Angrisani, Leopoldo

Capriglione, Domenico

Ferrigno, Luigi

Miele, Gianfranco

UPCommons. Portal del coneixement obert de la UPC

19TH IMEKO TC-4 Measurements of Electrical Quantities26   PSD estimation in Cognitive Radio systems: a performance analysis  On compressed sensing and super-resolution in DFT-based spectral analysisLeopoldo Angrisani62, Domenico Capriglione63, Luigi Ferrigno63, Gianfranco Miele63M. Bertocco64, G. Frigo64, C. Narduzzi64Nowadays, radio systems have to use the spectrum resource more intensely than in the past to meet the demanding expec-tations of the users. Several studies have demonstrated that portions of radio spectrum are not in use for significant peri-ods of time. Cognitive radios systems have been conceived to overcome this limit, enabling a flexible spectrum allocation, and making a more intensive and efficient spectrum use by the users sharing spectrum access. To meet this goal, cognitive radio terminals have to dynamically select the appropriate op-erating frequency based on the sensing of signals from other transmitters. This capability is usually called frequency agility. In this framework the authors have already proposed a meas-urement method able to meet the frequency agility require-ment. It is based on two sequential steps: the former performs the spectrum sensing, while the latter selects an operating fre-quency for the terminal that minimizes potential interference with a primary user. The paper focuses the attention on the improvement of the first step. Several power spectrum estima-tion methods are investigated in order to simplify the spec-trum sensing stage, especially in terms of overall computa-tional burden, without worsening the algorithm performance.Keywords-Power spectrum, PSD estimation, spectrum sens-ing, cognitive radio.The paper discusses a novel frequency interpolation and super-resolution method for multitone waveform analysis, where a compressive sensing algorithm is employed to pro-cess data. Each signal acquisition involves a short data record, whose DFT coefficients are computed and summed to obtain a single scalar quantity. A set of compressive measurements is obtained by taking records with different known starting in-stants, and employed to determine, by solving an l1-l2 convex problem, the set of frequency components of the analysed waveform. Interpolation is presented as a compressive sens-ing problem and algorithm performances discussed.Effect of the trace smoothing. The original PSD has been acquired considering a SNR equal to 5 dB.07WA128 07WA143

PSD estimation in Cognitive Radio systems: a performance analysis

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