Sampled-Data Consensus Control of MUSV Systems with Channel Fading and Transmission Delay

This paper studies sampled-data consensus control of a collection of unmanned surface vehicles(USV)operating in network environments with fading channels and time-varying transmission delay.The channel fading is modeled as each independent stochastic process whose probability distribution is known.By considering the effects of channel fading and transmission delay from sampler to the controller,a new MUSV system model is formulated in the framework of network.With the novel established model,stability analysis is given at first,then the sampled-data consensus controller is designed,which also extends to the robust control with wave-induced disturbance.The effectiveness of the presented method is demonstrated by numerical simulation.     

Network selection policy in multi-radio access environment using stochastic control theory

Network selection is crucial in improving the performance of heterogeneous wireless access systems.Most of previous work on network selection or radio resource allocation concentrates on the capability of each available network and ignores the time-varying nature of wireless media due to channel fading.However,the channel condition determines the state of each wireless network and plays a vital role in ensuring quality of service in multi-radio access environment.In this article,we propose a network selection policy using stochastic control theory considering the time-varying and stochastic character of wireless channels.The proposed scheme selects one network among different alternatives in each decision epoch according to the channel state of each network,which is modeled as finite-state Markov channel,with the objectives of increasing the data-rate,decreasing the bit error rate and minishing the delay.The procedure of network selection is formulated as a stochastic control problem,which can be solved using linear programming and primal-dual index heuristic algorithm.Simulation results are presented to show that network selection has great impact on the system performance,and the proposed scheme can improve the performance significantly.     

A Novel Event Model for Performance Analysis of IEEE 802.11 DCF

After considering the memory effect among series events occurring on the channel, we propose a novel event model to analyze the channel status more precisely. The memory effect is caused by the backoff freezing regulation of IEEE 802.11 Distributed coordination function （DCF）, which has been ignored before and thus resulted in the inaccurate evaluation of the network performance. Based on our new event model, the network performance of IEEE 802.11 DCF, including throughput, packet delay distribution and energy efficiency is analyzed. Simulation results show that our model is highly accurate.     

Distributed channel assignment combined with routing over multi-radio multi-channel wireless mesh networks

In order to realize the reduction of equipment cost and the demand of higher capacity,wireless mesh network(WMN) router devices usually have several interfaces and work on multi-channels.Jointing channel allocation,interface assignment and routing can efficiently improve the network capacity.This paper presents an efficient channel assignment scheme combined with the multi-radio link quality source routing(MR-LQSR) protocol,which is called channel assignment with MR-LQSR(CA-LQSR).In this scheme,a physical interference model is established:calculated transmission time(CTT) is proposed as the metric of channel assignment,which can reflect the real network environment and channel interference best,and enhanced weighted cumulative expected transmission time(EWCETT) is proposed as the routing metric,which preserves load balancing and bandwidth of links.Meantime,the expression of EWCETT contains the value of CTT,thus the total cost time of channel assignment and routing can be reduced.Simulation results show that our method has advantage of higher throughput,lower end-to-end time delay,and less network cost over some other existing methods.     

Fast capacity estimation algorithms for manets using directional antennas

In this letter,capacity estimation for Mobile Ad hoc NETworks (MANETs) using direc- tional antennas are studied.Two Matrix-based Fast Calculation Algorithms (MFCAs) are proposed to estimate the network capacity in a network scenario in which there is no channel sharing among multiple sessions and traffic is sensitive to delay with an end-to-end delay constraint.The first algo- rithm MFCA-1 is used to estimate network capacity in a situation where all links have the same delay. It estimates the maximum number of k-hop sessions in a network based on the k-hop adjacency matrix of the network.The second algorithm MFCA-2 is used to estimate network capacity in a situation where different links may have different delays.It calculates the maximum number of sessions in a network with an end-to-end delay constraint based on the adjacency matrix and the link-delay matrix of the network.Numerical and simulation results show that both MFCA-1 and MFCA-2 can calculate network capacity much faster than the well-known Brute-Force Search Algorithm (BFSA) but with the same accuracy.     

ROUTE SELECTION IN VIRTUAL CIRCUIT DATA NETWORKS BASED ON GENETIC ALGORITHMS

This paper addresses the problem of selecting a route for every pair of communicating nodes in a virtual circuit data network in order to minimize the average delay encountered by messages. The problem was previously modeled as a network of M/M/1 queues. Agenetic algorithm to solve this problem is presented. Extensive computational results across a variety of networks are reported. These results indicate that the presented solution procedure outperforms the other methods in the literature and is effective for a wide range of traffic loads.     

Data-flow in mobile edge computing networks: end-to-end performance analysis using stochastic network calculus

Mobile edge computing (MEC) networks can provide a variety of services for different applications. End-to-end performance analysis of these services serves as a benchmark for the efficient planning of network resource allocation and routing strategies. In this paper, a performance analysis framework is proposed for the end-to-end data-flows in MEC networks based on stochastic network calculus (SNC). Due to the random nature of routing in MEC networks, probability parameters are introduced in the proposed analysis model to characterize this randomness into the derived expressions. Taking actual communication scenarios into consideration, the end-to-end performance of three network data-flows is analyzed, namely, voice over Internet protocol (VoIP), video, and file transfer protocol (FTP). These network data-flows adopt the preemptive priority scheduling scheme. Based on the arrival processes of these three data-flows, the effect of interference on their performances and the service capacity of each node in the MEC networks, closed-form expressions are derived for showing the relationship between delay, backlog upper bounds, and violation probability of the data-flows. Analytical and simulation results show that delay and backlog performances of the data-flows are influenced by the number of hops in the network and the random probability parameters of interference-flow (IF).     

