NDLI: LTE signal classification and center frequency detection without Priori information

Content Provider	IEEE Xplore Digital Library
Author	Erpek, T. Steadman, K. Krishnan, R. Qiao Chen
Copyright Year	2012
Description	Author affiliation: Shared Spectrum Company, Vienna, VA, USA (Erpek, T.; Steadman, K.; Krishnan, R.; Qiao Chen)
Abstract	Creating a cognitive Long Term Evolution (LTE) network on an arbitrary frequency requires an LTE specific classifier. This paper explains a novel LTE signal classification method that requires no a priori information about the signal parameters including its frequency. The classification method consists of multiple steps. The first step is using a correlation-based discriminator which exploits the characteristics of the LTE cyclic prefix, cell-specific reference symbol sequence and physical broadcast channel. A set of candidate LTE signal frequencies and confidence factors are determined at the end of this step. The candidate frequency set is narrowed down in the second step using the confidence factors. The third step is to estimate the center frequency of the LTE signal. This step relies on known signal characteristics including the synchronization sequences. The time-domain LTE signal is represented in frequency and time grids and two-dimensional cross-correlation is performed. The algorithms were simulated and then implemented on a real-time platform. The results show that an LTE signal with signal-to-noise ratio (SNR) of less than 0 dB can be classified within 0.23 sec.
Starting Page	299
Ending Page	304
File Size	1360379
Page Count	6
File Format	PDF
ISBN	9781467344470
e-ISBN	9781467344487
e-ISBN	9781467344463
DOI	10.1109/DYSPAN.2012.6478153
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time-frequency analysis Correlation OFDM Bandwidth Classification Synchronization Sequences Classification algorithms Synchronization Cognitive radio LTE Long Term Evolution Reference Symbol
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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