Nakagami-m分布衰落信道的FSMC模型及其性能分析

本文将一阶FSMC(有限态Markov信道)模型引入Nakagami—m分布衰落信道的仿真中,并且分析对比了采用 FSMC模型后Nakagami—m分布衰落信道的电平穿越速率与输出误码率等指标,给出了状态转移概率的理论值与仿真值,说明FSMC模型在Nakagami—m分布衰落信道仿真中的可行性。     

时变多普勒衰落信道硬件模拟的FPGA实现

针对不同散射环境下衰落信道具有不同的多普勒功率谱形状,提出了一种改进的复谐波叠加模型用于时变多普勒衰落信道的模拟,仿真分析了该方法输出信道衰落的幅值及相位连续性,并据此设计了基于FPGA硬件平台的时变多普勒衰落信道模拟器。硬件实测结果表明,该模拟器输出的时变多普勒功率谱与理论仿真非常吻合,可用于实际中多普勒功率谱实时变化场景的模拟。     

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。     

基于BEM的非平稳双选信道估计方法

面向高速环境下的无线通信系统,针对高速信道的双选衰落和非平稳特性,提出一种基于基扩展模型（Basis Expansion Model,BEM）的贝叶斯滤波的信道估计方法.针对双选衰落特性,采用BEM信道模型,降低估计复杂度,消除子载波间干扰;针对非平稳特性,提出一种基于贝叶斯滤波的联合估计信道冲激响应与时变的时域自相关系数的信道估计方法.仿真分析表明,所提方法相较最小二乘法等传统方法在高速环境下能够提升估计精度和误码率性能.本方法特别适用于高速铁路的无线通信系统.     

多普勒频移测量方法研究

多普勒频移是表征多径衰落信道时变特性的重要参数。从实测角度出发,根据多普勒功率谱与信道时间差相关函数之间的傅里叶变换关系,提出了一种基于接收信号电平测量的多普勒频移测量方法。开发了相应的数据处理软件,将测量数据以直观的图形表示出来,利用此测量方法在多条野外线路上进行了多普勒频移测量,获得了较精确的数值,为进行多径衰落信道下通信系统的合理设计起到了重要作用。     

非平稳信道衰落FPGA实时模拟方法

针对由于收发端的高速移动导致信道衰落呈现的非平稳特性,提出了一种基于线性调频信号叠加的非平稳信道衰落产生方法,并对输出信道衰落的幅值分布和平均增益进行了详细分析,据此设计了基于FPGA硬件平台的非平稳信道衰落模拟器。硬件实测结果表明,该模拟器输出信道衰落分布、自相关函数和多普勒功率谱等均与理论结果非常吻合,可应用于针对非平稳散射环境下的下一代无线通信系统性能测试和验证。      

复杂环境下基于噪声匹配的最大多普勒频移估计

本文针对城市复杂信道环境下的最大多普勒频移估计需求,根据莱斯衰落信道中电平通过率(LCR)算法的理论推导,提出了一种基于噪声匹配的最大多普勒频移估计算法.所提算法通过对接收信号进行低通滤波处理,实现干扰噪声与多普勒检测器之间的匹配,从而有效提高最大多普勒频移的估计性能.而且基于莱斯衰落信道下最佳滤波比值的分析和推导,得...     

ITS宽带短波信道及其噪声的建模和仿真

文章介绍了宽带短波（WBHF）信道研究的发展历程,根据ITS信道建模的方法,在对信道衰落特征及其噪声干扰统计特性进行分析的基础上建立了适当模型,并设定了特定环境下信道衰落模型及其噪声模型的相关参数。最后通过计算机仿真与实测数据加以比较,从散射函数能量分布、噪声时／频域电平以及噪声电平交叉率（LCR）方面验证了信道模型的合理性。     

相关瑞利信道仿真方法的研究

在无线通信系统的仿真中,相关瑞利衰落信道扮演着重要的作用。一种基于对一系列统计独立的标准高斯随机过程进行线性变换,得到具有一定相关特性的瑞利衰落信道的仿真模型被提出。仿真结果及复杂度分析表明,由于本文提出的仿真模型采用了迭代算法,因此相对于传统的相关瑞利信道仿真模型,该模型具有准确,复杂度低,易实现等优点。     

多用户选择与协作干扰的安全性能分析

研究了一种多用户选择与协作干扰相结合的无线传输模型。在Nakagami-m衰落信道下，考虑到信道中的反馈延迟对信道状态信息的影响，采用合法信道的过时信道状态信息来选择目的用户。采用一般次序选择策略选择目的用户，并结合噪声干扰策略进行干扰，实现信息的安全传输。针对窃听信道两种不同信道状态信息，分别推导了中断概率和窃听概率的准确闭合表达式，并给出二者性能折中的表达式。理论分析与数值仿真表明，减小用户选择参数以及降低信道衰落参数能够有效地改善系统的可靠性与安全性折中安全性能。      

