Channel Modeling for Multiple Satellite Broadcasting Systems

In this contribution we present the results of a study on land mobile satellite channel models for satellite systems with multiple satellites. The slow fading of our channel model for several satellites is based on a Markov channel state model for joint processes while the Probability Density Function (PDF) of the signal amplitude within each state is fitted to the Loo distribution. The correlation between two satellite channels and the channel spatial autocorrelation have also been studied. We show that a channel state model that uses a Markov state model of order one or of a fixed higher order is not appropriate if the state duration is of very high importance, which can be the case in the process of system planning. Therefore, we propose a dynamic higher order Markov state model for joint processes that depends on the current state duration. This approach models precisely any PDF of the channel state duration for both single and multiple satellite broadcasting systems while having a significantly lower computational complexity than a fixed higher order Markov model. It models the channel states of the whole system correctly, as well as the channel states of each satellite observed independently. It is able to capture the state correlation between multiple satellites. We also study possible approximations of the proposed models in order to reduce their computational complexity while having a good PDF match. Our channel state models are validated by measurements.      

A Markov-Based Channel Model Algorithm for Wireless Networks

Techniques for modeling and simulating channel conditions play an essential role in understanding network protocol and application behavior. In [11], we demonstrated that inaccurate modeling using a traditional analytical model yielded suboptimal error control protocol parameters choices. In this paper, we demonstrate that time-varying effects on wireless channels result in wireless traces which exhibit non-stationary behavior over small window sizes. We then present an algorithm that extracts stationary components from a collected trace in order to provide analytical channel models that, relative to traditional approaches, more accurately represent characteristics such as burstiness, statistical distribution of errors, and packet loss processes. Our algorithm also generates artificial traces with the same statistical characteristics as actual collected network traces. For validation, we develop a channel model for the circuit-switched data service in GSM and show that it: (1) more closely approximates GSM channel characteristics than traditional Markov models and (2) generates artificial traces that closely match collected traces' statistics. Using these traces in a simulator environment enables future protocol and application testing under different controlled and repeatable conditions.     

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%。      

Application layer QoS optimization for multimedia transmission over cognitive radio networks

In cognitive radio (CR) networks, the perceived reduction of application layer quality of service (QoS), such as multimedia distortion, by secondary users may impede the success of CR technologies. Most previous work in CR networks ignores application layer QoS. In this paper we take an integrated design approach to jointly optimize multimedia intra refreshing rate, an application layer parameter, together with access strategy, and spectrum sensing for multimedia transmission in a CR system with time varying wireless channels. Primary network usage and channel gain are modeled as a finite state Markov process. With channel sensing and channel state information errors, the system state cannot be directly observed. We formulate the QoS optimization problem as a partially observable Markov decision process (POMDP). A low complexity dynamic programming framework is presented to obtain the optimal policy. Simulation results show the effectiveness of the proposed scheme.     

Linear-Complexity Models for Wireless MAC-to-MAC Channels

Wireless local area networks suffer from frequent bit-errors that result in Medium Access Control (MAC) layer packet drops. Bandwidth and media quality constraints of real-time applications necessitate analysis and modeling at the “MAC-to-MAC wireless channel”. In this paper, we propose and evaluate stochastic models for the 802.11b MAC-to-MAC bit-error process. We propose an Entropy Normalized Kullback-Leibler (ENK) measure to accurately evaluate the performance of the models. We employ this measure to demonstrate that the traditional full-state Markov chains of order-10 and order-9 are required for accurate representation of the channel at 2 and 5.5 Mbps, respectively. However, the complexity of this modeling paradigm increases exponentially with respect to the order. For many real-time and non-real-time applications, which require (or could benefit significantly from) accurate modeling, the high complexity of full-state high-order Markov models makes them impractical or virtually ineffective. Thus, we propose two new linear-complexity models, which we refer to as the short-term energy model (SEM) and the zero-crossing model (ZCM). These models, which constitute the most important contribution of this paper, constrain the complexity to increase linearly with the model order. We illustrate that the linear-complexity models, while yielding orders of magnitude reduction in complexity, provide a performance comparable to that of the exponential complexity full-state models. Within the linear-complexity context, we illustrate that the zero-crossing model perform better than its short-term energy counterpart. Finally, for varying window sizes and due to its low complexity, we show that the zero-crossing model can be adapted in real-time. Such an adaptive model provides accurate channel modeling and characterization for rate adaptive applications.Syed Ali Khayam received the B.S. degree in computer systems engineering from National University of Sciences and Technology (NUST) Pakistan in 1999. He secured the Pakistan Higher Education Commission M.S./Ph.D. scholarship to pursue post graduate studies at Michigan State University (MSU). He completed his M.S. in Electrical Engineering from MSU in 2003. He is currently a Ph.D. candidate in the Department of Electrical and Computer Engineering at MSU. He also worked at Communications Enabling Technologies where he led a design team which realized various modules of a Voice-over-IP system-on-chip. His research interests include statistical analysis and modeling of computer (and in particular wireless) networks, network security, cross-layer protocol design, real-time multimedia communications over IP-based networks, and VLSI chip design.Hayder Radha received the B.S. degree (with honors) from Michigan State University (MSU) in 1984, the M.S. degree from Purdue University in 1986, and the Ph.M. and Ph.D. degrees from Columbia University in 1991 and 1993 (all in electrical engineering). He joined MSU in 2000 as Associate Professor in the Department of Electrical and Computer Engineering. Between 1996 and 2000, Dr. Radha worked at Philips Research USA where he initiated the Internet Video project and led a team of researchers working on scalable video coding and streaming algorithms. Dr. Radha is a Philips Research Fellow. Prior to working at Philips, Hayder Radha was a Distinguished Member of Technical Staff at Bell Labs where he worked between 1986 and 1996 in the areas of digital communications, signal/image processing, and broadband multimedia. His research interests include image and video coding, wireless technology, multimedia communications and networking. He has more than 20 patents in these areas. Dr. Radha served as Co-Chair and Editor of the ATM and LAN Video Coding Experts Group of the ITU-T in 1994–1996.     

