Threshold Selection Algorithm Based on Skewness and Standard Deviation Using Back Propagation Artificial Neural Networks in the 60GHz Wireless Communication Systems

Xiao-Lin Liang; Hao Zhang; Ting-Ting Lu; Xue-rong Cui; T.Aaron.Gulliver

Threshold Selection Algorithm Based on Skewness and Standard Deviation Using Back Propagation Artificial Neural Networks in the 60GHz Wireless Communication Systems

원문정보

Xiao-Lin Liang, Hao Zhang, Ting-Ting Lu, Xue-rong Cui, T.Aaron.Gulliver

보안공학연구지원센터(IJSH) International Journal of Smart Home Vol.10 No.2 2016.02 pp.245-278

피인용수 : 0건 (자료제공 : 네이버학술정보)

Abstract
1. Introduction
2. System Model
  2.1. 60GHz Signal
  2.2. Signal Shift and Path Loss
  2.3. Multipath Fading Channel
  2.4. Energy Detector
3. TOA Estimation Based on Energy Detector
  3.1. TOA Estimation Algorithms
  3.2. Error Analysis
4. Statistical  Characteristics
  4.1. Kurtosis
  4.2. Standard Deviation
  4.3. Skewness
  4.4. Characteristics of the Parameters
5. Optimal Threshold Selection
  5.1. Relationship between G and SNR
  5.2. Relationship between MAE and the Normalized Threshold
  5.3. Optimal Thresholds
6. Threshold Selection Using an BP-ANN based on G
  6.1. Structure of the BP-ANN
  6.2. BP-ANN Training
  6.3. Vaildation of the BP-ANN
7. Results and Discussion
8. Conclusion
References

키워드

저자정보

Xiao-Lin Liang College of Information Science and Engineering, Ocean University of China
Hao Zhang College of Information Science and Engineering, Ocean University of China, Department of Electrical and Computer Engineering, University of Victoria, Victoria V8W 3P 6, China
Ting-Ting Lu College of Information Science and Engineering, Ocean University of China
Xue-rong Cui Department of Computer and Communication Engineering, China University of Petroleum(East China)
T.Aaron.Gulliver Department of Electrical and Computer Engineering, University of Victoria, Victoria V8W 3P 6, China

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