Novel Approach for Modeling Wireless Fading Channels Using a Finite State Markov Chain

Empirical modeling of wireless fading channels using common schemes such as autoregression and the finite state Markov chain (FSMC) is investigated. The conceptual background of both channel structures and the establishment of their mutual dependence in a confined manner are presented. The novel contribution lies in the proposal of a new approach for deriving the state transition probabilities borrowed from economic disciplines, which has not been studied so far with respect to the modeling of FSMC wireless fading channels. The proposed approach is based on equal portioning of the received signal‐to‐noise ratio, realized by using an alternative probability construction that was initially highlighted by Tauchen. The associated statistical procedure shows that a first‐order FSMC with a limited number of channel states can satisfactorily approximate fading. The computational overheads of the proposed technique are analyzed and proven to be less demanding compared to the conventional FSMC approach based on the level crossing rate. Simulations confirm the analytical results and promising performance of the new channel model based on the Tauchen approach without extra complexity costs.     

Fading Channel Modeling via Variable-Length Markov Chain Technique

Channel characterization and modeling are essential to the wireless communication system design. A model that optimally represents a fading channel with a variable-length Markov chain (VLMC) is proposed in this paper. A VLMC offers a general class of Markov chains whose structure has a variable order and a parsimonious number of transition probabilities. The proposed model consists of two main components: 1) the optimal fading partition under the constraint of a transmission policy and 2) the derivation of the best VLMC representation with respect to the Kullback-Leibler (K-L) distance of fading samples. The fading partition is used to discretize a continuous fading channel gain. The optimal discretization criterion is developed based on the cost function of fading channel statistics and the transmission policy used in the system. Once a continuous fading channel gain is discretized, a VLMC is then used to model the channel. To obtain the optimal VLMC representation, we use the K-L distance of the discretized fading samples as the optimization criterion. The K-L distance of the discretized fading samples is used to determine the appropriate transition probabilities characterizing the optimal VLMC. Last, we show simulation results that demonstrate the accuracy and the effectiveness of the proposed fading channel representation in modeling the Rayleigh fading as well as the lognormal fading.     

On first-order Markov modeling for the Rayleigh fading channel

Previous models for the received signal amplitude of the flat-fading channel that use first-order finite-state Markov chains are examined. The stochastic properties of a proposed first-order model based on these models are examined. The limitations of using an information theoretic metric, which is sometimes used to justify a first-order Markov chain as a sufficient model for very slowly fading channels, are discussed. A simple method of qualitatively comparing autocorrelation functions is instead proposed. The usefulness of the first-order Markov chain in representing the flat-fading channel is examined by looking at two specific problems in wireless system applications that represent two disparate cases. The first case involves analysis over a short duration of time, relative to the inverse of the normalized Doppler frequency, while the second involves analysis over a long duration of time. Contrary to previous reports, the results indicate that first-order Markov chains are not generally suitable for very slowly fading channels. Rather, first-order Markov chains can be suitable for very slowly fading applications, which require analysis over only a short duration of time     

Modeling End-to-End Wireless Lossy Channels: A Finite-State Markov Approach

In this paper, we present a model for wireless losses in packet transmission data networks. The model provides information about the wireless channel status that can be used in congestion control schemes. A Finite State Markov Channel (FSMC) approach is implemented to model the wireless slow fading for different modulation schemes. The arrival process statistics of the packet traces determine the channel state transition probabilities, where the statistics of both error-free and erroneous bursts are captured. Later, we establish SNR partitioning scheme that uses the transition probabilities as a basis for the state margins. The crossover probability associated with each state is calculated accordingly. We also propose an end-to-end approach to loss discrimination based on the channel state estimation at the receiver. Finally, we present a scheme for finding the channel optimal number of states as a function of the SNR. The presented FSMC approach does not restrict the state transitions to the adjacent states, nor does impose constant state duration as compared to some literature studies. We validate our model by experimental packet traces. Our simulation results show the feasibility of building a fading channel model for better wireless-loss awareness.     

Statistical analysis of mobile radio reception: an extension of clarke?s model

Statistical analysis and modeling of wireless channels is essential to wireless communication systems. Clarke?s model [1] and the corresponding statistical analysis of mobile radio reception has been widely accepted in numerous wireless applications. Since the component phases in Clarke?s model are assumed to be constant in time, the well-known results of statistical analysis based on this model, such as the autocorrelation and Doppler power spectrum, are not appropriate to describe real wireless channels for which the random environments (radio propagation paths) are time-varying and accordingly for which the channel is non-constant in the absence of Doppler frequency shift. In this paper, we extend the traditional Clarke?s model incorporating the effect of fluctuations in the component phases, and perform the statistical analysis which results in a closed-form expression of the autocorrelation of the fading. The theoretical power spectral density function, which is the Fourier transform of the resultant autocorrelation of the fading, is shown to fit the practical measured spectra, which is in contrast to the traditional theoretical flat fading channel spectra (Jakes? spectrum in [2]). The proposed model and statistical results should have important implications for detailed spectral analysis and channel simulations for real wireless communications systems in random fluctuating electromagnetic propagation environments.     

