Claude Shannon

Wednesday, February 24th, 2016

Room 202 in Packard Bldg., Stanford University
Parking Generally Free In Nearby Lots After 4:00 pm

Refreshments and Conversation at 6:00 P.M.
Presentation at 6:30 P.M.

Interleaved direct bandpass sampling for software defined radio/radar receivers

Prof. Bernard Levy
Department of Electrical and Computer Engineering, UC Davis


     Due to their low hardware complexity, direct bandpass sampling front ends have become attractive for software defined radio/radar applications. These front ends require three elements: a tunable filter to select the band of interest, a wideband sample and hold to acquire the bandpass signal, and finally an analog to digital converter (ADC) to digitize the signal. Unfortunately, due to the overlap of aliased copies of the positive and negative signal spectrum components, if a single ADC is employed, depending on the exact position of the band where the signal is located, it is not always possible to sample a signal of occupied bandwidth B at a sampling rate ?s just above the 2B Nyquist rate. Sometimes, much higher rates are needed. For software radio applications, this represents a significant challenge, since one would normally prefer to use a single ADC with fixed sampling rate to sample all possible signals of interest.
     A solution to this problem was proposed as early as 1953 by Kohlenberg, who showed that Nyquist rate sampling can be achieved by using time- interleaved sampling, where two sub-ADCs sample the signal at a rate ?s/2 each, but with a relative timing offset d (such that 0 < d < 1 if the offset is measured relative to the sub-ADC sampling period). However, certain offsets are forbidden, since for example d = 1/2 would result in a uniform overall ADC. In this presentation, a method will be described to simultaneously sample and demodulate the bandpass signal of interest. The sampled complex envelope of the bandpass signal is computed entirely in the DSP domain by passing the sub-ADC samples through digital FIR filters, followed by a digital demodulation operation. However, as the quality factor (ratio of the carrier frequency ?c to the signal bandwidth B) of the front-end selection filter increases, the performance of the envelope computation method becomes progressively more sensitive to mismatches between the nominal offset d0 and actual offset d of the two sampling channels. To overcome this problem, a blind calibration technique to estimate and correct mismatches, is presented.

Copy Of Presentation


Photo of Prof B. Levy Prof. Bernard Levy received the diploma of Ingenieur Civil des Mines from the Ecole Nationale Superieure des Mines, Paris, France, in 1974, and the Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, in 1979.
     From July 1979 to June 1987, he was Assistant and then Associate Professor in the Department of Electrical Engineering and Computer Science at M.I.T. Since July 1987, he has been with the University of California at Davis (UC Davis), where he is a Professor of Electrical Engineering and a member of the Graduate Group in Applied Mathematics. He served as Chair of the Department of Electrical and Computer Engineering at UC Davis from 1996 to 2000. He was a Visiting Scientist at the Institut de Recherche en Informatique et Systemes Aleatoires (IRISA), Rennes, France from January to July 1993, and at the Institut National de Recherche en Informatique et Automatique (INRIA), Rocquencourt, France, from September to December 2001. His research interests are in statistical signal processing, estimation, detection, and multidimensional signal processing.
     He has been an Associate Editor of Signal Processing since March 2011. He served earlier as Associate Editor of the IEEE Transactions on Circuits and Systems I from 2006 to 2007, of the IEEE Transactions on Circuits and Systems II from 2004 to 2005, and of the EURASIP Journal on Applied Signal Processing from 2005 to 2006. He was a member of the Image and Multidimensional Signal Processing technical committee of the IEEE Signal Processing Society from 1992 to 1998. He is a Fellow of the IEEE, and a member of SIAM and the Acoustical Society of America.



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