Algorithm and Performance Analysis of Optical Multistage Interconnection Network

A sorting algorithm based on the Batcher’s algorithm is presented. An 8×8 multistage interconnection network(MIN) is constructed. Applying wavelength division multiplexing(WDM) technology and integrating control mode, the designed network can realize non-blocking communication. The time delay of the MIN and the switches needed are also analyzed in theory, the deduced result conforms that the MIN designed previously is feasible. In the case of the same communication quality guaranteed, MIN uses the least switches and completes the communication more efficiently.     

Linear Precoder Design for Correlated Rician Fading Channel Under Imperfect CSI

In this paper, we have modeled a linear precoder for indoor multiuser multiple input multiple output(MU-MIMO) system with imperfect channel state information(CSI) at transmitter. The Rician channel is presumed to be mutually coupled and spatially, temporarily correlated. The imperfection with CSI is primarily due to the channel estimation error at receiver and feedback delay amidst the receiver and transmitter in CSI transmission. Along with, the insufficient spacing between the antenna at trans...     

V2X Offloading and Resource Allocation in SDN-Assisted MEC-Based Vehicular Networks

As an important application scenario of 5G, the vehicular network has a huge amount of computing data, which brings challenges to the scarce network resources. Mobile edge computing(MEC) sinks cloud services to the edge of network, which reduces the delay jitter caused by remote cloud computing. Software-defined networking(SDN) is an emerging network paradigm with the features of logic centralized control and programmability. In this paper, we construct an SDN-assisted MEC network architecture for the vehicular network. By introducing SDN controller, the efficiency and flexibility of vehicular network are improved, and the network state can be perceived from the global perspective. To further reduce the system overhead, the problem of vehicle to everything(V2X) offloading and resource allocation is proposed, where the optimal offloading decision, transmission power control, subchannels assignment, and computing resource allocation scheme are given. The optimization problem is transformed into three stages because of the heterogeneity of the offloaded tasks and the NP-hard property of the problem. Firstly, the analytic hierarchy process is used to select initial offloading node, then stateless Q-learning is adopted to allocate transmission power, subchannels and computing resources. In addition, the offloading decision is modeled as a potential game, and the Nash equilibrium is proved by the potential function construction. Finally, the numerical results show that the proposed mechanism can effectively reduce the system overhead and achieve better results compared with others’ algorithms.     

基于改进射线跟踪法和BP神经网络算法的室外微蜂窝毫米波信道特性研究

在28 GHz与39 GHz毫米波频段室外微蜂窝场景下,基于改进射线跟踪法和反向传播(back propagation,BP)神经网络算法对毫米波单发单收信道及单发多收信道进行建模仿真研究.在得到的无线信道仿真数据基础上,研究分析了毫米波信道的路径损耗、均方根(root-mean-square,RMS)时延扩展(del...     

面向6G的无线通信信道特性分析与建模

在28 GHz与39 GHz毫米波频段室外微蜂窝场景下,基于改进射线跟踪法和反向传播(back propagation, BP)神经网络算法对毫米波单发单收信道及单发多收信道进行建模仿真研究. 在得到的无线信道仿真数据基础上,研究分析了毫米波信道的路径损耗、均方根(root-mean-square, RMS)时延扩展(delay spread, DS)、接收功率等传播特性. 通过与现有文献的测量结果对比分析验证了改进射线跟踪法的正确性与有效性. 通过BP神经网络方法拟合得到的路径损耗模型参数结果与改进射线跟踪法仿真得到的路径损耗参数结果对比发现,两者吻合程度很高,验证了BP神经网络算法能很好地对室外微蜂窝毫米波信道大尺度参数进行预测. 同时,文中给出了一种普遍适用的用来表征室外微蜂窝视距(line-of-sight, LoS)与非视距(non-line-of-sight, NLoS)场景下28 GHz与39 GHz毫米波信道的路径损耗模型. 结果表明：LoS场景下的RMS DS和接收功率都小于NLoS场景下得到的结果;LoS场景与NLoS场景下RMS DS、水平方向到达角、多径簇的个数累积分布函数均服从高斯分布;RMS DS在毫米波频段微蜂窝场景下,随着频率的升高而增大,到达接收端的多径成簇呈现稀疏性.     

