A formulation based on multirate theory is introduced for analog-to-digital converters using parallel sigma-delta modulators in conjunction with modulation sequences. It is shown how the formulation can be used to analyze a system's sensitivity to channel mismatch errors by means of circulant and pseudo-circulant matrices. It is demonstrated how the time-interleaved-modulated (TIM), Hadamard-modulated (HM) and frequency-band decomposition (FBD) converters can be viewed as special cases of this more general description, and it is shown why the TIM and HM ADCs are sensitive to channel mismatch errors, whereas the FBD ADCs are not.
A general formulation based on multirate filterbanktheory for analog-to-digital converters using parallel sigmadeltamodulators in conjunction with modulation sequences ispresented. The time-interleaved modulators (TIMs), Hadamard modulators(HMs), and frequency-band decomposition modulators(FBDMs) can be viewed as special cases of the proposeddescription. The usefulness of the formulation stems from itsability to analyze a system's sensitivity to aliasing due to channel mismatch and modulation sequence level errors. BothNyquist-rate and oversampled systems are considered, and it isshown how the matching requirements between channels canbe reduced for oversampled systems. The new formulation isuseful also for the derivation of new modulation schemes, andan example is given of how it can be used in this context.
In this paper we examine the relation between signal-to-noise-ratio, oversampling ratio, transition bandwidth, and filter order for some commonly used sigma-delta-modulators and corresponding decimation filters. The decimation filters are equi-ripple finite impulse response filters and it is demonstrated that, for any given filter order, there exists an optimum choice of the stopband ripple and stopband edge which minimizes the signal-to-noise-ratio degradation.
This paper introduces multimode transmultiplexers (TMUXs) in which the Farrow structure realizes the polyphase components of general lowpass interpolation/decimation filters. As various lowpass filters are obtained by one set of common Farrow subfilters, only one offline filter design enables us to cover different integer sampling rate conversion (SRC) ratios. A model of general rational SRC is also constructed where the same fixed subfilters perform rational SRC. These two SRC schemes are then used to construct multimode TMUXs. Efficient implementation structures are introduced and different filter design techniques such as minimax and least-squares (LS) are discussed. By means of simulation results, it is shown that the performance of the transmultiplexer (TMUX) depends on the ripples of the filters. With the error vector magnitude (EVM) as the performance metric, the LS method has a superiority over the minimax approach.
This paper introduces a multi-mode transmultiplexer (TMUX) consisting of Farrow-based variable integer sampling rate conversion (SRC) blocks. The polyphase components of general interpolation/ decimation filters are realized by the Farrow structure making it possible to achieve different linear-phase finite-length impulse response (FIR) lowpass filters at the cost of a fixed set of subfilters and adjustable fractional delay values. Simultaneous design of the subfilters, to achieve overall approximately Nyquist (Mth-band) filters, are treated in this paper. By means of an example, it is shown that the subfilters can be designed so that for any desired range of integer SRC ratios, the TMUX can approximate perfect recovery as close as desired.
This paper introduces a multimode transmultiplexer (TMUX) structure capable of generating a large set of user-bandwidths and center frequencies. The structure utilizes fixed integer sampling rate conversion (SRC) blocks, Farrow-based variable interpolation and decimation structures, and variable frequency shifters. A main advantage of this TMUX is that it needs only one filter design beforehand. Specifically, the filters in the fixed integer SRC blocks as well as the subfilters of the Farrow structure are designed only once. Then, all possible combinations of bandwidths and center frequencies are obtained by properly adjusting the variable delay parameter of the Farrow-based filters and the variable parameters of the frequency shifters. The paper includes examples for demonstration. It also shows that, using the rational SRC equivalent of the Farrow-based filters, the TMUX can be described in terms of conventional multirate building blocks which may be useful in further analysis of the overall system.
