一种滞后控制的马尔可夫链计算方法

提出了一种带有滞后控制结构的马尔可夫链状态概率及应用中相关性能参数的数学计算方法。根据马尔可夫归一化特性,分解马尔可夫链状态图,先计算整体简化状态,再计算局部状态,最后推导出整个马尔可夫链状态概率的计算公式。带滞后控制结构的马尔可夫链在各个领域都有非常广泛的应用,以它在低轨道卫星通信中信道资源的分配模型为例,通过比较模拟仿真的各个性能参数值和计算所得参数值,验证了提出的马尔可夫链分解计算方法的正确性。     

Performance modeling and analysis of the ADHOC MAC protocol for vehicular networks

The ADHOC MAC protocol is a classical MAC protocol for supporting reliable broadcast services in vehicular ad hoc networks (VANETs). This paper develops an analytical model for analyzing the access performance of the ADHOC MAC protocol. A Markov chain is first constructed to describe the number of vehicles which have acquired a timeslot successfully at the end of a frame when using the ADHOC MAC protocol. Based on the Markov model, an analytical model is then derived to describe the relationship between the frame length and the channel utilization. Based on the derived analytical model, an optimal frame length that maximizes the channel utilization is further obtained. Simulation experiments are conducted to verify the effectiveness of the analytical model.     

基于IEEE 802.11的多信道多址接入协议性能分析

 本文对一种基于IEEE 802.11 DCF协议多信道多址接入方案的性能进行了分析,在该接入方案中,节点在公共的控制信道上预约数据信道,随后在预约成功的数据信道上,进行数据分组的传输.本文采用马尔科夫链构建了控制信道的预约模型,给出了多信道吞吐量的理论分析算法.最后,通过仿真验证了理论分析结果与仿真结果的一致性,并给出了信道吞吐量与信道数、数据分组长度、节点密度、信道切换时延等参数之间的数值关系.     

Characterizing Temporal SNR Variation in 802.11 Networks

The analysis and design of wireless medium access control (MAC) protocols, coding schemes, and transmission algorithms can significantly benefit from an understanding of the channel quality variation. We attempt to represent channel quality variation using a finite-state birth–death Markov model. We outline a method to compute the parameters of the model based on measured traces obtained using common wireless chipsets. Using this Markov chain, we statistically evaluate the performance based on the channel quality, long-term correlations, and burst length distributions. Such a model significantly performs better than a traditional two-state Markov chain in characterizing 802.11 networks while maintaining the simplicity of a birth–death model. We interpret the variation of the model parameters across different locations and different times. A finite-state stationary model is amenable to analysis and can substantially benefit the design of efficient algorithms and make simulations for wireless network protocols faster.      

Decoding of convolutional codes on a sliding window during signal propagation in a multipath communications channel

Anoptimal recursive algorithm for joint interpolation of the Markov sequence of information symbols on a sliding window and for the interpolation with a fixed delay of the coder state has been synthesized under conditions of signal propagation in a multipath communications channel with known parameters. This algorithm makes it possible to perform the decoding of convolutional codes using the criterion of maximum of a posteriori probability. The analysis of the resultant algorithm was performed by using the computer statistical simulation.     

Performance analysis of a fully-connected, full-duplex CDMA ALOHAnetwork with channel sensing and collision detection

In cases where machines having bursty data are equally likely to transmit to one another, code-division multiple-access (CDMA) ALOHA which allows for an individual “virtual channel” for each receiving station may be a better multiple-access protocol than simple ALOHA. With the use of a “receiver-based code” multiple-access protocol, it is also possible for a station to listen to the channel of the intended receiver before transmission, and also abort transmission when it detects others transmitting on the same channel. This paper describes a model for a fully-connected, full duplex, and slotted CDMA ALOHA network where channel sensing and collision detection are used. The model is analyzed using a discrete time Markov chain and some numerical results are presented. For a system with a large number of users, where Markov analysis is impractical, equilibrium point analysis is used to predict the stability of the system, and estimate the throughput as well as the delay performance of the system when it is stable. Finally, a comparison is made with a simple channel sense multiple-access with collision detection (CSMA-CD) network, showing that a substantial improvement in the performance is achieved by the proposed network     

The performances study of IEEE 802.11e to support QoS in channel error environment

One of the most important functions in IEEE 802.11e is enhanced distributed coordination function (EDCF). EDCF is an enhanced version of IEEE 802.11 distributed coordination function (DCF) which provides a priority scheme by differentiating the inter‐frame space and the initial window size. We proposed a modified Markov chain model to study the EDCF priority scheme. We have theoretically analyzed the saturation throughput and delay by using the modified Markov chain model in non‐ideal channel scenario. We also have compared it with the Markov chain model that exists under ideal channel scenario. Simulations are also conducted to validate analytical results. Our study shows that the modified model under ideal channel scenario is better than that in channel error scenario. Copyright © 2011 John Wiley & Sons, Ltd.     