ArgMax and ArgMin: transitional probabilistic models in cognitive radio mesh networks

The erratic nature of spectrum availability and diversity imposes the use of a probabilistic framework for channel selection in cognitive radio networks protocol design. In this work, two probability distributions called ArgMax and ArgMin are proposed, which have broad applications in channel selection mechanisms, routing, and media access control protocols. The ArgMax probability distribution locates the maximum random variable among a set of random variables, while the ArgMin locates the minimum random variable. We show that the ArgMax probability distribution is a better candidate than the frequently used odds‐on‐mean probability distribution through theoretical analysis and simulation. The ArgMin probability distribution has a variety of applications and is shown to be useful in achieving a lower bound on the network's minimum spectral capacity. In simulation, we develop a probabilistic selection routing procedure (PSRP) that adopts the ArgMax probability distribution to guide packets throughout the network. The stochastic framework of probabilistic selection routing procedure is also an appropriate skeleton for building stochastic‐based routing protocols for dynamic networks such as cognitive radio networks. The simulation results suggest that ArgMax enables the routing scheme to adapt to the network dynamic more quickly and to more accurately locate the best candidate to route to than the odds‐on‐mean probability distribution. The ArgMax enhances the network throughput and end‐to‐end delay by over 30% when network load increases. Copyright © 2013 John Wiley & Sons, Ltd.     

Resequencing of Messages in Communication Networks

In this paper we study a message resequencing problem in a store-and-forward computer network where messages may go out of order while traversing logical channels. The logical channels are assumed to consist of multiple physical links which may be of different capacities. A message is dispatched to the fastest available link. Resequencing methods suggested in the literature [3] (resequencing at the channel level and resequencing at the virtual circuit level) are investigated for this link selection rule. The analysis is done on a two-node network connected by multiple links. The source node together with the set of outgoing links are modeled as anM/M/mqueue with servers of different rates. The resequencing delay distribution and the average resequencing delay are derived. On multihop networks, the effect of message length, link numbers, link service rates, and the resequencing methods on resequeucing delay are investigated by simulation.     

The impact of stochastic resource availability on cognitive network performance: modeling and analysis

Cognitive radio networks emerge as a promising solution for overcoming shortage and inefficient use of bandwidth resources by allowing secondary users (SUs) to access the primary users' (PUs) channel so long as they do not interfere with them. The dynamical spectrum availability makes SU's packet average delay one of the most important performance measures of a cognitive network. It is important to understand the nature of delay, as well as its dependence on PU behaviors. In this paper, we analytically model and analyze the dynamics of the spectrum availability and their impact on the SU's packet delay. The cognitive network is modeled as a discrete‐time queueing system. PU channel occupancy is modeled as a two‐state Markov chain. Our contribution in this paper is defining and characterizing the properties of the random process that describes the availability of the opportunistic resources. In addition, we apply the mean residual service time concept to achieve an analytical solution for the queueing delay. Moreover, inspired by the slotted Aloha system, we model the packet service mechanism and determine the manner in which it depends on the resource availability. The delay becomes unbounded if the spectrum availability dynamics are not carefully considered in network design. Copyright © 2015 John Wiley & Sons, Ltd.     

基于Markov状态转移方法的网络编码时延分析

网络编码已被验证是改善无线网络吞吐量、可靠性等性能的有效手段,但其对业务流时延性能影响的研究还不充分。针对得到广泛应用的随机线性网络编码,提出了一种基于马尔可夫状态转移的方法对单跳场景下单播业务流时延的期望值以及概率分布进行了分析,同时给出了相应的递推解析式,然后数值分析了有限域大小、信道丢失率、编码批次大小等编码参数对时延的影响。结果表明,随着有限域q的增大,时延的方差不断变小;时延的期望值与信道丢失率、编码批次大小几乎都成线性关系。     

基于QualNet的无人机数据链时延仿真

概述了无人机数据链的网络组成,介绍了通信网络仿真软件QualNet的功能特点及其架构,并在该软件平台下建立无人机数据链时延仿真模型,分析远近程无人机在不同MAC信道接入协议下的平均端到端时延和平均抖动.仿真结果表明,设计无人机数据链时可优先采用TDMA接入协议.     

室内环境下2.6GHz同时同频全双工自干扰信道测量与建模

目前,对同时同频全双工的自干扰信道特性尚未进行研究.针对这一现状,采用基于网络分析仪的信道测量平台,对室内环境下2.6GHz同时同频全双工自干扰信道特性进行测量与分析.基于实测数据统计分析,得出了传输损耗模型与均方根时延扩展统计模型.结果表明：传输损耗服从断点损耗模型,天线间距在大于1m的传输损耗指数为1.86,天线间距小于1m的传输损耗指数为1.52;均方根时延扩展的统计特性随着天线间距在不同范围而不同,在天线间距大于1m时的均方时延扩展服从lognormal分布,在天线间距小于1m时,RMS时延扩展在不同的天线间距下服从lognormal分布,并且其分布的均值与标准差与天线间距呈现线性关系.     

Flow control in high-speed communication networks

Flow control within a virtual circuit on a high-speed network is modeled using fluid-flow queues with a fixed propagation delay for each channel. Data from other virtual circuits are modeled as disturbances of the available service capacities. The resulting dynamics are shown to form a linear hybrid system. This model allows the design of flow control mechanisms on a mathematical basis. Simulation results show a marked improvement over window flow control for a single channel, and a marginal improvement over window flow control for a virtual circuit of three tandem channels