1. bookVolume 11 (2011): Issue 1 (February 2011)
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
access type Open Access

A New Digital Signal Processing Method for Spectrum Interference Monitoring

Published Online: 08 Apr 2011
Volume & Issue: Volume 11 (2011) - Issue 1 (February 2011)
Page range: 1 - 8
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
A New Digital Signal Processing Method for Spectrum Interference Monitoring

Frequency spectrum is a limited shared resource, nowadays interested by an ever growing number of different applications. Generally, the companies providing such services pay to the governments the right of using a limited portion of the spectrum, consequently they would be assured that the licensed radio spectrum resource is not interested by significant external interferences. At the same time, they have to guarantee that their devices make an efficient use of the spectrum and meet the electromagnetic compatibility regulations. Therefore the competent authorities are called to control the access to the spectrum adopting suitable management and monitoring policies, as well as the manufacturers have to periodically verify the correct working of their apparatuses. Several measurement solutions are present on the market. They generally refer to real-time spectrum analyzers and measurement receivers. Both of them are characterized by good metrological accuracies but show costs, dimensions and weights that make no possible a use "on the field". The paper presents a first step in realizing a digital signal processing based measurement instrument able to suitably accomplish for the above mentioned needs. In particular the attention has been given to the DSP based measurement section of the instrument. To these aims an innovative measurement method for spectrum monitoring and management is proposed in this paper. It performs an efficient sequential analysis based on a sample by sample digital processing. Three main issues are in particular pursued: (i) measurement performance comparable to that exhibited by other methods proposed in literature; (ii) fast measurement time, (iii) easy implementation on cost-effective measurement hardware.

Keywords

Textronix Inc. (2007). Application Note "Advanced Spectrum Management with the RSA6100A Series Real-Time Spectrum Analyzer". Retrieved March 4, 2008, from Tektronix web site http://www.tek.comSearch in Google Scholar

Textronix Inc. (2007). Application Note "RF Signal Monitoring and Spectrum Management Using the Tektronix RSA3000B Series Real-Time Spectrum Analyzer". Retrieved March 4, 2008, from Tektronix web site http://www.tek.comSearch in Google Scholar

Luther, W. A. (2003). Spectrum management in the global village. In IEEE International Symposium on Electromagnetic Compatibility 2003, Vol. 2, 11-16 May 2003. Istanbul, Turkey, 701-704.10.1109/ICSMC2.2003.1428996Search in Google Scholar

Tektronix Inc. (2006). RSA3408A 8 GHz Real-Time Spectrum Analyzer User Manual. Beaverton, OR: Tektronix Inc.Search in Google Scholar

Erickson, D. (2007). Improving spectrum masurement and monitoring in commercial wireless applications. Agilent Meas. J., 2, 14-19. Retrieved May 30, 2007, from Agilent Technologies web site http://www.agilent.com http://www.agilent.comSearch in Google Scholar

Agilent Technologies Inc. (2009). Datasheet Agilent W1314A Multi-band Wireless Measurement Receiver. Retrieved April 30, 2009, from Agilent Technologies web site http://www.agilent.comSearch in Google Scholar

TCI International Inc. (2007). Datasheet TCI Model 745 spectrum monitoring system. Retrieved July 17, 2008, from TCI International web site http://www.tcibr.comSearch in Google Scholar

Marple, L. (1987). Digital Spectral Analysis with Applications. Englewood Cliffs, NJ, USA: Prentice-Hall.Search in Google Scholar

Angrisani, L., Capriglione, D., Ferrigno, L., Miele, G. (2008). Power measurements in DVB-T systems: New proposal for enhancing reliability and repeatability. IEEE Trans. Instrum. Meas., 57 (10), 2108-2117.10.1109/TIM.2008.922108Search in Google Scholar

Angrisani, L., Capriglione, D., Ferrigno, L., Miele, G. (2008). Sequential parametric spectral estimation for power measurements in DVB-T systems. In IEEE Instrumentation and Measurement Technology Conference, 12-15 May 2008. Victoria, BC, Canada, 314-319.10.1109/IMTC.2008.4547053Search in Google Scholar

Angrisani, L., Capriglione, D., Ferrigno, L., Miele, G. (2009). Power measurement in DVB-T systems: On the suitability of parametric spectral estimation in DSP-based meters. IEEE Trans. Instrum. Meas., 58 (1), 76-86.10.1109/TIM.2008.928870Search in Google Scholar

Burg, J. P. (1967). Maximum entropy spectral analysis. In 37th Meeting Society of Exploration Geophysicists, 31 Oct. 1967. Oklahoma City, USA.Search in Google Scholar

Kay, S. M., Marple, S. L. (1981). Spectrum analysis-A modern perspective. In Proc. of the IEEE, 69 (11), 1380-1419.10.1109/PROC.1981.12184Search in Google Scholar

Srinath, M. D., Viswanathan, M. M. (1975). Sequential algorithm for identification of parameters of an autoregressive process. IEEE Trans. Automat. Contr., 20 (4), 542-546.10.1109/TAC.1975.1101017Search in Google Scholar

Manolakis, D. G., Ingle, V. K., Kogon, S. M. (2005). Statistical and Adaptive Signal Processing. Norwood, MA, USA: Artech House.Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo