Generalized Markov modeling for flat fading

Babich, F.; Kelly, O.E.; Lombardi, G.

doi:10.1109/26.843121

Cited by 56 publications

(38 citation statements)

References 20 publications

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“…Therefore, the model designer can choose an appropriate balance between Markov model accuracy and complexity. In [17], a maximum CT depth of M = 7 was imposed when obtaining the context set and it was found that the actual context length for fading channels with f D T s ≥ 0.01 was always strictly less than seven in all constructed models.…”

Section: Ctp Methodsmentioning

confidence: 99%

“…CTP is the third technique for obtaining higher-order FSMC models for fading channels, proposed in [17] and [49]. Let us first assume that a sample-by-sample quantization of the fading channel gain sequence of length N is available and the discrete-valued fading channel gain sequence is denoted by u N 1 , The CTP method is an algorithm to estimate the contexts from the training sequence u N 1 and to simplify the full tree by merging contexts.…”

Section: Ctp Methodsmentioning

confidence: 99%

“…For Rayleigh fading, the pdf f A (a) was given in (2). Other statistical models used for the FSMC modeling of the fading amplitude include Rician [16], [17], [19], [49] and Nakagami m [23], [24]. Having an analytical expression for f A (a) is not necessary for obtaining FSMC steady-state probabilities.…”

Section: First-order Fsmc Models For the Tv-ffc Amplitude Or Receivedmentioning

confidence: 99%

“…This helps system designers analyze and improve performance measures in the physical or media access control layers. Since 1997, FSMC models have enabled closed-form or simulation-based analysis of system-level performance measures, such as packet throughput [20], [21], packet error distribution (PED) [18], and packet error rate (PER) [17] through bursty wireless channels. The bit error rate (BER) in more sophisticated communications systems that include receiver diversity has been studied using FSMC models in [23] and [24].…”

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confidence: 99%

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Finite-state Markov modeling of fading channels - a survey of principles and applications

Sadeghi

Kennedy

Rapajic

et al. 2008

IEEE Signal Process. Mag.

422

313

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In late 1950s and early 1960s, Gilbert and Elliott at Bell Labs were modeling burst-noise telephone circuits with a very simple two-state channel model with memory. This simple model allowed them to evaluate channel capacity and error rate performance through bursty wireline telephone circuits. However, it took another 30 years for the so-called Gilbert-Elliott channel (GEC) and its generalized finite-state Markov channel (FSMC) to be applied in the design of second-generation (2G) wireless communication systems. Since the mid 1990s, the GEC and FSMC models have been widely used for modeling wireless flat-fading channels in a variety of applications, ranging from modeling channel error bursts to decoding at the receiver. FSMC models are versatile, and with suitable choices of model parameters, can capture the essence of time-varying fading channels. This article's goal is to provide an in-depth understanding of the principles of FSMC modeling of fading channels with its applications in wireless communication systems. Digital Object Identifier 10.1109/MSP.2008 [ Parastoo Sadeghi, Rodney A. Kennedy, Predrag B. Rapajic, and Ramtin Shams ] While the emphasis is on frequency nonselective or flat-fading channels, this understanding will be useful for future generalizations of FSMC models for frequency-selective fading channels. The target audience of this article include both theory-and practice-oriented researchers who would like to design accurate channel models for evaluating the performance of wireless communication systems in the physical or media access control layers, or those who would like to develop more efficient and reliable transceivers that take advantage of the inherent memory in fading channels. Both FSMC models and flat-fading channels will be formally introduced. However, a background in time-varying fading communication channels is beneficial.We consider the FSMC modeling of fading channels from five distinct viewpoints. First, we provide a brief history of FSMC models and the FSMC modeling of flat-fading channels. Second, we define the parameters of FSMC models and discuss how these parameters can be derived from flat-fading channel statistics. We point out the trade-offs between model accuracy and complexity. Third, we categorize applications of FSMC models for fading channels into four categories and discuss the FSMC model applicability and accuracy in each application. We pay special attention to the effect of FSMC memory order on the model accuracy. Fourth, we consider the information-theoretical aspects of FSMC models and the FSMC modeling of fading channels. Finally, we present open questions and directions for future research. For easier access to the technical contents, the reader can refer to the "List of Acronyms" and "Notational Conventions." THE HISTORY OF FSMC 1957-1968: DEVELOPMENT OF FSMC MODELSThe study of finite-state communication channels with memory dates back to the work by Shannon in 1957 [1]. In [1], Shannon proved coding theorems for finite-state channels (FSCs) with discret...

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Section: Ctp Methodsmentioning

confidence: 99%

Section: Ctp Methodsmentioning

confidence: 99%

Section: First-order Fsmc Models For the Tv-ffc Amplitude Or Receivedmentioning

confidence: 99%

mentioning

confidence: 99%

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Finite-state Markov modeling of fading channels - a survey of principles and applications

Sadeghi

Kennedy

Rapajic

et al. 2008

IEEE Signal Process. Mag.

422

313

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“…The fading channel is modeled as a first order two state Markov model with certain assumptions [9], [10], [13], [14]. At any time, the channel has been in the one of the two possible states.…”

Section: The Channel Modelmentioning

confidence: 99%

A Simplified Approach to Estimate Bounds on Fading Channel Unavailability

Jain¹,

Vyavahare²,

Arya³

2009

IJCEE

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Abstract-A simplified approach is presented to evaluate fading channel unavailability. A fixed degree of certainty can be established and bounds on the same can be estimated. The slow fading channel is considered and is modeled as a discrete state Markov process. For such fading channel average value of outage time can be computed either using simulation or with the help of measured data set. But there is no indication of certainty that can be placed in its value. The paper presents an approach to estimate the range of outage rate and outage probability. Finally, bounds on channel unavailability are presented with the variation in outage time and number of outages. Proposed analysis can also be applied to fast fading channels when outage occurs frequently. Results may be used to provide higher order protocol performance evaluation and optimization. Examples are given to illustrate the results derived in the paper and to justify the approach presented.

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Discrete Rayleigh fading channel modeling

Aráuz

Krishnamurthy

Labrador

2004

Wireless Communications

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In order to understand the behaviour of upper-layer protocols and to design or fine tune their parameters over wireless networks, it is common to assume that the underlying channel is a flat Rayleigh fading channel. Such channels are commonly modeled as finite state Markov chains. Recently, hidden Markov models have also been employed to characterize these channels. In this paper, we study the different models that have been proposed along with the analysis of their validity. We start by presenting some preliminary concepts related to the modeling of the wireless communications channel. We then proceed to introduce finite state Markov channel models (FSMCs) along with the relations between them and the modulation schemes, error control protocols and channel coding. We propose and study the effects of taking into account the fading process in its characterization. We finish with a discussion on hidden Markov models for Rayleigh fading channel modeling.

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Generalized Markov modeling for flat fading

Cited by 56 publications

References 20 publications

Finite-state Markov modeling of fading channels - a survey of principles and applications

Finite-state Markov modeling of fading channels - a survey of principles and applications

A Simplified Approach to Estimate Bounds on Fading Channel Unavailability

Discrete Rayleigh fading channel modeling

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