基于跳频的自适应频谱共享方案

 本文针对异种网络之间的频谱共享问题,提出了基于跳频的自适应频谱共享方案.该方案中 ,频谱注册网络负责配置跳频频率表等跳频参数,并且将其在覆盖区域内广播.频谱共享网络中的可重构终端（CR-MTs）使用认知无线电（CR）技术对周围频谱进行监测,通过跳频频谱共享策略实现通信.本文设计了跳频频谱共享的信号发射模型和信令交换机制,提出了不同情况下的干扰避免（IA）策略.最后,对跳频频谱共享方案的性能进行了分析,基于干扰计算模型得到的仿真结果表明该方案具有较好的IA性能.     

基于跨层的加权自组网路由协议的设计及实现

以优化的链路状态路由（Optimized Link State Routing,OLSR）协议为原型,为无线移动自组织网络（Mobile Ad Hoc Networks,MANETs）设计了基于跨层的速率自适应的加权路由协议。该协议充分考察无线信道的时变性质,在路由计算过程中通过跨层信息共享节点的邻居关系及获取节点的当前发送速率,削减了协议的开销。将无线链路的速率与跳数相结合,设计了一种新的路由度量规则。仿真结果表明,提出的加权路由协议能够显著降低网络层的路由开销,提升网络吞吐量,降低端到端时延。     

基于模糊逻辑的无线网络流量自适应控制

文章在分析现有提高无线TCP性能方案的基础上，提出一种新的流量控制方法，即基于显式窗口反馈的无线网络流量控制方案。在Snoop中引入有线网络的显示窗口自适应（EWA）算法，通过对BS共享缓存的实时监测，应用模糊控制算法预测当前拥塞窗口（cwnd）的大小，并显式反馈给发送端，使TCP的发送窗口能快速响应网络负荷状况的变化．避免分组的丢失。仿真结果表明．该方法增强了网络对拥塞的自适应性以及对无线信道差错的实时处理能力．提高了网络的吞吐量。     

IRS辅助的感知增强认知无线电网络资源分配方案

在过去的几十年里,大部分可用频谱已被用于高速通信服务。这导致了无线通信系统中的频谱资源稀缺问题。另一方面,大量可用频谱的利用率并不高。为提升通信系统的频谱利用率,学界提出了基于共享的认知无线电技术。认知无线电允许次用户与主用户共享频谱资源,对于提升无线通信网络的频谱效率十分重要,然而目前基于认知无线电的通信网络存在着低信噪比情况下感知性能低下、严苛干扰条件下性能提升受限等缺点。最近,智能反射面（Intelligent Reflecting Surface,IRS）被广泛应用在无线通信的各个领域,可以智能调控无线传输环境以满足频谱和能效的高要求。为了进一步提升认知无线电感知性能与频谱效率,提出了一种新颖的IRS辅助的感知增强频谱共享认知无线电网络。针对此网络,建立了次用户和速率最大化优化问题,联合优化次基站波束赋形向量、智能反射面相移矩阵、感知时间。因存在变量耦合,所构建的优化问题是非凸的,提出一种基于块坐标下降（Block Coordinate Descent,BCD）的迭代算法以交替优化波束形成和智能反射面相位以及感知时间。以逐次凸逼近（SuccessiveConvex Approx...     

基于正交频分复用的无线认知传感器网络研究

OFDM（正交频分复用）的频谱感知、频谱成形能力及其灵活性、适应性,使其成为WCSN（无线认知传感器网络）的最佳传输技术,可以执行DSA（动态频谱接入）和频谱共享功能。文章给出0FDM的实现原理,研究OFDM系统中的同步问题,分析信道估计面临的两个主要挑战．推导连续和离散时间信号的PAPR（峰均功率比）表达式,分析OFDM系统中的自适应传输优化问题．总结频谱成形的重要性。探讨OFDM在无线认知传感器网络中的应用场景。     

基于剩余路径跳数的动态优先调度实现区分服务EF PHB

Internet区分服务（DiiffServ）中EF PHB(Expedited Forwarding Per Hop Behavior)提供严格的端到端延迟保证，其实现机制和性能是当前研究的热点。随着可扩展性成为核心网络考虑的关键因素，一般用简单的FIFO高度实现EF PHB。FIFO实现问题在于最坏的端到端延迟与流经历的最大跳数成正比，结果降低了网络最坏延迟性能，并影响了整个网络的总体利用率。文章在分析并比较FIFO实现以及考虑流跳数因素的绝对跳数优先（HBAP）实现、相对跳数优先（HBRP）实现的延迟性能基础上，提出了用基于剩余路径跳数的动态优先（DHBP）调度实现EF PHB。理论分析和实验结果表明，基于剩余路径跳数的动态优先调度算法可以平衡不同跳数流的端到端延迟性能，从而减小网络最坏的端到端延迟，并有效地提高了网络 选用率，最坏延迟性能明显优于FIFO和绝对跳数优先调度，与性能最优的相对跳数优先调度相似，并将计算复杂度降为0(1)。     