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.     

Discrete Rayleigh fading channel modeling

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. Copyright © 2004 John Wiley & Sons, Ltd.     

Efficient channel utilization for real-time video in OVSF-CDMA systems with QoS assurance

In this paper, the utilization of real-time video service in the downlink of an orthogonal variable spreading factor code division multiple access (OVSF-CDMA) system is studied. By modeling the video traffic and wireless channel as a joint Markov modulated process, and properly partitioning the states of the Markov process, an adaptive rate allocation scheme is proposed for real-time video transmission with quality of service provisioning while achieving high channel utilization. The scheme is applicable for packet switching and frame-by-frame real-time video transmission, and incorporates both the physical layer and network layer characteristics. For QoS provisions, the closed form expressions of packet delay and loss probability are derived based on the Markov model. Analytical and simulation results demonstrate that the proposed scheme can significantly improve the channel utilization over the commonly used effective bandwidth approach.     

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     

Performance Analysis of IEEE 802.15.4 MAC Protocol with ACK Frame Transmission

A common way of achieving reliable data transmission in wireless sensor network applications is by using a retransmission mechanism with medium access control (MAC) level acknowledgements. The IEEE 802.15.4 standard, which is widely acknowledged as the state-of-the-art PHY/MAC standard for wireless sensor networks, supports MAC-level acknowledgements and retransmissions. In this paper, based on a three-dimensional discrete-time Markov chain, we propose a new analytical model to analyse the performance of the IEEE 802.15.4 MAC protocol with retransmission and MAC level acknowledgements under unsaturated traffic conditions. Further, we present a simplified version of the proposed analytical model with some approximations. Using the proposed analytical models, we evaluate the network performance in terms of the aggregate channel throughput, average power consumption of a node, frame discard ratio, and frame delivery ratio. The analytical results are substantiated through ns?2 simulations. The effects of the frame arrival rate, number of nodes, frame length and various MAC parameters, on the performance of the network are discussed. The results of both analytical models are compared and it is shown that the simplified model provides an acceptable accuracy with less computational complexity.     

Delay statistics of cooperative automatic repeat request over wireless networks with link adaptation

This paper proposes a method to analyze the delay distribution at the transmitter side for cooperative diversity wireless networks with link adaptation, which uses decode‐and‐forward as a relay strategy. The equivalent end‐to‐end channel model is captured by a finite state Markov channel model representing the multiple states of the Nakagami fading channel, and the delay statistics are obtained by using matrix geometry method. Cooperative diversity wireless network has a better delay performance compared with noncooperation wireless network. Copyright © 2012 John Wiley & Sons, Ltd.     

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     

用于多信道无线网络的综合链路速率分配算法

This paper presents a link allocation and rate assignment algorithm for multi-channel wireless networks. The objective is to reduce network conflicts and guarantee the fairness among links. We first design a new network model. With this network model, the multi-channel wireless network is divided into several subnets according to the number of channels. Based on this, we present a link allocation algorithm with time complexity O(l2 ) to allocate all links to subnets. This link allocation algorithm adopts conflict matrix to minimize the network contention factor. After all links are allocated to subnets, the rate assignment algorithm to maximize a fairness utility in each subnet is presented. The rate assignment algorithm adopts a near-optimal algorithm based on dual decomposition and realizes in a distributed way. Simulation results demonstrate that, compared with IEEE 802. 11b and slotted seeded channel hopping algorithm, our algorithm decreases network conflicts and improves the network throughput significantly.     

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.     

A Partial Ordering of General Finite-State Markov Channels Under LDPC Decoding

A partial ordering on general finite-state Markov channels is given, which orders the channels in terms of probability of symbol error under iterative estimation decoding of a low-density parity-check (LDPC) code. This result is intended to mitigate the complexity of characterizing the performance of general finite-state Markov channels, which is difficult due to the large parameter space of this class of channel. An analysis tool, originally developed for the Gilbert-Elliott channel, is extended and generalized to general finite-state Markov channels. In doing so, an operator is introduced for combining finite-state Markov channels to create channels with larger state alphabets, which are then subject to the partial ordering. As a result, the probability of symbol error performance of finite-state Markov channels with different numbers of states and wide ranges of parameters can be directly compared. Several examples illustrating the use of the techniques are provided, focusing on binary finite-state Markov channels and Gaussian finite-state Markov channels. Furthermore, this result is used to order Gilbert-Elliott channels with different marginal state probabilities, which was left as an open problem by previous work.     

