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。     

一种无线信道复合衰落模型的分析与仿真

移动通信过程中由于移动设备所处的环境不同,存在不同的信道衰落,从各种衰落模型的相互关系出发,提出了一种移动无线衰落信道混合应用模型。通过实现瑞利衰落分布和对数正态分布,经线性和非线性变换可以得到Nakagami和Suzuki等分布。对提出的复合衰落模型进行仿真,仿真结果符合理论值。该混合衰落模型设计和仿真方法可以用于指导信道模拟器设计和通信系统仿真。     

矿井巷道多径信道模型研究

针对矿井无线信道快衰落多径信号幅度统计特性的可变性,介绍了描述矿井无线信道多径幅度分布的Rayleigh分布、Rician分布、Nakagami分布三种统计特性,提出了一种Nakagami幅度统计衰落信道的Simulink仿真模型。仿真结果显示,该模型能灵活地表述多径幅度分布不同的衰落程度,还可以改善信号性能,与其他衰落信道模型相比,有很大的优越性。     

改进的Summer算法及其在Turbo译码中的应用

由于Summer信噪比算法采用的信道模型为AWGN信道,他对衰落信道并不适用。通过在接收信号中增加了衰落因子,提出了一种能够应用于Nakagami衰落信道的改进Summer信噪比估计算法。仿真表明,运用改进的算法获得的信道信噪比信息非常接近实际的信噪比信息,同时,改进的Summer在线估计器使得Turbo译码性能得到明显的改善,而且不影响Turbo译码过程的总复杂度。     

空时相关复合衰落多输入多输出信道模型研究

针对多输入多输出(Multiple-Input Multiple-Output,MIMO)无线传播环境,综合考虑路径损耗、阴影衰落和多径衰落影响,提出一种基于Nakagami-Lognormal分布的相关复合衰落MIMO信道模型,推导并获得各信道自相关和互相关系数的理论表达式;提出一种基于谐波叠加思想的复合衰落MIMO信道仿真方法,并分析了该方法输出信道衰落的空时相关特性.数值仿真结果表明:仿真模型输出统计特性均与理论模型吻合;各子信道之间存在互相关性且随阴影衰落方差减小而下降,而自相关性则呈现快速起伏并缓慢下降的特性.     

噪声功率时变的瑞利慢衰落信道有限状态Markov模型

对衰落信道的准确建模对于自适应无线通信、认知无线电等应用中的信道预测具有重要意义。针对噪声功率存在时变特性的无线通信应用环境,提出了一种新的瑞利衰落信道的有限状态Markov模型。通过将接收信号的衰落电平进行离散化处理,建立了衰落电平区间与Markov模型状态之间的一一对应关系,推导了门限电平与状态转移概率和状态分布概率之间的理论关系式,并在此基础上提出了一种易于实现的基于等概率的信道模型。理论分析与仿真结果表明:在噪声功率时变的条件下,已有的基于信噪比的模型失效,而该模型能准确反映信道的衰落特性,最大相对误差小于7%。      

一种改进的C.Loo信道模型衰落因子算法

为更好地反映实际无线信道的特性,介绍一种改进的C.Loo信道模型衰落因子算法。原始C.Loo信道模型衰落因子算法中不考虑多普勒频移的影响,本文加载了多普勒频移对衰落因子的影响,并说明其合理性、可行性及优点。     

相关衰落信道下的一种层间联合自适应SR-ARQ传输机制

传统自适应传输机制在相关慢衰落信道下有较差的系统性能.针对相关衰落信道,提出了一种层间联合自适应传输机制.利用有限状态马尔可夫链来描述相关衰落信道,同时通过构建一个多状态马尔可夫系统模型来分析系统吞吐性能,并对调制方式和传输分组大小进行优化.另外,推导了系统平均吞吐性能的表达式.仿真结果显示所提出的自适应传输机制在相关衰落信道上能获得更好的系统性能.     

