Resource Allocation in Multi-channel Multi-user Relay System with Fairness Constraints

In this paper, we derive optimal joint power allocation, subchannel pairing and scheduling strategies in multiple orthogonal channels multiple users wireless networks in the presence of a single regenerative relay node. Two models with users’ data rate request (fairness) constraint in different time domains are considered. The first one is called deterministic model in which each user’s data rate request has to be satisfied in each time slot t (named short term fairness constraint) and the second one is called stochastic model in which users have average data rate request (named long term fairness). In these two models the optimization problems of maximizing system capacity with total transmit power constraint and fairness constraint are formulated. The Lagrangian dual method is used to derive the optimal solution for deterministic model and in the stochastic model stochastic approximation and dual method are employed to find out the optimal algorithm. Both algorithms have polynomial times complexity, which is reduced significantly compared with the Exhaustive Search Method (ESM). Since Lagrangian dual method is utilized in both schemes, the dual gap is also analyzed. Furthermore, through the analysis and simulation, we see that the optimal resource allocation algorithm in stochastic model has better performance than that in the deterministic model for its ability to exploit temporal diversity.     

Level-crossing rate and average duration of fades of deterministicsimulation models for Rice fading channels

The concept of Rice's sum of sinusoids is often applied to the design of deterministic simulation models for Rice fading channels. This paper investigates in detail the level-crossing rate (LCR), average duration of fades (ADF), and cumulative distribution function (CDF) of such classes of simulation models. Exact and simple approximative formulas are deduced for these statistical quantities. Several numerical results for the derived expressions are presented by using different procedures for the design of the parameters of the deterministic simulation model. Moreover, comparisons with the corresponding simulation results-obtained by evaluating the deterministic simulation models output data-are also given     

Fast Test Pattern Generation for Sequential Circuits Using Decision Diagram Representations

The paper presents a novel hierarchical approach to test pattern generation for sequential circuits based on an input model of mixed-level decision diagrams. A method that handles, both, data and control parts of the design in a uniform manner is proposed. The method combines deterministic and simulation-based techniques. On the register-transfer level, deterministic path activation is combined with simulation based-techniques used for constraints solving. The gate-level local test patterns for components are randomly generated driven by high-level constraints and partial path activation solutions. Experiments show that high fault coverages for circuits with complex sequential structures can be achieved in a very short time by using this approach.     

Spatio-temporal channel characterization in a suburban nonline-of-sight microcellular environment

This paper reports a spatio-temporal channel characterization of a suburban non-line-of-sight microcellular environment in which azimuth-delay profiles obtained by an experiment are compared with ray-tracing simulation. The results are statistically treated step by step to extract model parameters in order to characterize the spatio-temporal channel. The experimental results we obtain are used to improve the accuracy of the simulation process. We are able to obtain a very good agreement between the simulation and the experiment, with the exception of the exponential decay of the delay profile. The results presented can be directly used to implement the stochastic spatio-temporal channel model, based on the deterministic ray-tracing simulations     

确定性小世界特性记忆网络的建模与算法

为了形象直观的了解脑功能记忆小世界网络的形成及演化机制,采用复杂网络确定性建模的方法对记忆过程进行模拟,通过记忆节点及连边的抽取,建立符合记忆解剖特征和逻辑意义的连边机制.以集合为数据结构的建模算法仿真了小世界特性的记忆网络,同时数据元素的检索算法符合记忆特征.通过理论分析和数据仿真表明对脑功能记忆网络进行确定性建模是可行的.     

Jitter Analysis of Nonautonomous MOS Current-Mode Logic Circuits

In this paper, we analyze the occurrence of jitter due to random and deterministic disturbances in nonautonomous current-mode logic circuits. First, we present an analytical model that explains the transformation of noise into jitter as a linear time-variant process, with its time-domain impulse response function and a frequency-domain system function. The model is then used to analyze jitter in two different circuits, with different sources of noise. In the first example, we use the model to predict jitter due to device noise in a frequency divider, and identify devices that are the main contributors to the jitter. In the second example, we examine jitter of a buffer with deterministic ground noise. Jitter predictions are compared to the results obtained through exhaustive simulation. According to the comparison, the method predicts jitter with an error of up to 3.4%.      