In this paper, we introduce a non-uniform transmultiplexer capable of generating arbitrary-bandwidth user signals. The transmultiplexer consists of linear-phase finite-length impulse response (FIR) filters and Farrow structures for arbitrary-rate interpolation/decimation. By applying the FIR rational sampling rate conversion (SRC) equivalent of the Farrow structure, we model the behavior of the multiplexer and derive the conditions under which the system can approximate perfect reconstruction. Futhermore, we illustrate the functionality of the proposed transmultiplexer and we analyze the performance and functionality of a flexible frequency-band reallocation (FFBR) network using this transmultiplexer.
This paper discusses a new approach for implementing flexible frequency-band reallocation (FFBR) networks for bentpipe satellite payloads which are based on variable oversampled complex-modulated filter banks (FBs). We consider two alternatives to process real signals using real input/output and complex input/output FFBR networks (or simply real and complex FFBR networks, respectively). It is shown that the real case has a lower overall number of processing units, i.e., adders and multipliers, compared to its complex counterpart. In addition, the real system eliminates the need for two Hilbert transformers, further reducing the arithmetic complexity. An analysis of the computational workload shows that the real case has a smaller rate of increase in the arithmetic complexity with respect to the prototype filter order and number of FB channels. This makes the real case suitable for systems with a large number of users. Furthermore, in the complex case, a high efficiency in FBR comes at the expense of high-order Hilbert transformers; thus, trade-offs are necessary. Finally, the performance of the two alternatives based on the error vector magnitude (EVM) for a 16-quadrature amplitude modulation (QAM) signal is presented.
In this paper, alow-complexity approach to implement a class of flexible frequency-band reallocation (FFBR) multi-input multi-output (MIMO) networks, which use variable oversampled complex-modulated filter banks, is introduced. Two alternatives in processing real signals using real input/output and complex input/output FFBR networks (or simply, real and complex FFBR networks, respectively) are considered. It is shown that to process each sample, the real case requires less number of real operations compared to its complex counterpart. Furthermore, the real case has a smaller growth rate in the number of real operations with respect to the prototype filter order. In addition, the real FFBR network eliminates the need for two Hilbert transformers whereas in the complex FFBR case, to achieve high efficiency in FBR, there is a need for high-order Hilbert transformers.
This paper discusses the complexity trend in different finite length impulse response (FIR) filter structures when using multiplierless (shift-and-add) realization. We derive the total number of adders required by the transposed direct form, polyphase, and reduced-complexity polyphase FIR filter structures. A comparison of the arithmetic complexities of these structures for different filter characteristics is performed. The simulation results show that considering both the high level structure and the algorithm used to realize the subfilters gives a more accurate measure of complexity comparison between different FIR filter structures.
This paper discusses some issues related to the filter design in a class of multimode transmultiplexers (TMUXs). These TMUXs cover a large set of frequency division multiplexed (FDM) scenarios with simple reconfigurations. The reconfiguration is performed by changing the values of some multipliers. The paper outlines a direct filter design to decrease the level of inter-symbol and inter-carrier interference by the use of time-varying periodic filters. These time-varying periodic filters are derived from the known FDM scenarios and they are included as additional constraints in the filter design. Both minimax and constrained least-squares approaches are treated and it is shown that by including the additional constraints, the level of the TMUX noise can be reduced. This results in a better approximation of perfect reconstruction and makes the filter design direct.
This paper introduces reconfigurable nonuniform transmultiplexers (TMUXs) based on uniform modulated filter banks (FBs). Polyphase components, of any user, are processed by a number of synthesis FB and analysis FB branches of a uniform TMUX. One branch, of the TMUX, represents one granularity band and any user occupies integer multiples of a granularity band. By adjusting the number of branches, assigned to each user, a nonuniform TMUX is obtained. This only requires adjustable commutators which add no extra arithmetic complexity. The application of both cosine modulated and modified discrete Fourier transform FBs are considered and the formulations related to the appropriate choice of parameters are outlined. Examples are provided for illustration.
