A statistical discrete-time model for the WSSUS multipath channel

The computation of the tap gains of the discrete-time representation of a slowly time-varying multipath channel is investigated. Assuming the channel is wide-sense stationary with uncorrelated scattering (WSSUS), a known Monte Carlo based method approximating the given scattering function (which fully determines the WSSUS channel) is extended by including filtering and sampling. The result is a closed-form solution for the tap gains. This allows the efficient simulation of the continuous-time channel with, e.g., only one sample per symbol, and without explicit digital filtering     

Capacity of wireless optical communications

We consider the ergodic capacity and capacity-versus-outage probability of direct-detection optical communication through a turbulent atmosphere using multiple transmit and receive apertures. We assume shot-noise-limited operation in which detector outputs are doubly stochastic Poisson processes whose rates are proportional to the sum of the transmitted powers, scaled by lognormal random fades, plus a background noise. In the high and low signal-to-background ratio regimes, we show that the ergodic capacity of this fading channel equals or exceeds that for a channel with deterministic path gains. Furthermore, knowledge of these path gains is not necessary to achieve capacity when the signal-to-background ratio is high. In the low signal-to-background ratio regime, path-gain knowledge provides minimal capacity improvement when using a moderate number of transmit apertures. We also develop expressions for the capacity-versus-outage probability in the high and low signal-to-background ratio regimes, by means of a moment-matching approximation to the distribution for the sum of lognormal random variables. Monte Carlo simulations show that these capacity-versus-outage approximations are quite accurate for moderate numbers of apertures.     

State-Transition Monte Carlo for Evaluating Large, Repairable Systems

This paper presents a new Monte Carlo method to estimate unreliabilities of large, repairable systems which can be modeled by a stationary Markov transition diagram. Sequences of state transitions ending at absorbing states are generated, using random numbers. Times to transitions related to the state-sequences are not generated. Next, the probability of system failure occurring in a mission time along each state-sequence is calculated. Finally, the arithmetic mean of these probabilities estimates the system unreliability. This state transition Monte Carlo method yields better estimates in fewer trials than direct Monte Carlo methods. A cold-standby problem with non-identical units is also solved as a by-product of this paper.     

Performance analysis of linear multiuser detectors for randomlyspread CDMA using Gaussian approximation

The performance of a linear decorrelating detector (LDD) and a minimum mean square error (MMSE) detector is analyzed for random spreading waveforms. The performance of the LDD and MMSE detectors is expressed in terms of the so-called near-far resistance, defined by a reciprocal of a diagonal component of inverse matrix. For random code division multiple access, which employs random spreading waveforms, the near-far resistance can be regarded as a random variable. Many papers have dealt with the analysis of multiuser detectors for random spreading sequences. In most cases, however, these analyses derived only the expectations or bounds for the near-far resistance. In this paper, we directly derive the approximate probability density function (PDF) of the near-far resistance and corresponding bit error rate expression for random spreading sequences. It is based on Gaussian approximation of the cross correlation between any two randomly generated spreading codes. The resulting PDF turned out to be a reversed-and-scaled version of chi-square distribution. The approximate expressions, both the PDF and the corresponding bit error rate expression, were verified via Monte Carlo simulations. The results showed that the approximation is quite close to the simulation results when the number of users is less than half the processing gain     

三维粗糙面上的MIMO信道模型

多天线构成的多输入多输出MIMO（Multiple-Input Multiple-Output）信道是B3G/4G系统的关键技术之一。文章建立下垫三维粗糙面的MIMO信道模型,用基尔霍夫（KA,Kirchhoff approximation）近似随机粗糙面散射的数值计算方法研究下垫粗糙面产生的随机多路径传输对MIMO信道矩阵的影响,并数值地讨论接收、发射天线阵列位置以及下垫粗糙面几何参数对MIMO系统信道容量的影响。结果表明,双站距离大、天线高度低时,下垫随机粗糙面对MIMO信道容量的影响显著。当天线阵元间距小时,下垫粗糙面将显著增大MIMO系统信道容量;当天线间距大时,粗糙面减小MIMO系统信道容量。     

Blind detection in MIMO systems via sequential Monte Carlo

We provide a novel sequential estimation and detection approach for multiple-input-multiple-output (MIMO) systems. The basic idea is to design a probabilistic approximation method for the computation of the maximum a posterior distribution (MAP) via the sequential Monte Carlo methods (SMC). The SMC method has two advantages over the other methods in that it is a blind method and can be computed in parallel. Furthermore, the SMC has characteristics of soft-input and soft-output in nature and, thus, it can be employed as the first stage demodulator in a turbo receiver for a coded MIMO system. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information with the MAP outer channel decoder. Finally, the performance of the proposed sequential Monte Carlo receiver is demonstrated through computer simulations for MIMO systems over single-path and multipath fading channels.     

