An improved design of chip waveforms for band-limited DS-CDMA systems

This paper introduces an efficient and improved design of chip waveforms to minimize the multiple-access interference in band-limited direct-sequence code-division multiple-access (DS-CDMA) systems. For ease of implementation, the DS-CDMA system employs a time-limited chip waveform, whereas its band limitation is ensured by the low-pass filters at both the transmitter and receiver ends. The design uses sinusoids to synthesize the time-limited chip waveform so that the portion of its spectrum across the specified bandwidth is as flat as possible. It is shown that by using a simple series expansion (with only a few terms) the synthesized chip waveforms significantly outperform the spreading/despreading waveforms previously proposed, particularly for large values of the chip duration-bandwidth product.     

On the performance of band-limited asynchronous DS-CDMA over nakagami-m channels

In this paper we investigated the BER performance of DS-CDMA using various chip-waveforms, which include three time-limited chip-waveforms and two band-limited chip-waveforms. Closed-form formulae were derived for evaluating the achievable bit-error rate performance with the aid of the standard Gaussian approximation, when communicating over a Nakagami-m channel. The time-limited waveforms impose a low implementational complexity, since they maybe over sampled and read from a look-up table. However, they are outperformed by the frequency-domain raised-cosine waveform as well as the optimum waveform specifically designed by Cho and Lehnert for achieving the lowest possible bit error rate     

An optimal training signal structure for frequency-offset estimation

This paper addresses an optimal training-signal design for frequency-offset estimation. Based on minimizing the Cramer-Rao lower bound for frequency-offset estimation with constraints on the peak and the total training signal energies, and the training block length, the optimal training-signal structure is developed. An approximate version of the optimal training-signal structure is proposed, which has practically the same performance as the optimal one, and provides convenience in training-signal generation and estimator derivation. Two robust reduced-complexity frequency-offset estimation methods for the proposed training structures are presented. In order to handle larger frequency offsets, modified training-signal structures are proposed. Frequency-offset estimation methods suitable for these training signals are also derived, based on the best linear unbiased estimation principle. Analytical and simulation results show that the proposed training-signal structures improve the estimation performance significantly.     

Transmit signal design for optimal estimation of correlated MIMO channels

We address optimal estimation of correlated multiple-input multiple-output (MIMO) channels using pilot signals, assuming knowledge of the second-order channel statistics at the transmitter. Assuming a block fading channel model and minimum mean square error (MMSE) estimation at the receiver, we design the transmitted signal to optimize two criteria: MMSE and the conditional mutual information between the MIMO channel and the received signal. Our analysis is based on the recently proposed virtual channel representation, which corresponds to beamforming in fixed virtual directions and exposes the structure and the true degrees of freedom in the correlated channel. However, our design framework is applicable to more general channel models, which include known channel models, such as the transmit and receive correlated model, as special cases. We show that optimal signaling is in a block form, where the block length depends on the signal-to-noise ratio (SNR) as well as the channel correlation matrix. The block signal corresponds to transmitting beams in successive symbol intervals along fixed virtual transmit angles, whose powers are determined by (nonidentical) water filling solutions based on the optimization criteria. Our analysis shows that these water filling solutions identify exactly which virtual transmit angles are important for channel estimation. In particular, at low SNR, the block length reduces to one, and all the power is transmitted on the beam corresponding to the strongest transmit angle, whereas at high SNR, the block length has a maximum length equal to the number of active virtual transmit angles, and the power is assigned equally to all active transmit angles. Consequently, from a channel estimation viewpoint, a faster fading rate can be tolerated at low SNRs relative to higher SNRs.     

A linear, time-varying system framework for noniterativediscrete-time band-limited signal extrapolation

A technique for the analysis and design of noniterative algorithms for discrete-time, band-limited signal extrapolation is described. The approach involves modeling the extrapolation process as a linear, time-varying (LTV) system, or filter. Together with a previously developed Fourier theory for LTV systems, this model provides a frequency-domain transfer function representation for the extrapolation system. This representation serves as a powerful tool for characterizing and comparing the reconstruction properties of several well-known least squares optimal algorithms for band-limited extrapolation. Moreover, the frequency-domain setting provides a conceptually attractive means for understanding the process of extrapolation itself. Additionally, a least squares approximation methodology for designing LTV filters for band-limited extrapolation is developed. The design technique is shown to unify a broad class of algorithms for extrapolating discrete-time data and, further, to provide a means for designing new and improved extrapolation algorithms     

