Generalized Bandpass Sampling Receivers for Software Defined Radio

Based on different sampling theorem, for example classic Shannon’s sampling theo-rem and Papoulis’ generalized sampling theorem, signals are processed by the sam-pling devices without loss of information. As an interface between radio receiverfront-ends and digital signal processing blocks, sampling devices play a dominantrole in digital radio communications.Under the concept of Software Defined Radio (SDR), radio systems are goingthrough the second evolution that mixes analog, digital and software technologiesin modern radio designs. One design goal of SDR is to put the A/D converter asclose as possible to the antenna. BandPass Sampling (BPS) enables one to havean interface between the RF or the higher IF signal and the A/D converter, andit might be a solution to SDR. However, three sources of performance degradationpresent in BPS systems, harmful signal spectral overlapping, noise aliasing andsampling timing jitter, hinder the conventional BPS theory from practical circuitimplementations.In this thesis work, Generalized Quadrature BandPass Sampling (GQBPS) isfirst 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 complexcoefficients. By well-designed FIR filtering, GQBPS can also perform frequencydown-conversion in addition to noise aliasing reduction. GQBPS is a nonuniformsampling method in most cases. With respect to real circuit implementations, uni-form sampling is easier to be realized compared to nonuniform sampling. GQBPShas been also extended to Generalized Uniform BandPass Sampling (GUBPS).GUBPS shares the same property of noise aliasing suppression as GQBPS besidesthat the samples are uniformly spaced. Due to the moving average operation of FIRfiltering, the effect of sampling jitter is also reduced to a certain degree in GQBPSand GUBPS. By choosing a suitable sampling rate, harmful signal spectral overlap-ping can be avoided. Due to the property of quadrature sampling, the ”self-image”problem caused by I/Q mismatches is eliminated. Comprehensive theoretical anal-yses and program simulations on GQBPS and GUBPS have been done based ona general mathematic model. A circuit architecture to implementing GUBPS inSwitched-Capacitor circuit technique has been proposed and analyzed. To improvethe selectivity at the sampling output, FIR filtering is extended by adding a 1storder complex IIR filter in the implementation.iii GQBPS and GUBPS operate in voltage-mode. Besides voltage sampling, BPScan also be realized by charge sampling in current-mode. Most other researchgroups in this area are focusing on bandpass charge sampling. However, the theo-retical analysis shows that our GQBPS and GUBPS in voltage mode is more efficientto suppress noise aliasing as compared to bandpass charge sampling with embed-ded filtering. The aliasing bands of sampled-data spectrum are always weighted bycontinuous-frequency factors for bandpass charge sampling with embedded filteringwhile discrete-frequency factors for GQBPS and GUBPS. The transmission zerosof intrinsic filtering will eliminate the corresponding whole aliasing bands of bothsignal and noise in GQBPS and GUBPS, while it will only cause notches at a lim-ited set of frequencies in bandpass charge sampling. In addition, charge samplingperforms an intrinsic continuous-time sinc function that always includes lowpassfiltering. This is a drawback for a bandpass input signal.