This paper introduces reconfigurable nonuniform transmultiplexers (TMUXs) based on fixed uniform modulated filter banks (FBs). The TMUXs use parallel processing where polyphase components, of any user, are processed by a number of synthesis FB and analysis FB branches. One branch represents one granularity band, and any user can occupy integer multiples of a granularity band. The proposed TMUX also requires adjustable commutators so that any user occupies any portion of the frequency spectrum. The location and width of this portion can be modified without additional arithmetic complexity or filter redesign. This paper considers both cosine modulated and modified discrete Fourier transform FBs. It discusses the filter design, TMUX realization, and the parameter selection. It is shown that one can indeed decrease the arithmetic complexity by proper choice of system parameters. For the critically sampled case and if the number of channels is higher than necessary, we can reduce the arithmetic complexity. In case of an oversampled system, the arithmetic complexity can be reduced by proper choice of the number of channels and the roll-off factor of the prototype filter. The proposed TMUX is compared to existing reconfigurable TMUXs, and examples are provided for illustration.
This paper discusses two approaches for the baseband processing part of cognitive radios. These approaches can be used depending on the availability of (i) a composite signal comprising several user signals or, (ii) the individual user signals. The aim is to introduce solutions which can support different bandwidths and center frequencies for a large set of users and at the cost of simple modifications on the same hardware platform. Such structures have previously been used for satellite-based communication systems and the paper aims to outline their possible applications in the context of cognitive radios. For this purpose, dynamic frequencyband allocation (DFBA) and reallocation (DFBR) structures based on multirate building blocks are introduced and their reconfigurability issues with respect to the required reconfigurability measures in cognitive radios are discussed.
This paper proposes a systematic method to design adjustable fractional delay (FD) filters using the Farrow structure. The Farrow structure has even-order subfilters and the maximum magnitude approximation error determines the number of these subfilters. In the Farrow structure, different powers of the FD value are multiplied by the subfilters. As both the FD value and its powers are smaller than unity, they are considered as weighting functions. The approximation error for each subfilter can then increase in proportion to the power of the FD value. With the proposed design method, the first Farrow subfilter is a pure delay whereas the remaining subfilters are digital differentiators. Examples illustrate the proposed design method and comparison to some earlier designs shows an average reduction of 20% in arithmetic complexity.
A class of M-channel tree-structured digital filter banks is considered with half-band IIR analysis filters and FIR synthesis filters. The filter banks approximate perfect reconstruction with an exact linear phase response and zero aliasing. This particular configuration has a very low-complexity analysis filter bank. In this paper we address the problem of minimizing the synthesis filter complexity, given the minimum-complexity analysis filters. The filter banks are designed using linear and nonlinear programming
A class of tree-structured octave-band digital filter banks is introduced. The filter banks make use of half-band IIR filters in the analysis bank and FIR filters in the synthesis bank which results in very low-complexity analysis filters. Further, the overall complexity is lower than, or comparable to, that of conventional filter banks. The overall filter banks approximate perfect reconstruction in the following sense. The distortion function is a linear-phase function approximating one in magnitude whereas the aliasing terms approximate zero. The filter banks are designed using linear and nonlinear programming. Design examples are included demonstrating the properties of the new filter banks
This paper introduces new tree-structured uniform-band and octave-band digital filter banks (FBs). These FBs make use of half-band IIR filters in the analysis FBs and FIR filters in the synthesis FBs. The resulting FBs are asymmetric in the sense that the analysis FB has a very low arithmetic complexity whereas that in the synthesis FB is higher. However, compared with other asymmetric FBs, the proposed ones have in many cases a lower overall arithmetic complexity and delay. The proposed FBs have magnitude distortion but no phase distortion, further, the aliasing components are either zero (uniform-band case) or approximately zero (octave-band case). The FBs are designed using linear and nonlinear programming. Design examples are included demonstrating the properties of the proposed filters banks. ⌐ 2003 Published by Elsevier B.V.