A Novel Optimal Channel Partitioning Algorithm for Integrated Wireless and Mobile Networks

How to efficiently support multi-class services is a very important issue in integrated wireless and mobile networks because each type of services has distinct characteristics and quality of service (QoS) requirements. This paper presents an efficient algorithm for near optimal channel allocation when different types of services are to be provided in the next generation integrated wireless and mobile networks. We specifically propose a preemptive priority scheme for an integrated wireless and mobile network by first dividing channels into three independent groups and classifying traffic into four different types. The proposed system is modeled by a multi-dimension Markov chain model. Then such a model is used to obtain a set of relations that correlate performances with various system parameters. A novel recursive algorithm is developed to determine the minimal number of channels in each channel group that would be necessary to satisfy the QoS requirements. We also investigate the impact of load ratio for different types of traffic on channel assignment. Finally, we discuss some limitations of our approach and indicate possible future work. We believe that the partitioning scheme proposed in this paper can become a starting point for analysis of future integrated wireless and mobile networks.     

Impact of Doppler spread and adaptive modulation on TCP throughput in Rayleigh fading channels

A number of wireless systems have recently adopted adaptive modulation (AM) schemes to improve its efficiency. In this letter, our aim is to study the impact Doppler spread and adaptive modulation has on transmission control protocol (TCP) throughput in Rayleigh fading channels. We consider a finite state Markov channel (FSMC) model, which is a useful model for analyzing radio channel with nonindependent fading. Furthermore, we use a Markov model for TCP evolution and evaluate the TCP performance by computer simulations. In our simulations we have compared the TCP Reno scheme with TCP Tahoe scheme. The results indicate that a large Doppler spread leads to lower TCP throughput due to more frequent transitions of channel states and modulation schemes which make it difficult for the TCP congestion control mechanism to accommodate the dynamic link characteristics.     

GA Optimized HMM Error Model for OFDM

Finite-state HMM error models are an established powerful tool for capturing temporal characteristics of fading channels. They make network simulations much more practical and fast while developing and testing higher layer wireless system protocols and designing interleaving and FEC schemes. This paper has introduced two new Genetic Algorithm (GA) based approaches, namely, GA-S and GA-B as an alternative to HMM error models, for the accurate learning of error statistics of autocorrelation function (ACF) and error-run distributions. Validity comparisons of fit obtained show that the GA method is better than both the conventional Baum–Welch algorithm (BWA) and Semi-hidden Markov model (SHMM) methods, even when the target sequences are as short as 1000 in length. The independent elements of the [A] and [B] parameters of BWA used as chromosomes of the population space are used for error generation within the Genetic Algorithm. Mean square error of statistical properties of the error sequences is used to determine fitness of the chromosomes unlike other works using average log-likelihood ratio. Applicability has been tested by numerical simulations using error sequences of different lengths as well as target sequences of fixed length from an OFDM transceiver system under different fading rates. A T _s spaced time-delay model of the propagation channel with a fixed power delay profile has been used. For slow faded channels or when long sequences of error free intervals poses difficulties for BWA training, the GA method proves to be an excellent alternative for fast and accurate modeling of the error bursts. Unlike the computationally cumbersome BWA or the simplified SHMM approach, the GA model is capable of arriving at desired levels of accuracy with two to three states, in contrast to the Markov models needing a much higher number of states.

     

Determination of Reliability Parameters of a Digital Multiplex Frame Strategy Using Markov Chains and a State Reduction Method

This paper discusses the analysis of a digital multiplex framing strategy to determine certain reliability parameters for the frame synchronization system. The only model found suitable for determining the desired parameters is a Markov chain with ~ 5 × 105 states. To make meaningful calculations using this Markov chain, a state reduction method is employed. This method makes possible a determination of mean time between failures, availability, and several other parameters as a function of channel error rate. The model and analysis are applied to a framing strategy of greater complexity than those reported in the literature. The analysis makes it possible to include several effects, such as channel errors during the frame search operation, which are not possible with other methods.     

Cooperative MIMO channel models: A survey

Cooperative multiple-input multiple-output technology allows a wireless network to coordinate among distributed antennas and achieve considerable performance gains similar to those provided by conventional MIMO systems. It promises significant improvements in spectral efficiency and network coverage and is a major candidate technology in various standard proposals for the fourth-generation wireless communication systems. For the design and accurate performance assessment of cooperative MIMO systems, realistic cooperative MIMO channel models are indispensable. This article provides an overview of the state of the art in cooperative MIMO channel modeling. We show that although the existing standardized point-to-point MIMO channel models can be applied to a certain extent to model cooperative MIMO channels, many new challenges remain in cooperative MIMO channel modeling, such as how to model mobile-to-mobile channels, and how to characterize the heterogeneity and correlation of multiple links at the system level appropriately.