An optimal design for a homomorphic deconvolution system

A precise expression for the deconvolved signal is derived by introducing the transmission factor, which is defined as the factor of the ratio of the deconvolved signal to the desired signal. An optimal deconvolution system is then defined as the system which minimizes the energy of the maximum distortion factor (=1-transmission factor). It is shown by numerical examples that the proposed system gives superior performance compared to the conventional     

Time-frequency formulation, design, and implementation oftime-varying optimal filters for signal estimation

This paper presents a time-frequency framework for optimal linear filters (signal estimators) in nonstationary environments. We develop time-frequency formulations for the optimal linear filter (time-varying Wiener filter) and the optimal linear time-varying filter under a projection side constraint. These time-frequency formulations extend the simple and intuitive spectral representations that are valid in the stationary case to the practically important case of underspread nonstationary processes. Furthermore, we propose an approximate time-frequency design of both optimal filters, and we present bounds that show that for underspread processes, the time-frequency designed filters are nearly optimal. We also introduce extended filter design schemes using a weighted error criterion, and we discuss an efficient time-frequency implementation of optimal filters using multiwindow short-time Fourier transforms. Our theoretical results are illustrated by numerical simulations     

LDPC code design for asynchronous Slepian-Wolf coding

We consider asynchronous Slepian-Wolf coding where the two encoders may not have completely accurate timing information to synchronize their individual block code boundaries, and propose LDPC code design in this scenario. A new information-theoretic coding scheme based on source splitting is provided, which can achieve the entire asynchronous Slepian-Wolf rate region. Unlike existing methods based on source splitting, the proposed scheme does not require common randomness at the encoder and the decoder, or the construction of super-letter from several individual symbols. We then design LDPC codes based on this new scheme, by applying the recently discovered source-channel code correspondence. Experimental results validate the effectiveness of the proposed method.     

On predicting a band-limited signal based on past sample values

The prediction of samples of a band-limited real signal xa(t) from a finite number of past samples is considered. It is shown how a signal-independent linear predictor of finite order can be constructed based on Chebyshev polynomials, such that the prediction error tends to zero for sampling rate exceeding the Nyquist rate.     

On the prediction of a band-limited signal from past samples

An alternate proof is given of a recent result due to A. Papoulis on predicting the current value of a wide-sense stationary band-limited random process in terms of its past samples. The possibility of such prediction is shown to be equivalent to the completeness of a certain set of complex exponentials on an interval, a property that also allows extension to the prediction of deterministic band-limited signals.     

An exact algorithm for wirelength optimal placements in VLSI design

We present a new algorithm designed to solve floorplanning problems optimally. More precisely, the algorithm finds solutions to rectangle packing problems which globally minimize wirelength and avoid given sets of blocked regions. We present the first optimal floorplans for 3 of the 5 intensely studied MCNC block packing instances and a significantly larger industrial instance with 27 rectangles and thousands of nets. Moreover, we show how to use the algorithm to place larger instances that cannot be solved optimally in reasonable runtime.     

关于异步FIFO设计的探讨

在两个不同时钟域中传送数据时,异步先进先出(FIFO,First In First Out)通常被用来保证数据传送的安全性.将某一个时钟域中的数据安全地传送到另一个时钟域中,需要多异步时钟设计技术.关于FIFO设计方法的报道有很多,但我们很难分析其正确性.文章较为详细地介绍了利用格雷码指针实现不同时钟域数据传输的FIFO设计.     

An exact algorithm for optimal MAE stack filter design.

We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.     

An optimal design method for magnetic resonance imaging gradient waveforms

A method of using nonlinear constrained optimization to design gradient waveforms for magnetic resonance imaging is described. Formulation and solution of the waveform optimization problem are described and example waveforms are presented for a variety of design objectives and constraint sets. Most design objectives can be expressed as linear or quadratic functions of the discrete parameter set, and most constraint functions are linear. Thus, linear and quadratic programming techniques can be utilized to solve the optimization problem. Among the objectives considered are: minimize RMS current; minimize waveform slewing; minimize waveform moments to reduce motion induced dephasing; minimize echo time (TE) for given imaging and motion refocusing conditions; maximize the gradient amplitude during RF application and sampling and the area of the phase encoding waveform to maximize resolution; and minimize or maximize the gradient b factor or diffusion sensitivity. This optimal design procedure produces physically realizable waveforms which optimally achieve specific imaging and motion artifact reduction goals, and it is likely to reduce waveform design time by making it more scientifically (rather than heuristically) based.     

