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Algorithms for Nonuniform Bandpass Sampling in Radio Receiver
KTH, Superseded Departments, Microelectronics and Information Technology, IMIT.
KTH, Superseded Departments, Microelectronics and Information Technology, IMIT.
2003 (English)In: PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL I - ANALOG CIRCUITS AND SIGNAL PROCESSING, 2003, 1-4 p.Conference paper, Published paper (Refereed)
Abstract [en]

Bandpass Sampling (BPS) technique enables one to have an interface between IF stage and ADC in a radio receiver. Nonuniform BPS has the potential to suppress aliasing without care of the information band position of a modulated signal. However, a signal cannot be reconstructed from its nonuniform samples by using only an ideal lowpass filter. In this paper, a filter is, generalized to a reconstruction algorithm (RA). Six different algorithms for reconstructing a signal from its nonuniform samples are summarized. A general reconstruction formula in terms of a basis-kernel (BK) function is used to describe the algorithms. Finally, with regard to. the application of radio communications, accuracy of reconstruction, computational complexity and hardware implementation are shown and compared for these algorithms.

Place, publisher, year, edition, pages
2003. 1-4 p.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-5849OAI: oai:DiVA.org:kth-5849DiVA: diva2:10365
Conference
IEEE International Symposium on Circuits and Systems BANGKOK, THAILAND, MAY 25-28, 2003
Note
QC 20100921Available from: 2006-05-30 Created: 2006-05-30 Last updated: 2010-09-21Bibliographically approved
In thesis
1. Generalized Bandpass Sampling Receivers for Software Defined Radio
Open this publication in new window or tab >>Generalized Bandpass Sampling Receivers for Software Defined Radio
2006 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Based on different sampling theorem, for example classic Shannon’s sampling theorem and Papoulis’ generalized sampling theorem, signals are processed by the sampling devices without loss of information. As an interface between radio receiver front-ends and digital signal processing blocks, sampling devices play a dominant role in digital radio communications.

Under the concept of Software Defined Radio (SDR), radio systems are going through the second evolution that mixes analog, digital and software technologies in modern radio designs. One design goal of SDR is to put the A/D converter as close as possible to the antenna. BandPass Sampling (BPS) enables one to have an interface between the RF or the higher IF signal and the A/D converter, and it might be a solution to SDR. However, three sources of performance degradation present in BPS systems, harmful signal spectral overlapping, noise aliasing and sampling timing jitter, hinder the conventional BPS theory from practical circuit implementations.

In this thesis work, Generalized Quadrature BandPass Sampling (GQBPS) is first invented and comprehensively studied with focus on the noise aliasing problem. GQBPS consists of both BPS and FIR filtering that can use either real or complex coefficients. By well-designed FIR filtering, GQBPS can also perform frequency down-conversion in addition to noise aliasing reduction. GQBPS is a nonuniform sampling method in most cases. With respect to real circuit implementations, uniform sampling is easier to be realized compared to nonuniform sampling. GQBPS has been also extended to Generalized Uniform BandPass Sampling (GUBPS). GUBPS shares the same property of noise aliasing suppression as GQBPS besides that the samples are uniformly spaced. Due to the moving average operation of FIR filtering, the effect of sampling jitter is also reduced to a certain degree in GQBPS and GUBPS. By choosing a suitable sampling rate, harmful signal spectral overlapping can be avoided. Due to the property of quadrature sampling, the “self image” problem caused by I/Q mismatches is eliminated. Comprehensive theoretical analyses and program simulations on GQBPS and GUBPS have been done based on a general mathematic model. Circuit architecture to implementing GUBPS in Switched-Capacitor circuit technique has been proposed and analyzed. To improve the selectivity at the sampling output, FIR filtering is extended by adding a 1st order complex IIR filter in the implementation.

GQBPS and GUBPS operate in voltage-mode. Besides voltage sampling, BPS can also be realized by charge sampling in current-mode. Most other research groups in this area are focusing on bandpass charge sampling. However, the theoretical analysis shows that our GQBPS and GUBPS in voltage mode are more efficient to suppress noise aliasing as compared to bandpass charge sampling with embedded filtering. The aliasing bands of sampled-data spectrum are always weighted by continuous-frequency factors for bandpass charge sampling with embedded filtering while discrete-frequency factors for GQBPS and GUBPS. The transmission zeros of intrinsic filtering will eliminate the corresponding whole aliasing bands of both signal and noise in GQBPS and GUBPS, while it will only cause notches at a limited set of frequencies in bandpass charge sampling. In addition, charge sampling performs an intrinsic continuous-time sinc function that always includes lowpass filtering. This is a drawback for a bandpass input signal.

Place, publisher, year, edition, pages
Stockholm: KTH, 2006. xvi, 104 p.
Series
Trita-ICT-ECS AVH, ISSN 1653-6363 ; 06:01
Keyword
Radio receivers, Software Defined Radio (SDR), uniform/nonuniform sampling, reconstruction, bandpass sampling, noise aliasing, sampling jitter, generalized bandpass sampling, complex signal processing, complex FIR and IIR filter design, Switched-Capacitor (SC) circuit
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-4009 (URN)91-7178-350-4 (ISBN)
Public defence
2006-06-09, Sal E, KTH-Forum, Isafjordsgatan 39, Kista, 14:00
Opponent
Supervisors
Note
QC 20100921Available from: 2006-05-30 Created: 2006-05-30 Last updated: 2010-09-21Bibliographically approved

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