Multiframe video coding for improved performance over wirelesschannels

We propose and evaluate a multi-frame extension to block motion compensation (BMC) coding of videoconferencing-type video signals for wireless channels. The multi-frame BMC (MF-BMC) coder makes use of the redundancy that exists across multiple frames in typical videoconferencing sequences to achieve additional compression over that obtained by using the single frame BMC (SF-BMC) approach, such as in the base-level H.263 codec. The MF-BMC approach also has an inherent ability of overcoming some transmission errors and is thus more robust when compared to the SF-BMC approach. We model the error propagation process in MF-BMC coding as a multiple Markov chain and use Markov chain analysis to infer that the use of multiple frames in motion compensation increases robustness. The Markov chain analysis is also used to devise a simple scheme which randomizes the selection of the frame (amongst the multiple previous frames) used in BMC to achieve additional robustness. The MF-BMC coders proposed are a multi-frame extension of the base level H.263 coder and are found to be more robust than the base level H.263 coder when subjected to simulated errors commonly encountered on wireless channels.     

COMPLEX ENVELOPE THREE-STATE MARKOV MODEL BASED SIMULATOR FOR THE NARROW-BAND LMS CHANNEL

S-band measured land mobile satellite (LMS) propagation data were processed in order to obtain the parameters of a three-state Markov chain model for several environmental and elevation angle conditions. In this paper the results of this study are reported. The model was extended to produce a narrow-band complex envelope simulator. This simulator produces as an output a complex time series representing the received signal complex envelope variations. This approach allows relevant parameters of the channel such as phase variations, random FM, Doppler shift spectra, etc. to be present in the simulated time series. © 1997 by John Wiley & Sons, Ltd.     

Accurate Bluetooth Positioning Using Weighting and Large Number of Devices Measurements

One of the most efficient methods to reduce the dropping and blocking probabilities of the secondary users (SUs) in cognitive radio networks is channel sub-banding strategy. This means that when all the channels are occupied by the primary and secondary users, then the SUs’ channels can be divided into two sub-bands, and two SUs can use a sub-band, simultaneously. In this paper, we propose an opportunistic spectrum sharing system in cognitive radio networks in which, the channel sub-banding strategy is implemented. Furthermore, we describe the problem of channel sub-banding considering the spectrum sensing errors such as false alarm and miss-detection events for both initial and on-going SUs’ calls. Due to unreliable spectrum sensing by the SUs and subsequently possible interference with the primary users, we assume that both primary and secondary users may lose the channel due to the collision. The proposed model is analyzed by a two-dimensional Markov chain model and for performance evaluation, metrics such as blocking and dropping probabilities and channel utilization are derived. Numerical and simulation results show the accuracy of the proposed model which can be used in the evaluation of future cognitive radio networks’ performance.     

多类别终端无线局域网实时业务性能研究

针对具有不同MAC参数和应用类型的终端在IEEE802.11DCF无线局域网内共存的情况,使用离散Markov模型分析信道在饱和状态时的竞争特性,研究实时业务吞吐量、竞争延迟和丢失率等性能指标与协议参数和数据帧长度的关系。计算和仿真实验结果的对比验证了分析模型的正确性,表明部分终端协议参数的改变会引起所有业务性能变化,而合理调整最小竞争窗口和最大回退次数可以改善实时业务的性能。     

Performance evaluation of a receiver-based handshake protocol forCDMA networks

A receiver-based handshake (RBHS) protocol for multipacket channels, such as code-division multiple-access (CDMA) networks, is proposed and its throughput and delay performance is analyzed. This scheme is based on a sensing period and a handshake procedure which can avoid collision and eliminates unwanted transmissions. Several system models under different assumptions, such as completely orthogonal codes and very large processing gain (we call it perfect channel) or with quasiorthogonal codes (nonperfect channel), are investigated. We assume the channel error probability due to other users' interference to be a function of the number of transmissions in a given slot as well as other system parameters. Under a slotted structure with uniform traffic assumption, the system is modeled as a discrete-time two-dimensional Markov chain. The analysis, based on various channel conditions, demonstrates that the average throughput and delay are significantly improved over other spreading code protocols, especially when the channel is likely to accommodate more channel errors, and when the handshaking time is reasonably short compared to the average packet length     

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     

Saturation throughput analysis of IEEE 802.11 in the presence of non ideal transmission channel and capture effects