非理想信道感知下的频谱共享容量的理论分析

在现有的以理想信道感知为条件的机会频谱共享容量分析基础上,重点讨论非理想感知对机会频谱共享中次用户信道容量的影响。关注两条不同传输途径的信道,一条是从次用户发送端到次用户接收端的无线信道,另一条是次用户发送端到主用户接收端的无线信道。以主用户接收端功率受限作为约束条件,得到了关于非理想信道信号噪声比条件下机会频谱共享的次用户信道容量的关系表达式。首先分析次用户发送端到主用户接收端信道和次用户发送端到次用户接收端信道为非对称时次用户的信道容量,其次分别探讨不同衰落信道模型下两条信道上感知（包括信道估计和预测）误差为对称和非对称结果时,次用户信道容量的变化。     

安全保障：无线Mesh网络中支持QoS的DSR路由协议的改进与实现

随着无线Mesh网络传输多媒体业务需求的增加,要求网络支持服务质量（QoS）,本文基于DSR协议设计了一个支持QoS的路由协议算法QDSR（QoS-DSR）。该算法保证了数据流的带宽、时延的QoS需求,根据路径跳数和节点拥塞情况定义路由代价函数,选择最优路径。仿真结果表明,与DSR相比,QDSR提高了网络吞吐量,降低了平均端到端延时,提高了网络利用率,更好地满足业务的QoS需求,并且具有更强的适用性和可扩展性。     

动态频谱分配与频谱共享研究综述

文中针对当前无线频谱政策和无线频谱技术局限所导致的频谱整体利用率低的问题,分析了能有效提高频谱利用率的动态频谱分配和共享技术的研究现状,包括相邻和分片动态频谱分配技术,共存和覆盖式频谱共享技术,感知无线电技术,以及频谱池技术,并讨论了其未来的研究方向,尤其是感知无线电和基于OFDM的频谱池方法.     

无线Mesh网络中数据传输可靠性的保障策略

无线Mesh网技术是一种新的无线网络技术,其核心是任何无线设备节点都可以同时作为接入点（AP）和路由器,网络中的每个节点都可以发送和接收信号,每个节点都可以与一个或者多个对等节点进行直接通信。无线Mesh网中需要考虑完成通信的多跳过程中产生的数据传输可靠性的保障问题。使用第三代合作伙伴计划（3GPP）的系统架构中提出的混合自动重传请求（HARQ）和自动重传请求（ARQ）功能,可以对多跳链路数据可靠传输进行保障。其中针对HARQ提出了逐跳和端到端两种方法,而对于ARQ功能除了逐跳和端到端两种方法外还增加了最后一跳的保障机制。从协议栈构架设计的角度,根据HARQ和OARQ机制提出了3种解决方法：分层机制、Relay ARQ机制、多剧SARQ机制。     

Study on dynamic routing and spectrum assignment in bitrate flexible optical networks

The exponential growth of Internet traffic necessitates high-capacity optical networks and has also highlighted the importance of bandwidth-flexible and multi-granularity transport platforms. Improving both transport capacity and bandwidth flexibility is a significant challenge in optical networks. A bitrate flexible network architecture that is based on orthogonal frequency division multiplexing has been proposed as a promising solution for meeting this challenge. In the current study, we focus on the online routing and spectrum assignment problems in the aforementioned network architecture and introduce a general solution for dynamic bitrate flexible traffic in distributed environments. A novel spectrum representation method based on continuous spectrum segments is introduced into the networks. Segment-based routing and signaling mechanisms provide general solutions that support both the conventional slot-based networks and the ideal fully gridless networks. The routing algorithms and spectrum selection approaches are demonstrated and compared in a simulation. Performance estimation indicates that random spectrum segment assignment achieves the lowest capacity blocking rate in light traffic, whereas the adaptive routing plus minimum residual spectrum scheme obtains the lowest capacity blocking rate under heavy traffic.     