Two-Layer multistate Markov model for modeling a 1.8 GHz narrow-band wireless propagation channel in urban Taipei city

An accurate propagation channel model is crucial for evaluating the performance of a communication system. A propagation channel can be described by a Markov model with a finite number of states, each of which is considered to be quasi-stationary over a short period. This work proposes a two-layer multistate Markov model. Instead of a large Markov transition matrix used in a conventional single-layer Markov model, two small Markov transition matrices are employed by a two-layer Markov model to reduce the computational complexity of the model without increasing the memory requirements. The proposed approach characterizes the multiplicative processes of a propagation channel as shadowing and fast fading. Each type of fading is considered as several channel states and each of the states corresponds to a specific mixed Rayleigh-lognormal distribution. Numerical results reveal that the statistical properties of the simulated data are quite close to those obtained from the measurements; indeed, the proposed two-layer Markov model is more accurate and less complex, and requires less memory than the single-layer Markov model. Furthermore, the proposed two-layer Markov model enables the fading statistics and error probability performance of a quadrature phase-shift keying modulation scheme in a typical urban Taipei environment to be more accurately predicted. Besides, it can easily be applied to similar environmental scenarios.     

Optimized Transmission for Fading Multiple-Access and Broadcast Channels With Multiple Antennas

In mobile wireless networks, dynamic allocation of resources such as transmit powers, bit-rates, and antenna beams based on the channel state information of mobile users is known to be the general strategy to explore the time-varying nature of the mobile environment. This paper looks at the problem of optimal resource allocation in wireless networks from different information-theoretic points of view and under the assumption that the channel state is completely known at the transmitter and the receiver. In particular, the fading multiple-access channel (MAC) and the fading broadcast channel (BC) with additive Gaussian noise and multiple transmit and receive antennas are focused. The fading MAC is considered first and a complete characterization of its capacity region and power region are provided under various power and rate constraints. The derived results can be considered as nontrivial extensions of the work done by Tse and Hanly from the case of single transmit and receive antenna to the more general scenario with multiple transmit and receive antennas. Efficient numerical algorithms are proposed, which demonstrate the usefulness of the convex optimization techniques in characterizing the capacity and power regions. Analogous results are also obtained for the fading BC thanks to the duality theory between the Gaussian MAC and the Gaussian BC.     

Finite-State Markov Chain Models for the Intensity of Nakagami Fading

For the design, analysis, and simulation of communication systems with Nakagami-m fading channels, it is very convenient to model the fading by finite-state Markov chains in which the states represent fade levels or signal-to-noise ratios in decibels. Our approach to the development of such Markov chain models is to work with the intensity of the fading process, which is proportional to the logarithm of squared envelope of the faded signal. We demonstrate that all the parameters of the Markov chains can be determined from the bivariate distribution of the intensity of the Nakagami-m fading process. Several analytical results are derived from the bivariate distribution of the intensity, including expressions for the chain’s transition probabilities for both adjacent and nonadjacent states and the asymptotic distribution of the intensity for deep fades. For several values of m, we verify the accuracy of our Markov chain models as simulation tools by comparisons of the state probabilities and level-crossing rates obtained from simulations of the Markov chain with those obtained from our analytical expressions.     

Adaptive coding for time-varying channels using outdated fadingestimates

The idea of using knowledge of the current channel fading values to optimize the transmitted signal in wireless communication systems has attracted substantial research attention. However, the practicality of this adaptive signaling has been questioned due to the variation of the wireless channel over time, which results in a different channel at the time of data transmission than at the time of channel estimation. By characterizing the effects of fading channel variation on the adaptive signaling paradigm, it is demonstrated here that these misgivings are well founded, as the channel variation greatly alters the nature of the problem. The main goal of this paper is to employ this characterization of the effects of the channel variation to design adaptive signaling schemes that are effective for the time-varying channel. The design of uncoded adaptive quadrature amplitude modulation (QAM) systems is considered first, and it demonstrates the need to consider the channel variation in system design. This is followed by the main contribution of this paper; using only a single outdated fading estimate when neither the Doppler frequency nor the exact shape of the autocorrelation function of the channel fading process is known, adaptive trellis-coded modulation schemes are designed that can provide a significant increase in bandwidth efficiency over their nonadaptive counterparts on time-varying channels