A New Design Concept for High-Performance Fading Channel Simulators Using Set Partitioning

In this paper, we introduce a new technique for the design of high-performance Rayleigh fading channel simulators. The proposed design method uses set partitioning – a technique, which plays a key role in the design of trellis-coded modulation schemes. We show how set partitioning can be used to design multiple uncorrelated fading waveforms enabling the simulation of Rayleigh fading channels. For the important case of isotropic scattering, we show that the sample average of the generated waveforms results in a deterministic process, the autocorrelation function (ACF) of which tends to the zeroth-order Bessel function of the first kind as the number of sample functions increases. The proposed procedure is completely deterministic. The comparison with a stochastic procedure using Monte Carlo techniques will be made. A study of the performance shows clearly that the new technique using set partitioning outperforms by far existing Monte Carlo methods.     

Estimation of Incoherent Scattered Field by Multiple Scatterers in Random Media

This paper proposes a method to estimate directly the incoherent scattered intensity and radar cross section (RCS) from the effective permittivity of a random media. The proposed method is derived from the original concept of incoherent scattering. The incoherent scattered field is expressed as a simple formula. Therefore, to reduce computation time, the proposed method can estimate the incoherent scattered intensity and RCS of a random media. To verify the potential of the proposed method for the desired applications, we conducted a Monte‐Carlo analysis using the method of moments; we characterized the accuracy of the proposed method using the normalized mean square error (NMSE). In addition, several medium parameters, such as the density of scatterers and analysis volume, were studied to understand their effect on the scattering characteristics of a random media. The results of the Monte‐Carlo analysis show good agreement with those of the proposed method, and the NMSE values of the proposed method and Monte‐Carlo analysis are relatively small at less than 0.05.     

A soft decision-directed LMS algorithm for blind equalization

An adaptation algorithm for equalizers operating on very distorted channels is presented. The algorithm is based on the idea of adjusting the equalizer tap gains to maximize the likelihood that the equalizer outputs would be generated by a mixture of two Gaussians with known means. The decision-directed least-mean-square algorithm is shown to be an approximation to maximizing the likelihood that the equalizer outputs come from such an independently and identically distributed source. The algorithm is developed in the context of a binary pulse-amplitude-modulation channel, and simulations demonstrate that the algorithm converges in channels for which the decision-directed LMS algorithms does not converge     

Turbo Estimation and Equalization for Asynchronous Uplink MC-CDMA

In this contribution, we propose a new code-aided synchronization and channel estimation algorithm for uplink MC-CDMA. The space alternating generalized expectation- maximization (SAGE) algorithm is used to estimate the channel impulse responses, propagation delays and carrier frequency offsets of the different users. The estimator, multi-user detector, equalizer, demapper and channel decoder exchange soft information in an iterative way. The performance of the proposed algorithm is evaluated through Monte Carlo simulations. Impressive performance gains are visible as compared to a conventional data-aided estimation scheme.     

Ergodic capacity formula of MIMO-OFDM systems under correlated frequency selective Rayleigh fading channels

An explicit formula for the ergodic capacity of Orthogonal Frequency Division Multiplexing (OFDM)-based Multiple-Input Multiple-Output (MIMO) systems under correlated frequency selective Rayleigh channels is derived,by simplifying the channel response matrix in frequency domain into the so-called Kronecker model composed of three kinds of correlations,i.e.multipath tap gain correlation and spatial fading correlations at both transmitter and receiver.The derived formula is very simple and convenient for one to estimate the effects of all three kinds of correlations on MIMO-OFDM capacity.If taps are independent,there is a very simple expression for the ergodic capacity.In case of tap correlation,the capacity formula could be further given in an integral expression.The validity of the new formula is verified and the effects of correlations,delay spread as well as the number of subcarriers on the ergodic capacity are evaluated via Monte Carlo simulations.     