单波长掺铒光纤放大器的智能优化设计

提出了一种基于单波长的智能化掺铒光纤放大器结构方案,并进行了相关仿真研究.该掺铒光纤放大器通过控制若干个1×2光开关选择对于不同输入光信号功率所需要的最佳铒纤长度,结合泵浦功率的调节,可以得到最优的增益和输出光信号功率.仿真实验表明该放大器可以达到较好的性能,既可以作为功率放大,也可以用作前置放大和线路放大.     

Accurate computation of bit error probabilities of band-limited asynchronous DS-CDMA systems using higher order moments

An existing method called the simplified improved Gaussian approximation (SIGA) was previously applied to compute the bit error probabilities (BEPs) of band-limited asynchronous direct sequence code division multiple access (DS-CDMA) systems employing general pulse shaping (IEEE Trans. Commun., vol. 50, p. 656, 2002). The SIGA method uses moments up to the second order and is more accurate than the standard Gaussian approximation (SGA) (IEEE Trans. Commun., vol. 50, p. 656, 2002). In this paper, a new method that uses moments up to the fourth order is proposed for computing the BEP. The method is derived from a five-point Chebyshev interpolation formula and is inherently more accurate than the SIGA. Like the SIGA, the new method requires the evaluation of only closed-form expressions and the error function. The new method achieves higher accuracy with a modest increase in computational complexity.     

A simple and accurate method of probability of bit error analysisfor asynchronous band-limited DS-CDMA systems

This paper considers probability of bit error (P_e) analysis in asynchronous band-limited direct-sequence code-division multiple-access (DS-CDMA) systems. It presents a simple and accurate method of P_e analysis. The proposed method can serve as an attractive alternative to the only two techniques currently available for band-limited systems: the standard Gaussian approximation (SGA) and the characteristic function method. The former is prone to inaccuracy while the latter, large computational complexity. The method generalizes the simplified improved Gaussian approximation (SIGA) derived previously for rectangular pulses. This paper also outlines a generalization of another method referred to as the improved Gaussian approximation (IGA). Numerical examples demonstrate the far greater accuracy of the generalized SIGA with respect to the SGA. The examples consider the IS-95 and square-root raised cosine (Sqrt-RC) pulses as well as uniform and nonuniform received power conditions     

Signal set design for band-limited memoryless multiple-access channels with soft decision demodulation

Signal sets are identified that maximize the cutoff rate region for a multiple-access channel with an additive white Gaussian noise, in which the demodulator output alphabet is allowed to be infinite ("infinitely soft decisions"). The optimizing designs consist of a simplex signal set for each sender, such that each sender's set is orthogonal to those of the other senders. For "second moment" and for "fractional out-of-band-energy" bandwidth constraints on the signals of each sender, conditions are derived under which mutually orthogonal simplex sets are still optimal. For the second moment constraint, simplex sets derived from sinusoidal functions yield an optimal design and, for the out-of-band energy constraint, simplex Sets derived from prolate spheroidal wave functions are optimal. Choices of signal sets that maximize the cutoff rate region for an additive shot-noise limited multiple-access optical channel, subject to average energy and peak amplitude constraints, are also identified.     

An integrated switched-capacitor signal processing design system

A CAD system integrating switched-capacitor network function synthesis, circuit synthesis, and layout is presented. The tool addresses the design of programmable gain, cosine, interpolation, and arbitrary transfer functions in addition to canonical filter structures. Amplifier design is based on numerical optimization of highly accurate analytic models derived with the aid of symbolic-mathematics-based model development aids. The physical design of the filter is created by a general-purpose switched-capacitor circuit synthesizer. The tool makes it possible to synthesize a complete switched-capacitor signal path with full handcrafted quality in a single day. Examples taken from actual IC designs illustrate the utility and accuracy of the various functions     

An iterative algorithm for optimal design of non-frequency-selective FIR digital filters

This paper proposes a novel iterative algorithm for optimal design of non-frequency-selective Finite Impulse Response （FIR） digital filters based on the windowing method. Different from the traditional optimization concept of adjusting the window or the filter order in the windowing design of an FIR digital filter, the key idea of the algorithm is minimizing the approximation error by successively modifying the design result through an iterative procedure under the condition of a fixed window length. In the iterative procedure, the known deviation of the designed frequency response in each iteration from the ideal frequency response is used as a reference for the next iteration. Because the approximation error can be specified variably, the algorithm is applicable for the design of FIR digital filters with different technical requirements in the frequency domain. A design example is employed to illustrate the efficiency of the algorithm.