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| Minimum Bayesian Risk Based Robust Spectrum Prediction in Dynamic Spectrum Access |
| CHEN Xi① YANG Jian② |
①(School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China)
②(Nanjing Telecommunication Technology Institute, Nanjing 210007, China) |
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Abstract The accumulation of miss detection and false alarm in spectrum sensing leads to the persistently decreasing of prediction accuracy in spectrum prediction. This paper takes neural network based spectrum prediction for example, and presents a minimum Bayesian Risk based spectrum prediction to solve this problem. The distribution fitting shows that the prediction output follows the normal distribution. The expectation of prediction mean square error is defined as the Bayesian Risk, and the optimal detection threshold of the prediction output is derived through minimizing the Bayesian Risk. Through this method, the prediction accuracy is insensitive to the spectrum sensing errors. Compared with the traditional spectrum prediction with fixed detection thresholds, simulation results demonstrate the robust spectrum prediction keeps the prediction accuracy stable, and improve the performance in dynamic spectrum access.
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Received: 27 May 2017
Published: 27 December 2017
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| Fund:The National Natural Science Foundation of China (61471395, 61471392, 61301161), The Natural Science Foundation of Jiangsu Province (BK20141070) |
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Corresponding Authors:
YANG Jian
E-mail: yangjian_njust@foxmail.com
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| [1] |
WANG Tan, LI Gen, and DING Jiaxin. 5G Spectrum: Is China ready?[J]. IEEE Communications Magazine, 2015, 53(7): 58-65. doi: 10.1109/MCOM.2015.7158266.
|
| [2] |
NING Guoqin and NINTANAVONGSA P. Time prediction based spectrum usage detection in centralized cognitive radio networks[C]. 2012 IEEE Wireless Communications and Networking Conference (WCNC), Shanghai, China, 2012: 300-305. doi: 10.1109/WCNC.2012.6214320.
|
| [3] |
SONG Yi and XIE Jiang. ProSpect: A proactive spectrum handoff framework for cognitive radio ad hoc networks without common control channel[J]. IEEE Transactions on Mobile Computing, 2012, 11(7): 1127-1139. doi: 10.1109/ TMC.2011.140.
|
| [4] |
GUAN Quansheng, RICHARD Y F, and JIANG Shengming. Prediction-based topology control and routing in cognitive radio mobile Ad hoc networks[J]. IEEE Transactions on Vehicular Technology, 2011, 59(9): 4443-4452. doi: 10.1109/ TVT.2010.2069105
|
| [5] |
GHOSH A and SARKAR S. Quality-sensitive price competition in secondary market spectrum oligopoly-single location game[J]. IEEE/ACM Transactions on Networking, 2016, 24(3): 1894-1907. doi: 10.1109/TNET.2015.2440422.
|
| [6] |
GHOSH A, SARKAR S, and BERRY R. The value of side information in secondary spectrum markets[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(1): 6-19. doi: 10.1109/JSAC.2016.2632579.
|
| [7] |
KUMAR A, SINGH S, and ZHENG Haitao. Reliable open spectrum communications through proactive spectrum access[C]. 2006 International Workshop on Technology and Policy for Accessing Spectrum (TAPAS), Boston, American, 2006: 5. doi: 10.1145/1234388.1234393.
|
| [8] |
ELTOM H, KANDEEPAN S, LIANG Yingchang, et al. HMM based cooperative spectrum occupancy prediction using hard fusion[C]. 2016 IEEE International Conference on Communications Workshops (ICC), Kuala Lumpur, Malaysia, 2016: 669-675. doi: 10.1109/ICCW.2016.7503864.
|
| [9] |
TUMULURU V, WANG Ping, and NIYATO D. Channel status prediction for cognitive radio networks[J]. Wireless Communications and Mobile Computing, 2012, 12(10): 862-874. doi: 10.1002/wcm.1017.
|
| [10] |
SU Jinzhao and WU Wei. Wireless spectrum prediction model based on time series analysis method[C]. 2009 ACM workshop on Cognitive radio networks, Beijing, China (CoRoNET), Beijing, China, 2009: 61-66. doi: 10.1145/ 1614235.1614250.
|
| [11] |
WEN Zheng, LUO Tian, and WANG Xiang. Autoregressive spectrum holes prediction model for cognitive radio systems[C]. 2008 IEEE Communications Workshop (ICC), Beijing, China, 2008: 154-157. doi: 10.1109/ICCW.2008.34.
|
| [12] |
TANG Mengyun, DING Guoru, WU Qihui, et al. A joint tensor completion and prediction scheme for multi- dimensional spectrum map construction[J]. IEEE Access, 2016(4): 8044-8052. doi: 10.1109/ACCESS.2016.2627243.
|
| [13] |
RAZALI N M and WAH Y B. Power comparisons of shapiro- wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests[J]. Journal of Statistical Modeling and Analytics, 2011, 2(1): 21-33.
|
| [14] |
BAO Yong. On sample skewness and kurtosis[J]. Econometric Reviews, 2013, 32(4): 415-448. doi: 10.1080/07474938.2012. 690665.
|
| [15] |
MASONTA M, MZYECE M, and NTLATLAPA N. Spectrum decision in cognitive radio networks: A survey[J]. IEEE Communications Surveys & Tutorials, 2013, 15(3): 1088-1107. doi: 10.1109/SURV.2012.111412.00160.
|
|
|
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