Accurate and time efficient estimation of the probability of error in bursty channels

A method and a technique for the probability of error estimation in digital channels with memory are developed and demonstrated. The expressions for the mean and variance of a random variable, representing a block of bits transmission in a bursty channel (channel with memory), are derived. The influence of the memory is expressed by a parameter called the memory factor. It is shown that the traditional Monte Carlo method can be applied for the probability of error estimation. In order to control the accuracy and increase the time efficiency of estimation this method is modified and a new method, called the modified Monte Carlo method, is proposed. Based on this modified method a technique of estimation with controlled accuracy is developed and demonstrated using data obtained by simulation. According to this technique the sample size is adjusted in the course of estimating procedure to give an accurate estimate of the probability of error for a minimum required time of estimation. Copyright © 2003 John Wiley & Sons, Ltd.     

对数正态分布衰落下的光OFDM水下可见光通信空间分集系统

水下可见光通信(UVLC)是实现高速宽带信息传输的有效方案,但由于受到信道中吸收、散射和湍流的不利影响而面临着许多困难。针对水下湍流信道中多径和衰落带来的影响,提出了一种光正交频分复用(O-OFDM)等增益合并的分集方案,根据广义的朗伯定律得到信道增益,通过对数正态分布模拟信号衰落。采用蒙特卡洛方法对正交幅度调制(QAM)的非对称削波光正交频分复用(ACOOFDM)和直流偏置光正交频分复用(DCO-OFDM)两种分集系统进行建模仿真,分析高斯信道和弱湍流信道下系统的误比特率,探讨不同分集数目和闪烁系数情况下的分集增益。研究结果验证了分集是降低湍流影响的有效手段,有利于改善水下信息传输性能,为弱湍流信道下正交频分复用可见光通信系统的设计、预测和评估提供参考。     

大规模MIMO-OFDM系统结构化压缩感知信道估计中导频优化方法研究

对于FDD模式的大规模MIMO-OFDM系统,本文研究了将结构化压缩感知理论用于该系统的稀疏信道估计。考虑在该系统中将每个发送天线上的导频重叠放置,即每个发送天线可以在相同的时频资源块上发送导频符号,那么此时的系统稀疏信道估计问题可以建模为结构化压缩感知重建问题。为了优化导频位置和导频符号来改进稀疏信道估计的质量,提出了一种最小化完全块间相关值的导频优化准则以及基于此准则的导频搜索算法,完全块间相关值是结构化压缩感知框架下衡量恢复矩阵子块间相关程度的量值。仿真结果表明,与其他导频相比,使用此优化方法获得的导频可以使信道估计误差明显减小,其性能增益大约为2~5 dB。另外,仿真结果还表明,在相同的导频数量前提下,使用优化导频获得的性能增益会随着发送天线数量的增加而变得更加明显。      

Supporting Asymmetric Traffic in a TDD/CDMA Cellular Network via Interference-Aware Dynamic Channel Allocation and Space–Time LMMSE Joint Detection

In a time-division duplexing (TDD)/code-division multiple-access (CDMA) cellular network with asymmetric data traffic, dynamic channel allocation (DCA) enhances resource utilization compared with fixed channel allocation (FCA). However, it also induces base-to-base and mobile-to-mobile crossed-slot intercell interference, which can severely degrade system performance. To deal with this problem, a decentralized scheme is proposed, which combines an interference-aware DCA algorithm with space–time linear minimum-mean-square-error (LMMSE) joint detection at the base and mobile stations. The former assigns active links to timeslots in a way that crossed-slot interference is mitigated, while the latter suppresses the remaining intercell interference (along with intersymbol and intracell interference), exploiting its spatio-temporal autocorrelation statistics. The performance of this scheme is evaluated in terms of downlink and uplink signal-to-interference-plus-noise ratio (SINR) outage and average throughput via analytical approximations and Monte Carlo simulations, and it is compared with that of benchmark random DCA (RDCA) and FCA schemes. The cases of single- and dual-antenna reception with perfect and imperfect channel state information are examined. It is shown that the proposed scheme achieves higher average throughput than FCA (particularly for dual-antenna reception) as well as RDCA (for heavy traffic loads). These throughput gains are more significant in uplink than in downlink.      