In this paper, we provide a saturation throughput analysis of the IEEE 802.11 protocol at the data link layer by including the impact of both transmission channel and capture effects in Rayleigh fading environment. Impacts of both non-ideal channel and capture effects, specially in an environment of high interference, become important in terms of the actual observed throughput. As far as the 4-way handshaking mechanism is concerned, we extend the multi-dimensional Markovian state transition model characterizing the behavior at the MAC layer by including transmission states that account for packet transmission failures due to errors caused by propagation through the channel. This way, any channel model characterizing the physical transmission medium can be accommodated, including AWGN and fading channels. We also extend the Markov model in order to consider the behavior of the contention window when employing the basic 2-way handshaking mechanism. Under the usual assumptions regarding the traffic generated per node and independence of packet collisions, we solve for the stationary probabilities of the Markov chain and develop expressions for the saturation throughput as a function of the number of terminals, packet sizes, raw channel error rates, capture probability, and other key system parameters. The theoretical derivations are then compared to simulation results confirming the effectiveness of the proposed models.     

Joint source-channel turbo decoding of entropy-coded sources

We analyze the dependencies between the variables involved in the source and channel coding chain. This analysis is carried out in the framework of Bayesian networks, which provide both an intuitive representation for the global model of the coding chain and a way of deriving joint (soft) decoding algorithms. Three sources of dependencies are involved in the chain: (1) the source model, a Markov chain of symbols; (2) the source coder model, based on a variable length code (VLC), for example a Huffman code; and (3) the channel coder, based on a convolutional error correcting code. Joint decoding relying on the hidden Markov model (HMM) of the global coding chain is intractable, except in trivial cases. We advocate instead an iterative procedure inspired from serial turbo codes, in which the three models of the coding chain are used alternately. This idea of using separately each factor of a big product model inside an iterative procedure usually requires the presence of an interleaver between successive components. We show that only one interleaver is necessary here, placed between the source coder and the channel coder. The decoding scheme we propose can be viewed as a turbo algorithm using alternately the intersymbol correlation due to the Markov source and the redundancy introduced by the channel code. The intermediary element, the source coder model, is used as a translator of soft information from the bit clock to the symbol clock     

Enhancement to IEEE 802.11 Distributed Coordination Function to Reduce Packet Retransmissions Under Imperfect Channel Conditions

In this paper, we provide an extended model for analytical analysis of IEEE 802.11 wireless local area networks under noisy wireless channel. A reservation stage is introduced in the Markov chain model to reduce unnecessary retransmissions in the case of transmission failure due to channel error. A lot of work has been carried out to enhance the performance of 802.11 distributed coordination function in the error free channel. Throughput enhancement of 802.11 medium access control protocol under error prone channel was still missing in the available literature. Through the analysis result it is shown that the proposed method significantly improves the performance of the backoff algorithm when the reservation stage is employed in the Markov chain model. The analysis result is validated by using the network simulator tool ns-2. The proposed modifications can be employed in the Markov chain model of any backoff algorithm.     

Principle phase decomposition: a new concept in blind seismic deconvolution

This paper outlines an exciting new approach for carrying out blind seismic deconvolution. In this algorithm, overlapping source wavelets are modeled as amplitude-modulated sinusoids, and blind deconvolution is carried out by initially determining the seismogram's principle phase components. Once the principle phases are determined, a Rao-Blackwellized particle filter (RBPF) is utilized to separate the corresponding overlapping source wavelets. This deconvolution technique is referred to as principle phase decomposition (PPD). The PPD technique makes use of the fact that in reflection seismology the discrete convolution operation can be represented as the summation of several source wavelets of differing arrival times. In this algorithm, a jump Markov linear Gaussian system (JMLGS) is defined where changes (jumps) in the state-space system and measurement equations are due to the occurrences and losses of overlapping source wavelet events. The RBPF obtains optimal estimates of the possible overlapping source wavelets by individually weighting and subsequently summing a bank of Kalman filters (KFs). These KFs are specified and updated by samples drawn from a Markov chain distribution that defines the probability of the overlapping source wavelets that compose the JMLGS. In addition, hidden Markov model filters are utilized for refining the principle phase estimates.     

Detection of baseband signals using a delta modulator

The performance of a digital delta modulator when used as a repeater for binary non-return-to-zero signals between a noisy channel and an error-free link is analyzed. A Markov chain is used to model the accumulator output (observation process) of the device, and a Bayes test with a probability of error criterion is formulated to evaluate its performance in additive band-limited Gaussian channel noise. The key design parameters of sampling rate and accumulator range are varied for computation of performance degradation relative to the optional matched filter. Numerical results are presented that demonstrate the feasibility of this technique