A new class of two-channel IIR/FIR filter banks was introduced by the authors in 2000 with half-band IIR analysis filters and FIR synthesis filters. This type of filter bank features very low-complexity analysis filters and simultaneously a low overall complexity. In this paper, we consider finite-wordlength effects of these filter banks
A polynomial-based division algorithm and a corresponding hardware structure are proposed. The proposed algorithm is shown to be competitive to other conventional algorithms like the Newton-Raphson algorithm for up to about 32 bits accuracy. For example, using Newton-Raphson with less than 12 bits accuracy of the initial approximation, requires 33% more general multiplications than the proposed algorithm, in order to achieve 24 bits accuracy.
This paper introduces a least-squares filter design technique for the compensation of frequency response mismatch errors in M-channel time-interleaved analog-to-digital converters. The overall compensation system is designed by determining M filter impulse responses analytically through M separate matrix inversions. The proposed technique offers an alternative to least-squares techniques that determine all filters simultaneously. Several design examples are included for illustration.
An important issue in the next-generation satellite-based communication systems is the satellite on-board reallocation of information which calls for digital flexible frequency-band reallocation (FFBR) networks. This paper introduces a new class of FFBR networks based on variable oversampled complex-modulated filter banks (FBs). The new class can outperform previously existing ones when flexibility, low complexity and inherent parallelism, perfect frequency-band reallocation, and simplicity are considered simultaneously.
A crucial issue in the next-generation satellite-based communication systems is the satellite on-board reallocation of information which requires digital flexible frequency-band reallocation (FBR) networks. This paper introduces a new class of flexible FBR networks based on variable oversampled complex-modulated filter banks (FBs). The new class can outperform the previously existing ones when all the aspects flexibility, low complexity and inherent parallelism, near-perfect frequency-band reallocation, and simplicity are considered simultaneously.
This paper considers the design of linear-phase FIR digital filters that have a variable bandwidth whereas the phase response is fixed. For this purpose, we employ a structure in which the overall transfer function is a weighted linear combination of fixed subfilters and where the weights are directly determined by the bandwidth. We introduce a linear programming design technique which generates globally optimal overall filters in the minimax (Chebyshev) sense. Further, both the cases where the subfilters are of equal and different orders, respectively, are treated. Earlier, only the equal-order case has been considered.
Recently, a particular structure for linear-phase finite-impulse response (FIR) filters with a variable bandwidth has received attention. In this structure, the overall transfer function is a weighted linear combination of fixed subfilters, with the weights being directly determined by the bandwidth. An advantage of this structure is that there are only a few adjustable parameters (weights), which results in a simple updating routine. However, in this paper, it is demonstrated that the use of a number of fixed regular overdesigned filters, each taking care of a part of the frequency region, in fact results in a lower overall arithmetic complexity. The price to pay is an increased group and phase delay.
This brief considers minimax design of adjustable fractional delay finite-impulse response (FIR) filters. We employ a filter structure that, in the paper by Vesma and SaramΣki in 1997, is referred to as the modified Farrow structure which makes use of a number of linear-phase FIR subfilters. Previously, only the cases where all subfilters are of equal orders have been considered. In this brief, we propose a design technique that in general produces subfilters of different orders which results in a lower overall arithmetic complexity. Design examples are included, illustrating the efficiency of the proposed design technique.
This paper introduces a system for reconstructing a class of nonuniformly sampled and decimated bandlimited signals. This system makes use of a number of real-valued multipliers and one digital filter. One advantage of the new system is that it easily can achieve perfect reconstruction in the whole frequency band. A drawback is that it requires that the signals be oversampled by a factor that exceeds the theoretical value.
