Channel Order and Noise VarianceEstimation in the Low SNR Region of OFDM Signals

doi: 10.11999/JEIT150599

1.
(College of Computer and Control Engineering, Nankai University, Tianjin 300071, China)
2.
(College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, China)

Funds:

Natural Science Foundation of Tianjin (14JCYBJC16100)

Received Date: 2015-05-21
Rev Recd Date: 2015-11-04
Publish Date: 2016-02-19

Abstract

Abstract

This paper proposes a new Non-Data-Aided (NDA) scheme to estimate the channel order and noise variance in the low Signal to Noise Ratio (SNR) region of Orthogonal Frequency Division Multiplexing (OFDM) signals. In this scheme, a new cost function is derived based on the joint Maximum Geometric Mean (MGM) which relies on both the Cyclic Prefix (CP) redundancy and channel memory. Compared with the schemes which only rely on the CP, more accurate estimations of channel order and noise variance can be obtained from this joint MGM cost function. Simulation results show that the proposed channel order estimator gets approximately 10 dB SNR gain in the low SNR region. Meanwhile, the proposed noise variance estimator outperforms significantly the other existing NDA algorithms, and suppresses the performance deterioration when SNR below 20 dB.
- OFDM,
- Channel order and noise variance estimation,
- Low SNR,
- Non-Data-Aided (NDA),
- Joint Maximum Geometric Mean (MGM)

FullText(HTML)

References(21)

References

袁龙, 邢禄, 彭涛, 等. 基于精确噪声估计的迭代频谱感知算法[J]. 电子与信息学报, 2014, 36(3): 655-661. doi:10.3724/SP. J.1146.2013.00659.

YUAN Long, XING Lu, PENG Tao, et al. An iterative spectrum sensing algorithm based on accurate noise estimation[J]. Journal of Electronics Information Technology, 2014, 36(3):655-661. doi:10.3724/SP.J.1146. 2013.00659.

谢显中, 胡小峰, 马彬. 噪声功率不确定性区间估计和降低SNR WALL恶化的能量检测算法[J]. 电子与信息学报, 2014, 36(2): 364-370. doi: 10.3724/SP.J.1146.2013.00928.

XIE Xianzhong, HU Xiaofeng, and Ma Bin. Estimation of noise power uncertainty interval and energy detector with lowering SNR WALL deterioration[J]. Journal of Electronics Information Technology, 2014, 36(2): 364-370. doi: 10.3724/SP.J.1146.2013.00928.

劳子轩, 刘子扬, 彭涛, 等. 全盲频谱感知：噪声估计与能量检测联合迭代算法[J]. 电子与信息学报, 2013, 35(8): 1958-1963. doi: 10.3724/SP.J.1146.2012.01617.

LAO Zixuan, LIU Ziyang, PENG Tao, et al. Totally-blind spectrum sensing: A joint iterative algorithm of noise estimation and energy detection[J]. Journal of Electronics Information Technology, 2013, 35(8): 1958-1963. doi: 10.3724/SP.J.1146.2012.01617.

SHENG Bin. A robust non-data-aided SNR estimation method for OFDM systems[J]. Transactions on Emerging Telecommunications Technologies, 2013, 26(2): 103-106. doi: 10.1002/ett.2612.

SAVAUX V, DJOKO-KOUAM M, LOUET Y, et al. Convergence analysis of a joint signal-to-noise ratio and channel estimator for frequency selective channels in orthogonal frequency division multiplexing context[J]. IET Signal Processing, 2014, 8(6): 693-701. doi:10.1049/ iet-spr.2013.0407.

SUN Minying, LI Yuan, and SUN Sumei. Impact of SNR estimation error on turbo code with high-order modulation[C]. IEEE 59th Vehicular Technology Conference, Milan, 2004, 3: 1320-1324. doi:10.1109/VETECS.2004. 1390467.

岳光荣, 田浩, 杨霖, 等. LTE中一种基于探测参考信号的信噪比估计算法[J]. 电子与信息学报, 2014, 36(1): 241-245. doi: 10.3724/SP.J.1146.2013.00885.

YUE Guangrong, TIAN Hao, YANG Lin, et al. SNR estimation algorithm based on sounding reference signal in LTE[J]. Journal of Electronics Information Technology, 2014, 36(1): 241-245. doi: 10.3724/SP.J.1146.2013.00885.

BAUMGARTNER S, HIRTZ G, and BAUMGARTNER A. A modified maximum likelihood method for SNR estimation in OFDM based systems[C]. IEEE International Conference on Consumer Electronics.(ICCE), Las Vegas, 2014: 155-158. doi: 10.1109/ICCE.2014.6775951.

CUI Tao and TELLAMBURA C. Power delay profile and noise variance estimation for OFDM[J]. IEEE Communications Letters, 2006, 10(1): 25-27. doi:10.1109/ LCOMM.2006.1576558.

SOCHELEAU F, AISSA-EL-BEY A, and HOUCKE S. Non data-aided SNR estimation of OFDM signals[J]. IEEE Communications Letters, 2008, 12(11): 813-815. doi:10.1109/ LCOMM.2008.081134.

WANG Kun and ZHANG Xianda. Blind noise variance and SNR estimation for OFDM systems based on information theoretic criteria[J]. Signal Processing, 2010, 90(9): 2766-2772. doi: 10.1016/j.sigpro.2010.03.007.

NGUYEN V D, KUCHENBECKER H, and PATZOLD M. Estimation of the channel impulse response length and the noise variance for OFDM systems[C]. IEEE 61th Vehicular Technology Conference, Stockholm, 2005, 1: 429-433. doi: 10.1109/VETECS.2005.1543326.

田浩, 杨霖, 李少谦. LTE上行链路中基于探测参考信号的信噪比估计[J]. 电子与信息学报, 2014, 36(2): 353-357. doi: 10.3724/SP.J.1146.2013.00445.

TIAN Hao, YANG Lin, and LI Shaoqian. SNR estimation based on sounding reference signal in long term evolution uplink[J]. Journal of Electronics Information Technology, 2014, 36(2): 353-357. doi: 10.3724/SP.J.1146.2013.00445.

WANG Kun and ZHANG Xianda. Robust spectrum sensing algorithm for cognitive radio networks[C]. IEEE 10th International Conference on Signal Processing (ICSP), Beijing, 2010: 1520-1523. doi: 10.1109/ICOSP.2010.5656703.

VAN DE BEEK J, SANDELL M, and BORJESSON P O. ML estimation of time and frequency offset in OFDM systems[J]. IEEE Transactions on Signal Processing, 1997, 45(7): 1800-1805. doi: 10.1109/78.599949.

BARTLETT M S. On the theoretical specification and sampling properties of autocorrelated time-series[J]. Supplement to the Journal of the Royal Statistical Society, 1946, 8(1): 27-41. doi: 10.2307/2983611.

Relative Articles

Supplements(0)

Cited By

Proportional views