One-bit quantization converts real-valued signals into binary sequences, offering significant hardware simplification advantageous for low-power and real-time applications. However, it introduces considerable quantization noise, challenging signal quality, especially for signals with spectral complexity. Traditional methods like Sigma-Delta Quantization (SDQ) effectively mitigate quantization noise for lowpass signals by pushing it outside the signal bandwidth, but struggle with more complex spectral requirements.We present a block-based optimization framework (OBBQ) for one-bit quantization, which divides signals into smaller blocks, and optimizes each block independently. By formulating quantization as an optimization problem, our method enhances signal reconstruction accuracy and enables precise noise shaping adaptable to complex spectral content. It outperforms traditional SDQ methods in both flexibility and fidelity, facilitating real-time processing across various desired frequency domains.

In many industrial fields, one-bit signals play an important role, such as improving the operational efficiency in a wide range of applications. This paper introduces a mapping function $\mathcal{F}(\cdot)$ that converts real-valued discrete-time signals into two-level discrete-time one-bit signals, i.e., one-bit signals. By introducing an error function, we can evaluate the quality of the mapping and can introduce different optimization strategies to minimize the error. Mathematical analysis and numerical simulations demonstrate that the optimization approach leads to specific characteristics of the quantization. The well-known Sigma-Delta modulator, for example, turns out to be a special case of the introduced optimization. The new approach has the potential to introduce new ways of one-bit quantization, which can be tailored to specific applications.

A two-stage difference-based estimation method is presented to extract the timing skew of each sub-ADC in time interleaved analog to digital converters (TIADCs). Compared with the previous techniques, such as the correlation-based method, the main advantage is that it greatly reduces the number of multipliers and does not require digital filters. Simulation results of a four-channel TI-ADC behavioral model and experimental results from a commercial 12-bit 3.6-GS/s TI- ADC demonstrate the effectiveness and superiority of the proposed estimation method.

We present an analytical model of the joint linearity-efficiency behavior of radio frequency power amplifiers. The model is derived by Fourier series analysis of a generic amplifier circuit including both strong nonlinearity due to current-clipping as well as weak nonlinearity due to transconductance variation. By selection of the biasing point, common amplifier classes like class A, class B and class AB can be modeled. For numerical evaluation, the model reduces to two lookup-tables, which makes it well suited for high-level system simulations. In an application example we demonstrate how the model can be used to simulate the error-vector-magnitude and the average efficiency for specific single-carrier and multi-carrier modulation schemes.

Behavioral modeling of nonlinear passband systems like radio frequency power amplifiers is mainly based on polynomial baseband models. Motivated by the convolution property of the Fourier transform applied to passband signals, it is common practice to include only odd-order terms in these models. Experimental results show, however, that significant improvements can be achieved by also including even-order terms. In this paper, the fundamental relationship of even-order terms in polynomial passband and baseband models is analyzed, providing a theoretical foundation for the improved modeling accuracy of polynomial baseband models with even-order terms.

We present a new approach to identify the parameters of a given digital predistortion (DPD) structure for power amplifier (PA) linearization. Traditional methods optimize a single objective, typically the time-domain mean squared error. We propose to use a multi-objective optimization algorithm to jointly optimize the in-band and out-of-band performance as quantified by the respective metrics defined in the particular communication standard. Our constrained approach allows for checking standard-compliance at the time of DPD identification. Furthermore, the DPD model is not required to be linear in the parameters. We exemplify our approach with a WLAN simulation using a PA model at low back-off. By jointly optimizing the error vector magnitude (EVM) and spectral mask margin, we achieve significantly better results than the widely-used indirect learning architecture for the same memory polynomial DPD structure.

This paper presents a systematic approach to block processing with iterative correction filters for time-interleaved analog-to-digital converters (TI-ADCs). TI-ADCs consist of several channels and can significantly increase the achievable sampling rate, but suffer from mismatches among the channels. Iterative digital correction filters are a general approach to mitigate the impact of mismatches in TI-ADCs. To reduce the requirements on the digital hardware, we introduce block processing for such filters. To this end, the transformation of a single-input single-output linear time-varying (LTV) finite impulse response filter into a multiple-input multiple-output LTV filter is described as a design equation and applied to two representative iterative correction structures from the literature. Finally, the beneficial properties and advantages of the transformation are high-lighted.

A mathematical framework for analytical description of multilevel carrier-based pulse-width modulation (PWM) is presented. The framework does not make any assumptions on the input signal and is able to model any configuration of periodic, piecewise-linear carrier signals, specified by two line-segments. By using the framework it is shown that analytical equations can be obtained for two practically relevant multilevel PWM schemes. The derived equations simplify spectral analysis, which is exemplified by numerical simulations.

