Fast simulation of diversity nakagami fading channels using finite-state markov models

Iskander, C.-D.; Mathiopoulos, P. Takis

doi:10.1109/tbc.2003.817096

Cited by 91 publications

(39 citation statements)

References 32 publications

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Section: Historical Background On Applications Of Fsmc Models For Fadmentioning

confidence: 99%

“…FSMC modeling of the TV-FFC amplitude a or the received SNR γ has been predominantly studied in the literature from 1995 onwards [13]- [21], [23]- [26], [28], [40]- [50]. In amplitude-only FSMC modeling, the effects of unknown channel phase on the received signal are not considered.…”

Section: First-order Fsmc Models For the Tv-ffcmentioning

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%

“…We now discuss some of the main partitioning methods used in the literature, which will be revisited in light of FSMC applications for fading channels later in the article. Equiprobable partitioning of fading amplitude is a reasonable, but the ad-hoc method that has been used in the literature [14], [15], [23], [35]. In this method, steady-state probabilities for all obtained FSMC states are equal to π k = 1/K.…”

Section: Selection Of Amplitude Region Boundariesmentioning

confidence: 99%

“…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].The potential benefits of incorporating FSMC memory into decoding algorithms at the receiver to achieve higher information rates has been known as early as 1989 [10]. Since the late 1990s, an active area of research has been to develop practical decoding techniques at the receiver using FSMC models for fading channels.…”

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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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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