小尺度时变多径衰落信道的仿真研究

从理论上分析了多径效应和多普勒效应对无线信道的影响,并分别从时域和频域给出了信号经历信道后的仿真图形,分析了典型时变多径衰落信道理论模型,并在此基础上建立了抽头延迟线（TDL）的确定性仿真模型;仿真分析表明,通过改变时延功率谱和确定性模型的参数计算方法,此模型可以进一步扩展并用于多种传播环境下的小尺度衰落仿真。     

Accurate System Voltage and Timing Margin Simulation in High-Speed I/O System Designs

Accurate analysis of system timing and voltage margin including deterministic and random jitter is crucial in high-speed I/O system designs. Traditional SPICE-based simulation techniques can precisely simulate various deterministic jitter sources, such as intersymbol interference (ISI) and crosstalk from passive channels. The inclusion of random jitter in SPICE simulations, however, results in long simulation time. Innovative simulation techniques based on a statistical simulation framework have been recently introduced to cosimulate deterministic and random jitter effects efficiently. This paper presents new improvements on this statistical simulation framework. In particular, we introduce an accurate jitter modeling technique which accounts for bounded jitter with arbitrary spectrum in addition to Gaussian jitter. We also present a rigorous approach to model duty cycle distortion (DCD). A number of I/O systems are considered as examples to validate the proposed modeling methodology.      

Statistically based parametric yield prediction for integratedcircuits

This paper presents a novel procedure for predicting integrated circuit parametric performance and yield when provided with sample transistor test results and a circuit schematic. Two enhancements to the existing Monte Carlo simulation procedures are described: (1) a multivariate nested model is used to reproduce random process-induced device-variations, rather than the multivariate multinormal model typically used, and (2) the stochastic Monte Carlo method for mapping process variability into a performance distribution is replaced with a deterministic mapping technique. The use of multivariate nested distributions allows estimation not only of correlation between various model parameters, but also allows each of those variations to be apportioned among the various stages of the process (i.e., wafer to wafer, lot to lot, etc.). This allows matched devices to be more accurately simulated, without having to develop customized models for each configuration of matching, and provides focus for process improvement efforts into those areas with the maximum potential reward. The use of deterministic mapping provides simulation results which are repeatable and do not rely on chance to insure that the process parameter space has been evenly explored. A software package which implements the entire procedure has been written in C++     

SHIM: a deterministic model for heterogeneous embedded systems

Typical embedded hardware/software systems are implemented using a combination of C and an HDL such as Verilog. While each is well-behaved in isolation, combining the two gives a nondeterministic model of computation whose ultimate behavior must be validated through expensive (cycle-accurate) simulation. We propose an alternative for describing such systems. Our software/hardware integration medium (shim) model, effectively Kahn networks with rendezvous communication, provides deterministic concurrency. We present the Tiny-shim language for such systems and its semantics, demonstrate how to implement it in hardware and software, and discuss how it can be used to model a real-world system. By providing a powerful, deterministic formalism for expressing systems, designing systems, and verifying their correctness will become easier.     

A stochastic model of the electrically stimulated auditory nerve:single-pulse response

Most models of neural response to electrical stimulation, such as the Hodgkin-Huxley equations, are deterministic, despite significant physiological evidence for the existence of stochastic activity. For instance, the range of discharge probabilities measured in response to single electrical pulses cannot be explained at all by deterministic models. Furthermore, there is growing evidence that the stochastic component of auditory nerve response to electrical stimulation may be fundamental to functionally significant physiological and psychophysical phenomena. In this paper we present a simple and computationally efficient stochastic model of single-fiber response to single biphasic electrical pulses, based on a deterministic threshold model of action potential generation. Comparisons with physiological data from cat auditory nerve fibers are made, and it is shown that the stochastic model predicts discharge probabilities measured in response to single biphasic pulses more accurately than does the equivalent deterministic model. In addition, physiological data show an increase in stochastic activity with increasing pulse width of anodic/cathodic biphasic pulses, a phenomenon not present for monophasic stimuli. These and other data from the auditory nerve are then used to develop a population model of the total auditory nerve, where each fiber is described by the single-fiber model.     