基于FDTD方法的无线信道衰落特性模拟研究

为了表述无线信道衰落的时变及远区分布特性，提出了利用时域有限差分(FDTD)方法研究由多径效应引起的时变无线信道衰落的方法。在此将无线信道的衰落建模为随机过程，而不是通常的确定性随机变量。首先基于Clarke统计模型，利用FDTD方法研究了时变无线信道的小尺度平坦衰落特征；然后利用Monte Carlo方法和FDTD方法产生了具有信道多普勒功率谱特性的色高斯随机过程，再基于无线信道的时变统计特性建模，用Suzuki模型研究了时变无线信道的快衰落；最后将无线信道衰落特性分布和理论分布做了比较，验证了方法的有效性。     

Uplink sum capacity evaluation of multi-user distributed antenna systems

This letter focuses on the simplified sum capacity evaluation for the uplink of a generalized multi-user distributed antenna system (DAS). Based on system scale-up, we derive a good approximation of the sum capacity by generalizing the results from random matrix theory. An iterative method is presented to calculate the unknown parameters in the approximation. The approximation is illustrated to be quite accurate and the iterative method is demonstrated to be quite efficient by Monte Carlo simulations.     

Sparse array of sub-surface aided blockage-free multi-user mmWave communication systems

Recently, Reconfigurable Intelligent Surfaces (RISs) have drawn intensive attention in the realization of the smart radio environment. However, existing works mainly consider the RIS as a whole uniform plane, which may be unrealistic to be installed on the facade of buildings when the RIS is extremely large. In contrast, this paper investigates a practical Sparse Array of Sub-surface (SAoS) deployment of the RIS for uplink multi-user millimeter Wave (mmWave) communication systems, in which the Mobile Stations (MSs) are distributed in the blind coverage area due to the blockage. In order to exploit the benefits of the sparse deployment, the correlation of the effective channel is firstly investigated. Then the approximation and lower bounds of the ergodic spectral efficiency are derived under frequency and spatial multiplexing scenarios, respectively. Based on the autocorrelation of the effective channel, we obtain an optimal reflect coefficient design as well as the deployment guidelines of RIS tiles. Moreover, the RIS tile scheduling algorithms are also proposed. Numerical results show that the ergodic spectral efficiency approximation matches well with the Monte Carlo result under frequency multiplexing scenarios, and the lower bound is tight under spatial multiplexing scenarios only when the effective channel is strongly correlated. On the basis of the RIS tile scheduling algorithm and the reflect coefficient design, the system performance can be significantly improved under frequency multiplexing scenarios. On the other hand, by deploying more sparse RIS tiles, we can increase the multiplexing gain under spatial multiplexing scenarios.     

BER Performance of Bandlimited DS-CDMA Systems in Nakagami Fading

Accurate average bit-error rate analysis of asynchronous bandlimited binary direct-sequence code-division multiple-access (DS-CDMA) systems in Nakagami-m fading is studied. The fading is assumed to be flat and slow. The spectrum raised-cosine (SRC) and Beaulieu-Tan-Damen (BTD) pulse-shapes are employed. A new method which combines the characteristic function (CF) method with the improved Gaussian approximation (GA) is proposed for evaluating the BER of bandlimited DS-CDMA. A substantial computational complexity reduction is achieved. The well-known standard GA, Holtzman's simplified improved GA, and improved Holtzman's GA methods are also considered. The accuracies of the approximation methods are assessed using Monte Carlo simulation. For a system employing a deterministic sequence for the desired user and random sequences for the active interfering users, a CF method is employed to derive precise BER results. The new BTD pulse outperforms the SRC pulse in all situations     

Partition function estimation of Gibbs random field images usingMonte Carlo simulations

A Monte Carlo simulation technique for estimating the partition function of a general Gibbs random field image is proposed. By expressing the partition function as an expectation, an importance sampling approach for estimating it using Monte Carlo simulations is developed. As expected, the resulting estimators are unbiased and consistent. Computations can be performed iteratively by using simple Monte Carlo algorithms with remarkable success, as demonstrated by simulations. The work concentrates on binary, second-order Gibbs random fields defined on a rectangular lattice. However, the proposed methods can be easily extended to more general Gibbs random fields. Their potential contribution to optimal parameter estimation and hypothesis testing problems for general Gibbs random field images using a likelihood approach is anticipated