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Spectrum sensing based on flexible RF filtering

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Background

Spectrum sensing is a fundamental technique for cognitive radio (CR) systems which aim at dynamic spectrum access to increase the system capacity. Basically, a user who in an opportunistic way would like to access a fragment of RF spectrum must avoid interference with a possible current user. For this reason a reliable and time-effective spectrum sensing over the frequencies of interest is necessary. The problem becomes not trivial when the signal to be detected is difficult to distinguish from noise. In this case, algorithms like cyclostationary feature-based or matched filter-based can be used. For strong enough signals detection of the RF power level is sufficient and further signal processing at baseband can be omitted. In any case, however, appropriate RF filtering preceding the detection process is essential.

Problem statement

In this project a flexible RF filter model should be investigated in terms of different spectrum sensing scenarios. The objective is to derive minimum processing-time procedures based on RF filtering where both the filter center frequency and bandwidth can be programmed online. The filter, so called RF N-path filter, provides both RF and baseband signal so it can be used to measure the signal power level at RF (using a simple RF detector) or to measure the corresponding baseband signal suitable for digital processing. In the latter case the possible noise-like signal should be discriminated, e.g. by a matched filter.

One design tradeoff to be verified is presented by the RF filter, i.e. as the filter is more narrowband it makes use of larger capacitances that in turn result in longer transient time when the filter is reprogrammed to change the center frequency or bandwidth.

Prerequisites

Familiarity with Cadence simulator and programing skills in Matlab.

References

[1] Qazi F., Duong Q-T and Dabrowski J., Two-Stage Highly Selective Receiver Front-End Based on Impedance Transformation Filtering, IEEE Trans. on Circuits and Systems II, 2014, DOI: 10.1109/TCSII.2014.2385213
[2] A. Garhwal and P. P. Bhattacharya, A Survey on Spectrum Sensing Techniques in Cognitive Radio, Intl. Journal of Computer Science & Communication Networks,Vol 1(2), 196-206 //www.ijcscn.com/Documents/Volumes/vol1issue2/ijcscn2011010213.pdf

Page responsible: Danyo Danev
Last updated: 2015 04 16   10:37