一种通用宽带MIMO信道模型

针对宽带的MIMO信道建模问题,提出一种通用多天线信道模型及其构造方法.该方法把克罗内克积应用到频域,同时提出频域散射衰落加权因子的概念,由此导出一种室外宽带MIMO散射分布模型.经过简化,该模型还可以应用到室内场景.仿真结果表明,这种通用信道模型能够准确的描述出宽带MIMO信道的视距(LoS)、非视距(NLoS)、室内外散射特征以及孔径效应.     

室内MIMO无线信道:模型和性能预测

提出了一种包含小尺度衰落、相对路径衰落和阴影衰落的室内MIMO信道模型,考虑到室内人员的流动性,并对模型的性能进行了预测,拓展了室内MIMO无线衰落信道模型的研究.实验结果验证了提出模型的性能.得到有用的结论:在低秩的信道,信道容量减少,能合理解释针孔信道容量,在高秩的信道,不考虑相对的路径衰落和阴影衰落的情况下,信道的容量随天线的数目增加和信号相关性的减少而增大.考虑相对的路径衰落和阴影衰落,在LOS传播环境中,若存在丰富的散射传播,信道容量要高得多.     

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.     

An average error probability evaluation in a fading environment using finite state Markov channel for LEO satellite communication system

Recent research shows that fading channels have a much larger capacity than anticipated with traditional approaches. This modern view on fading channels encouraged us to characterize these channels more precisely for better identification and use of wireless channel capacity.Since the Markov model is a natural way to approximate a channel with memory, many people have considered finite state first-order Markov modeling for describing a wireless communication channel.In this paper, we first introduce the relationship between a physical fading channel and the corresponding finite state Markov Model (FSMC) in case of low earth orbit (LEO) satellite communication system, which can be used for performance evaluation in an M-order quadrature amplitude-modulation (MQAM) transmission scheme by deriving an analytical expression of average bit error rate in Rayleigh fading channel. By establishing the FSMC, we show that the FSMC is accurate enough to evaluate the performance of MQAM modulation scheme to be implemented on board a LEO satellite communication system.     

On Information Rates of Time-Varying Fading Channels Modeled as Finite-State Markov Channels

We study information rates of time-varying flatfading channels (FFC) modeled as finite-state Markov channels (FSMC). FSMCs have two main applications for FFCs: modeling channel error bursts and decoding at the receiver. Our main finding in the first application is that receiver observation noise can more adversely affect higher-order FSMCs than lower-order FSMCs, resulting in lower capacities. This is despite the fact that the underlying higher-order FFC and its corresponding FSMC are more predictable. Numerical analysis shows that at low to medium SNR conditions (SNR ≲12 dB) and at medium to fast normalized fading rates (0.01 ≲fDT ≲0.10), FSMC information rates are non-increasing functions of memory order. We conclude that BERs obtained by low-order FSMC modeling can provide optimistic results. To explain the capacity behavior, we present a methodology that enables analytical comparison of FSMC capacities with different memory orders. We establish sufficient conditions that predict higher/lower capacity of a reduced-order FSMC, compared to its original high-order FSMC counterpart. Finally, we investigate the achievable information rates in FSMC-based receivers for FFCs. We observe that high-order FSMC modeling at the receiver side results in a negligible information rate increase for normalized fading rates fDT ≲0.01.     

Achievable Rates with Imperfect Transmitter Side Information Using a Broadcast Transmission Strategy

rdquoWe investigate the performance of the broadcast approach for various fading distributions, which correspond to different models of partial transmit channel state information (CSI). The first model considered is the quantized limited feedback. In this model, the receiver can send as feedback only a finite number of bits describing the fading gain. We derive the optimal power allocation for the broadcast approach for the quantized feedback model. For a Rayleigh fading channel, numerical results here show that if the feedback word can be longer than one bit, the broadcasting gain becomes negligible, due to diminished channel uncertainty. The second partial transmit CSI model is a stochastic Gaussian model with mean and variance information, which is commonly used for modeling the channel estimation error. In a single-input single-output (SISO) channel, this model also corresponds to the Ricean fading distribution, for which we derive maximal achievable broadcasting rates. We further consider a multiple-input single-output (MISO) channel, and derive the optimal power allocation strategy in a broadcast approach. Numerical results here show that uniform power allocation is preferable over beamforming power allocation in the region where broadcasting gain over single level coding is non-negligible.     