This paper considers the problem of reconstructing a class of nonuniformly sampled bandlimited signals of which a special case occurs in, e.g., time-interleaved analog-to-digital converter (ADC) systems due to time-skew errors. To this end, we propose a synthesis system composed of digital fractional delay filters. The overall system (i.e., nonuniform sampling and the proposed synthesis system) can be viewed as a generalization of time-interleaved ADC systems to which the former reduces as a special case. Compared with existing reconstruction techniques, our method has major advantages from an implementation point of view. To be precise, 1) we can perform the reconstruction as well as desired (in a certain sense) by properly designing the digital fractional delay filters, and 2) if properly implemented, the fractional delay filters need not be redesigned in case the time skews are changed. The price to pay for these attractive features is that we need to use a slight oversampling. It should be stressed, however, that the oversampling factor is less than two as compared with the Nyquist rate. The paper includes error and quantization noise analysis. The former is useful in the analysis of the quantization noise and when designing practical fractional delay filters approximating the ideal filters.
This paper deals with reconstruction of nonuniformly sampledbandlimited continuous-time signals using time-varyingdiscrete-time finite-length impulse response (FIR) filters. Themain theme of the paper is to show how a slight oversamplingshould be utilized for designing the reconstruction filters in aproper manner. Based on a time-frequency function, it is shownthat the reconstruction problem can be posed as one that resemblesan ordinary filter design problem, both for deterministic signalsand random processes. From this fact, an analytic least-squaredesign technique is then derived. Furthermore, for an importantspecial case, corresponding to periodic nonuniform sampling, it isshown that the reconstruction problem alternatively can be posedas a filter bank design problem, thus with requirements on adistortion transfer function and a number of aliasing transferfunctions. This eases the design and offers alternative practicaldesign methods as discussed in the paper. Several design examplesare included that illustrate the benefits of the proposed designtechniques over previously existing techniques.
This paper considers the problem of reconstructing nonuniformly sampled bandlimited signals using a synthesis system composed of digital fractional delay filters. The overall system can be viewed as a generalization of time-interleaved ADC systems. By generalizing these systems, it is possible to eliminate the errors that are introduced in practice due to time-skew errors
This paper proposes polynomial impulse response finite-impulse response filters for reconstruction of two-periodic nonuniformly sampled signals. The foremost advantages of using these reconstruction filters are that on-line filter design thereby is avoided and subfilters with fixed dedicated multipliers can be employed in an implementation. The overall implementation cost can in this way be reduced substantially in applications where the sampling pattern changes from time to time. The paper presents two different design techniques that yield optimum filters in the least-squares and minimax senses, respectively. Design examples are included that illustrate the benefits of the proposed filters. © 2007 IEEE.
This paper introduces multivariate polynomial impulse response time-varying FIR filters for reconstruction of M-periodic nonuniformly sampled signals. The main advantages of these reconstruction filters are that 1) they do not require on-line filter design, and 2) most of their multipliers are fixed and can thus be implemented using low-cost dedicated multiplier elements. This is in contrast to existing filters that require on-line design as well as many general multipliers in the implementation. By using the proposed filters, the overall implementation cost may therefore be reduced in applications where the sampling pattern changes now and then. Design examples are included demonstrating the usefulness of the proposed filters.
This paper introduces polynomial impulse response time-varying FIR filters for reconstruction of two-periodic nonuniformly sampled signals. The main advantages of using these reconstruction filters are that on-line filter design is avoided, and filters with fixed dedicated multipliers can be used in an implementation (except for a few general multipliers). This is in contrast to existing filters that require on-line design as well as general multipliers in the implementation. By using the proposed filters, the overall implementation cost can therefore be reduced dramatically in applications where the sampling pattern changes now and then.
This paper considers the design of digital linear-phase finite-length impulse response (FIR) filters that have adjustable bandwidth(s) whereas the phase response is fixed. For this purpose, a structure is employed in which the overall transfer function is a weighted linear combination of fixed subfiltcrs and where the weights are directly determined by the bandwidth(s). Minimax design techniques are introduced which generate globally optimal overall filters in the minimax (Chebyshev) sense over a whole set of filter specifications. The paper also introduces a new structure for bandstop and bandpass filters with individually adjustable upper and lower band edges, and with a substantially lower arithmetic complexity compared to structures that make use of two separate adjustable-bandwidth low-pass and high-pass filters in cascade or in parallel. Design examples are included in the paper. © 2006 IEEE.
