| Popis: |
In the context of Cognitive Radio (CR), opportunistic transmissions can exploit temporarily vacant spectral bands. Efficient and reliable spectrum sensing is key in the CR process. CR receivers traditionally deal with wideband signals with high Nyquist rates and low Signal to Noise Ratios (SNRs). Sub-Nyquist sampling of such signals has been proposed for efficient sampling in CRs. The modulated wideband converter (MWC) is an example of such a sampling scheme. It is composed of an analog front-end, that aliases the signal intentionally before sampling it at a low rate. The signal can then be digitally reconstructed from the low rate samples, using the known relation between the samples and the original signal. Unfortunately, in real hardware implementation, this relation becomes unknown. Physical effects have a considerable impact on the sampling process, and as a consequence, the signal cannot be reliably recovered. In this paper, we present an efficient automated calibration algorithm that builds the actual transfer function of the system, without any prior knowledge. We then present a new, MWC based, CR prototype, on which the calibration algorithm was tested. Experiments on our hardware prototype, based on an embedded proprietary card, show that our calibrated transfer function leads to signal reconstruction whereas the theoretical one fails. Our specification complies with CR requirements of the IEEE standard 802.22 and was experimentally verified with different modulations. It vastly improves a previous prototype in terms of bandwidth, higher maximal frequency and coping with lower SNR. |