Mathematical modeling of rayleigh fading channels based on finite state markov chains

To mathematically model the Rayleigh fading channel, we propose a new method to partition the received Signalto-Noise ratio (SNR) range into a finite number of states and construct a finite state Markov chain (FSMC). Our method is based on the assumption that the transitions of the FSMC occur only between adjacent states. We provide numerical and simulation results to verify that our method constructs an accurate FSMC and our method outperforms existing methods.     

Finite-state Markov channel-a useful model for radio communicationchannels

The authors first study the behavior of a finite-state channel where a binary symmetric channel is associated with each state and Markov transitions between states are assumed. Such a channel is referred to as a finite-state Markov channel (FSMC). By partitioning the range of the received signal-to-noise ratio into a finite number of intervals, FSMC models can be constructed for Rayleigh fading channels. A theoretical approach is conducted to show the usefulness of FSMCs compared to that of two-state Gilbert-Elliott channels. The crossover probabilities of the binary symmetric channels associated with its states are calculated. The authors use the second-order statistics of the received SNR to approximate the Markov transition probabilities. The validity and accuracy of the model are confirmed by the state equilibrium equations and computer simulation     

Throughput Analysis of DS CDMA/Unslotted ALOHA Wireless Networks with Fixed Packet Length in Rayleigh Fading Finite-State Markov Channel Model

We propose the finite-state Markov channel (FSMC) model to the throughput analysis of DS CDMA/unslotted ALOHA wireless networks in the mobile environment. The FSMC model can characterize the correlation structure of Rayleigh fading process, and the degree of correlation depends on the Doppler frequency shift. The FSMC model is suited to the throughput analysis by queueing theory due to its Markov chain nature. The previous papers in DS CDMA/unslotted ALOHA wireless networks in Rayleigh fading consider a whole packet. They ignore that the channel gain or multiple access interference can change symbol-to-symbol. In our proposed analysis, both the channel gain and multiple access interference can change from symbol to symbol. It is not just a packet-level analysis in the previous papers, and is a more general symbol-level analysis. Our generalized scheme should be more suited to realistic Rayleigh fading in the mobile environment. We consider two cases: (1) the system without carrier load sensing protocol (CLSP) and (2) systems with CLSP. For both cases, we analyze the theoretical throughput by queueing theory for various averaged signal-to-noise ratios and Doppler frequency shifts, and the computer simulated throughput matches the theoretical throughput.     

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.     

Finite-state Markov modeling of fading channels

Wireless communication systems that operate through fading channels have become more diverse and complex. In the last ten years, there has been a growing interest for research and development of advanced wireless communications systems that employ multicarrier (MC) techniques. So far, applications of FSMC models for fading channels has been mainly limited to single carrier (SC) communications with very few exceptions [24], [47]. FSMC models are particulary suitable to represent and estimate the relatively fast flat-fading channel gain in each subcarrier. An unexplored avenue for research is to find appropriate FSMC models to represent MC fading channels. However, the number of TV-FFC gains to be modeled in the MC system is often much higher than in a SC system and a major challenge would be to keep the number of FSMC states to computationally manageable levels.     

Efficient rate allocation for progressive image transmission via unequal error protection over finite-state Markov channels

This paper proposes a unified framework for addressing progressive image transmission over noisy channels based on the finite-state Markov channel (FSMC) model. FSMC models are simple yet general enough to model binary symmetric, Gilbert-Elliott, and fading channels. They allow error sequence analysis that facilitates quantifying the statistical characteristics of the embedded bitstreams transmitted over FSMC in closed form. Using a concatenation of rate-compatible puncturing convolutional code and cyclic redundancy check code for error protection, we use a concatenation of rate-compatible punctured convolutional code and cyclic redundancy check code for error protection, which results in an unequal error protection (UEP) system, and find (sub-)optimal rate allocation solutions for our setup. By mapping fading channels to FSMCs, the JSCC problem is thus solved without the burden of simulations using an image-dependent lookup table. Fast algorithms are proposed to search for the optimal UEP. Experiments on embedded image bitstreams over FSMCs confirm our analytical results.