Analog-to-digital converters (ADCs) making use of analog and digital filter banks have been proposed as a means to increase the performance of the analog-to-digital conversion. In this paper we consider the quantization noise in such filter banks. Basically, two different schemes are treated, namely single-rate and multirate filter bank ADCs. Further, both narrow-band and wide-band input signals are considered, The differences between these two ADC schemes and the single conventional ADC are pointed out
This paper introduces a class of two-channel hybrid analog and digital filter banks which find application in high-speed A/D conversion. The distortion caused by mismatch errors in time-interleaved A/D converters is attenuated using hybrid filter banks. The proposed class of filter banks satisfy perfect reconstruction within certain tolerances that can be controlled in the filter design. The filter design uses both linear and nonlinear programming
This paper introduces a class of hybrid analog/digital filter banks with approximately perfect magnitude reconstruction. The filter bank consists of analog analysis and digital synthesis filter banks. The analog analysis filters are formed as a sum and difference of two allpass subfilters, respectively, resulting in filters with low orders and few free parameters, which is advantageous from implementation and design points of view. The digital synthesis filters are odd-order linear-phase FIR filters with symmetric and anti-symmetric impulse responses, respectively. The filter design is performed by first optimizing the analog analysis filters. Then, with the analog filters fixed, optimum digital synthesis filters, in the minimax sense, are obtained with the aid of linear programming
A class of digital filter banks is introduced, in which the anal-ysis filters are half band IIR filters and the synthesis filters are FIR filters. The proposed filter bank satisfy approximately perfect reconstruction and has an exact linear phase. Further, it is suitable for applications where a very low complexity analysis filter bank is required. 1 INTRODUCTION This paper introduces a class of two-channel digital filter banks. This class belongs to the general class of two-channel maximally decimated filter banks shown in Fig. 1. It consists of an analysis filter bank, formed by the analysis filters H 0 (z) and H 1 (z), and a synthesis filter bank, formed by the synthesis filters G 0 (z) and G 1 (z). Downsamplers and upsamplers are present between the analysis and synthesis filter banks in order to reduce the computational workload. In the filter banks that have been proposed during the past decades, the analysis and synthesis filters have equal complexities [1], [2]. This holds true for both IIR and FIR filter banks. In this paper, we propose a filter bank in which the analy-sis filters are half-band IIR filters whereas the synthesis filters are FIR filters. The complexity of the analysis filter bank is then very low whereas that of the synthesis filter bank is higher. However, the overall complexity is comparable to that of conventional filter banks. Such filter banks are of interest in applications where it is important to have a very low com-plexity for the analysis filter bank, and where one can afford a higher complexity in the synthesis filter bank. One is mixed discrete-time and digital filter banks for A/D-conversion, where the analysis filters are discrete-time filters, such as SC-filters. Here filter banks are used to reduce the distortion caused by gain-and phase mismatch errors which is inherent in parallel A/D converters. Since it is more difficult to imple-ment high-resolution discrete-time filters than digital filters, it is essential to use low-order analysis filters. The proposed class of filter banks are approximately per-fect reconstruction filter banks. They have magnitude distor-tion, but no phase distortion. Further, the aliasing can be made either exactly zero or approximately zero. In this paper we only consider the case in which the analysis filters have low complexity. Naturally, it is possible to let the synthesis filters be the low-complexity filters by simply interchanging the analysis and synthesis filters.
In this paper a design procedure for 2-channel hybrid filter banks for use in high-speed A/D converters is proposed. By using minimax optimization, A/D converting systems consisting of an analog analysis filter bank and a digital synthesis filter bank are designed with the aid of bireciprocal lattice wave digital filters. Using hybrid filter banks the requirements on the A/D converters used in each channel are reduced. The performance of the resulting system when simultaneously introducing gain and phase errors due to mismatches between the A/D converters and sample time uncertainty in the sample-and-hold circuits, respectively, is analysed by means of the expected attenuation of the resulting aliasing components