David J. Allstot

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Compressed sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist processing of sparse signals such as electrocardiogram (ECG) and electromyogram (EMG) biosignals. Consequently, it can be applied to biosignal acquisition systems to reduce the data rate to realize ultra-low-power performance. CS is compared to conventional and(More)
Dynamic spectrum access (DSA) is a promising approach for the more effective use of existing spectrum. Of fundamental importance to DSA is the need for fast and reliable spectrum sensing over a wide bandwidth. A model for two-stage sensing is described based on an analysis of the mean time to detect an idle channel. Simulation results show that it provides(More)
Inductive-peaking-based bandwidth extension techniques for CMOS amplifiers in wireless and wireline applications are presented. To overcome the conventional limits on bandwidth extension ratios, these techniques augment inductive peaking using capacitor splitting and magnetic coupling. It is shown that a critical design constraint for optimum bandwidth(More)
A parallel, multi-resolution spectrum sensing technique that is amenable to multiple-antenna cognitive radios is introduced. We show that for energy-detector-type spectrum sensors, the total sensing time due to FFT latency is reduced by 100 times using the proposed method versus the fixed-resolution, serial detection method employed in singleantenna(More)
A fully integrated switched-capacitor power amplifier (SCPA) utilizes switched-capacitor techniques in an EER/Polar architecture. It operates on the envelope of a nonconstant envelope modulated signal as an RF-DAC in order to amplify the signal efficiently. The measured maximum output power and PAE are 25.2 dBm and 45 %, respectively. When amplifying an(More)