Advanced Modeling and Accurate Characterization of a 16 Gb/s Memory Interface

As the input/output (I/O) data rate increases to several gigabits per second, determining the performance of high-speed interfaces using conventional simulation and measurement techniques is becoming very challenging. The models of the interconnects have to be broadband and accurate to represent high frequency and second-order effects such as frequency dependence of dielectric losses and surface roughness. The large and small signal behaviors of the transmitter and receiver circuitries have to be correctly represented in link analysis. In addition, the system simulation needs to properly capture the interactions between the circuits and interconnect subsystems to optimize the overall system. However, determining the values of the critical link parameters and their correlations can be complicated. Some of the key parameters are not deterministic and some cannot be observed directly. A combined modeling and measurement approach is indispensable to determine the performance of high-speed links. This paper presents the modeling and characterization techniques employed in the design and verification of a 16 Gb/s bidirectional asymmetrical memory interface. Direct frequency and time-domain methods as well as indirect techniques based on bit-error-rate testing are used to model and determine important link parameters. Complex de-embedding procedures are utilized to extract parameters from externally observed data. On-chip measurements are also used to complement off-chip instrumentation and accurately measure the true performance of the link. The modeling and characterization of prototypes are also discussed and model-to-hardware correlations are presented at component and system levels. Based on both simulation and measurement results, the behavioral model of the complete system is constructed and statistical simulation technique is used to predict the yield and performance at low bit error rate.      

A Modified Loo Model with Partially Blocked and Three Dimensional Multipath Scattering: Analysis,Simulation and Validation

This paper presents a novel mobile fading channel model, belonging to the class of Loo models, in which the multipath power arrives both in three dimensions (3-D) and in two angular sectors at the azimuth receiver’s plane. Moreover shadowing affects the amplitude of the line of sight (LOS) component, making it time varying and following a lognormal distribution, as required for a Loo model. The Doppler power spectral density (PSD) is analytically calculated, after Fourier transforming the closed form autocorrelation function. Afterwards exact solutions for the probability density function (PDF) of the envelope and phase are presented. What follows are approximate solutions for the second order statistics, i.e. the level crossing rate (LCR) and the average duration of fades (ADF’s). A new, appropriate for 3-D scattering cases, deterministic simulation scheme is developed, which implements the analytical model on a digital computer and is used to test the validity of the approximate solutions. Moreover the deterministic model is thoroughly investigated for all the possible cases, in terms of its convergence to the analytical one. Finally a curve fitting of the LCR to real world data, drawn from channel measurements, will demonstrate the flexibility and usefulness of the modified Loo model.     

Microwave imaging-complex permittivity reconstruction-by simulatedannealing

A preliminary study of the application of simulated annealing (SA) to complex permittivity reconstruction in microwave tomography is presented. Reconstructions of a simplified model of a human arm obtained with simulated noise-free data are presented for three different methods: SA, quenching, and a Newton-Kantorovich method. These results show that SA can converge to an accurate solution in cases where the two deterministic methods fail. For this reason SA can be used to get closer to the final solution before applying a faster deterministic method     

The Single Server Queue with Periodic Arrival Process and Deterministic Service Times

We derive an algorithm for computing the exact delay distribution for the following first-come-first-served single server queue. The arrival process is the superposition ofN + 1independent equivalent deterministic arrival streams, and the service times are deterministic. Numerical results are used to compare this system with an approximating system which has been used in the absence of exact results: theM/D/1queue (Poisson input, deterministic service time). A comparison with a finite source model is also given. This study was motivated by the following issue germane to packet switching data networks. There areN + 1packet processes, arriving over identical trunks, which must share the transmission capacity of a single high-speed trunk in a store-and-forward manner. The idealized queueing model above analyzes the worst-delay situation for this problem when the incoming trunks are fully utilized and the packets are maximum sized. The results indicate that anM/D/1approximation can be quite pessimistic in predicting the performance of such a system.     