The burst-mode transmitter has been proposed as an efficiency enhancement technique for signals with high peak-to-average-power ratios (PAPRs), where appropriate modulation schemes such as pulse-width modulation (PWM) are used to generate a switching signal to drive the radio frequency (RF) power amplifier (PA). Ideally, a PWM signal is of infinite bandwidth, however, high-frequency spectral components are attenuated, e.g., by the bandlimitation of the PA matching network or the PWM circuit itself. Bandlimitation introduces ripples in the signal amplitude, which might reduce the PA efficiency in burst-mode operation. In this paper, we show that a bandlimited PWM signal does not necessarily degrade the overall transmitter efficiency because of the higher coding efficiency. The coding efficiency of bandlimited PWM signals, i.e., PWM signals with a finite number of harmonics, is derived analytically and verified by measurements. Additionally, from the measurements, we exemplarily determine the number of harmonics for bandlimited PWM signals with the best transmitter efficiency-linearity trade-off, and therefore demonstrate the excellence of bandlimited PWM for burst-mode transmitters in terms of transmitter efficiency as well as transmission signal quality.

Among other goals, multilevel burst-mode radio frequency (RF) transmitters have to achieve two main objectives: high efficiency, and good transmission signal quality. Both of these goals depend, to a large extent, on the driving signal modulator, which can, for example, be a digital pulse-width modulator. However, conventional digital pulse-width modulation (PWM) contains aliasing distortion that prevents achieving satisfying transmission signal quality. In this paper, an aliasing-free digital multilevel PWM method is introduced that allows for achieving good transmission signal quality, while at the same time offering the potential of reaching a coding efficiency of 100%. The mathematical equations for aliasing-free digital PWM are extended in a way that makes them suitable for the use in multilevel burst-mode RF transmitters. It is then shown how the aliasing-free multilevel PWM method can be used to achieve 100% coding efficiency. Simulations demonstrate the performance capabilities of the proposed PWM method.

This paper investigates the adaptive compensation of frequency response mismatches in an M-channel time-interleaved analog-to-digital converter (TI-ADC) using an extra low-resolution ADC and a time-varying FIR filter. The introduced compensation structure may be used to compensate any linear frequency response mismatches including time skew mismatches. The coefficients of the time-varying filter are adapted using the least-mean square (LMS) algorithm. The performance of the proposed compensation structure is demonstrated through numerical simulations.

The first stage of the signal processing chain in a Global Positioning System (GPS) receiver is the acquisition, which provides for a desired satellite coarse code phase and Doppler frequency estimates to subsequent stages. Thus, acquisition is a two-dimensional search, implemented as demodulation and non-coherent correlation. For a certain Doppler estimate, software-defined GPS receivers typically compute the correlation for all time lags in parallel. One way to detect the presence of a signal is by comparing the ratio between the largest and the second largest correlation peak against a threshold. For this type of receivers, the detection and false alarm probabilities are derived. Interestingly, the false alarm probability is independent of the noise power spectral density, which allows a fixed threshold setting. The analytic results are verified by a series of simulations.

An overview of digital enhancement techniques for analog circuits is presented. Recent research suggests that the high density and low energy of digital circuits can be leveraged to enable a new generation of interface electronics that is based on minimal precision, low complexity analog blocks. Today, examples of enhancement schemes can be found in diverse applications and include nonlinearity compensation of ADCs, predistortion of power amplifiers and mismatch calibration in radio receivers. Since it is often difficult to identify commonalities among these different, but conceptually related schemes, this tutorial paper aims to provide a unified and system-oriented perspective of the field.

Parallel time-interleaved analog-to-digital converters (TI-ADCs) are an attractive architecture to realize low-power and high-speed data conversion. As a drawback of such converters, mismatches between the channels impair their performance, e.g., the spurious free dynamic range (SFDR). One characteristic that varies among all channels is the magnitude response. The authors proposed a method to compensate magnitude response mismatches in two-channel TI-ADCs. In this paper the authors extend this method to an arbitrary number of channels, discuss a possible implementation, and evaluate its performance. For an M-channel TI-ADC the compensation method requires (M-1) linear-phase FIR filters with relatively short tap sizes and (M-1) multipliers to modulate the filter output. Simulations confirm the effectiveness of the proposed method.

We discuss time-interleaved analog-to-digital converters (ADCs) as a prime example of merging analog and digital signal processing. A time-interleaved ADC (TI-ADC) consists of M parallel channel ADCs that alternately take samples from the input signal, where the sampling rate can be increased by the number of channels compared to a single channel. We recall the advantages of time interleaving and investigate the problems involved. In particular, we explain the error behavior of mismatches among the channels, which distort the output signal and reduce the system performance significantly, and provide a concise framework for dealing with them. Based on this analysis, we review the principle possibilities of calibrating TI-ADCs, where we point out the necessities and advantages of digital enhancement. To this end, we discuss open issues of channel mismatch identification as well as channel mismatch correction