Simulation of average fading duration using deterministic method

Measurements and modelling of average fading duration (AFD) for a mobile channel with line-of-sight (LOS) component at VHF frequencies (69.75 MHz) show that the deterministic method can be used to simulate the AFD of a mobile channel, and that a mobile channel with a LOS component can be modelled using Loo's model. To obtain an accurate simulated AFD, an appropriate sample interval should be used in the simulation     

Equivalent Resonant Cavity Model of Arbitrary Periodic Guided-Wave Structures and Its Application to Finite-Difference Frequency-Domain Algorithm

An equivalent resonant cavity model is proposed and developed for efficiently and accurately extracting the complex propagation constant of any arbitrary bounded and unbounded periodic guided-wave structures, which is known as a difficult eigenvalue problem with respect to a deterministic or S-parameter-based field solver. In this study, this problem is formulated as a standard eigenvalue one, which is made possible by effectively translating the transmission distance-related attenuation part of complex propagation constant into a time-dependent damping factor. This allows the development of an equivalent resonant cavity model to substitute or replace the periodic guided-wave model, leading to a complex frequency simulation model. As a result, the simulation time and storage requirement are then reduced significantly with this complex frequency approach. A finite-difference frequency-domain algorithm combined with this model is used to demonstrate the concept, and the properties of arbitrary complex closed/open periodic guided-wave structures are rigorously investigated. The proposed algorithm has been validated by both simulations and experiments     

基于泛函网络求解随机优化问题的EM算法

研究了一类带有随机变量的不确定优化问题。为了解决这类随机优化问题,首先用随机仿真为泛函网络产生训练样本,用泛函网络逼近随机函数的均值,将随机函数的均值转为不合随机变量的确定性函数,然后用类电磁算法求解确定性函数的最优解。最后,给出一些数值例子验证了所提算法的有效性。     

An Improved Deterministic SoS Channel Simulator for Multiple Uncorrelated Rayleigh Fading Channels

The generation of multiple uncorrelated Rayleigh fading waveforms is often demanded for simulating wideband fading channels, multiple-input multiple-output (MIMO) channels, and diversity-combined fading channels. In this letter, an improved deterministic sum-of-sinusoids (SoS) channel simulator with a new parameter computation method is proposed to simulate a large number of uncorrelated Rayleigh fading processes. Compared with the existing SoS channel simulators, the proposed deterministic SoS model yields a much better simulation efficiency while still preserving satisfactory approximations to the desired statistical properties of the reference model.     

Detection of broadband planewaves in the presence of Gaussian noiseof unknown covariance: asymptotically optimum tests using the 2-Dautoregressive noise model

This paper addresses the problem of detecting a broadband planewave in noise of unknown spatial and temporal covariance at a linear array of sensors. Results of asymptotic detection theory are applied to derive detectors that approach optimal performance for large data records. A parametric approach is used to model the statistics of the data. A 2-D autoregressive (2DAR) model is chosen to model the noise process. Two broadband planewave signal models are considered. Both models represent the signal as a sum of monochromatic planewaves. In the Gaussian model, the amplitudes are assumed to be Gaussian with a single variance parameter, whereas in the deterministic assumption, they are individual unknown parameters. Detectors based on asymptotic theory are derived for both models. As part of the development of the asymptotically (AS) optimum detector, the Fisher information matrix (FIM) is derived. A proof of the locally asymptotic normal (LAN) property is provided for the Gaussian model probability density function (PDF). Both detectors, however, are AS equivalent to the generalized likelihood ratio test (GLRT), are AS of constant false alarm rate (CFAR), and perform AS as well as the GLRT constructed with full knowledge of the noise statistics. The performance of both detectors are compared with each other and to a standard spatially normalized beamformer in a computer simulation