CRN中一种优化的数据传输方案

在认知无线电网络(CRN)中,如何有效地实现认知用户间快速可靠的数据传输是目前的研究热点。针对现有传输方案的不足,提出了一种优化的数据传输方案。在考虑节点发射功率和负载均衡的约束条件下,基于对认知用户间链路可靠性预测,联合频谱分配与按需路由策略实现认知用户数据的最优化传输。仿真实验表明,在减少路由重构次数的同时,较大地提高了系统的吞吐量。     

基于地理位置的无线传感器网络路由协议

基于地理位置的路由协议是无线传感器网络路由协议研究的一个重要方向。利用位置信息指导路由的发现、维护和数据转发,能够优化路径选择,减少路由能耗,实现网络的全局优化。从限制洪泛机制、虚拟分区机制、最优路由确认机制3个方面,可以看出地理位置信息在路由协议中的重要性。     

Scaling Group Communication Services with Self-adaptive and Utility-driven Message Routing

Group communication services typically generate large multicast data streams. Delivering such massive data streams to the end system nodes at the edge of the Internet has been a challenging problem in terms of high stress on the network links and high demand on network resources and routing node capacities. Most of existing research has been dedicated on geo-distance based routing with various optimizations to alleviate the performance impact on geo-distance based routing due to unpredictable network dynamics. Most representative techniques are targeted at reducing the delivery path length or optimizing routing path by utilizing network locality. In this paper, we identify the inefficiency of geo-distance based routing protocols in many existing multicast overlay networks in terms of both resource utilization and group communication efficiency. To address this issue, we develop a utility-based routing scheme (UDR) that can provide efficient group communication services in a decentralized geographical overlay network. Our approach makes three unique contributions. First, we introduce a utility function to refine the geo-distance based routing in such a way that the routing path selection can carefully incorporate both geo-distance based metric and the network latency. Second, we enhance our utility driven routing scheme with self-adaptive capability by considering the nodes?? state and network density. Thus, nodes in the multicast network can dynamically accommodate the changes of network conditions based solely on their local knowledge about the network. Third, we devise a suite of optimization techniques to minimize the maintenance cost and computational complexity of our self-adaptive and utility-drive routing scheme. We evaluate our approach through extensive experiments based on a realistic network topology model and show that the UDR method is highly scalable and it effectively enhances the multicast delivery efficiency for large scale group communication services compared to existing geo-distance based routing protocols.     

Energy‐efficient management using a traffic‐oriented routing scheme for cognitive radio networks

This paper elaborates on a traffic manipulation routing scheme that associates the moments of the traffic, targeting the maximization of the energy conservation, as well as the effective resource management of the network nodes. The energy conservation is achieved through the data flow coordination, in association with the data traffic volume and the resource exchange, between the nodes that exploit radio spectrum access in cognitive radio networking architectures. The routing scheme that is proposed in this paper interrelates the backward difference of traffic moments for each node based on a series model, together with the sleep‐time period, towards reflecting this measurement to the minimization of the nodes activity durations to achieve energy conservation. The effective operation of the routing scheme is achieved by exploiting a signalling mechanism that was adopted for the proper communication of the nodes over the available radio spectrum parts, such as the television white spaces. Simulation tests were conducted towards examining the validity of the proposed routing scheme via multiple performance evaluation experiments. Simulation results have shown the offered reliability and the efficiency of the proposed traffic‐aware scheme, in reference to the efficient energy consumption of the networking nodes and the minimization of the delays. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy efficient fault-tolerant multipath routing scheme for wireless sensor networks

In wireless sensor network （MSN）, reliability is the main issue to design any routing technique. To design a comprehensive reliable wireless sensor network, it is essential to consider node failure and energy constrain as inevitable phenomena. In this paper we present energy efficient node fault diagnosis and recovery for wireless sensor networks referred as energy efficient fault tolerant multipath routing scheme for wireless sensor network. The scheme is based on multipath data routing. One shortest path is used for main data routing in our scheme and other two backup paths are used as alternative path for faulty network and to handle the overloaded traffic on main channel. Shortest pat data routing ensures energy efficient data routing. Extensive simulation results have revealed that the performance of the proposed scheme is energy efficient and can tolerates more than 60% of fault.     

A decision tree cognitive routing scheme for cognitive radio mesh networks

Routing in a cognitive radio network operating in a dynamic environment is a complex decision problem. Diversity in the number of available spectrum bands and their stability, in addition to the secondary users' heterogeneities, affect the consequence of the routing decision. We use a decision theory framework to model the problem of routing under uncertainties involved in a cognitive radio network. A utility function is designed to capture the effect of spectrum measurement, fluctuation of bandwidth availability, and path quality. A node cognitively decides its best candidate among its neighbors by utilizing a decision tree. Each branch of the tree is quantified by the utility function and a posterior probability distribution that predicts the suitability of available neighbors. In decision tree cognitive routing (DTCR), nodes learn their operational environment and adapt their decision‐making accordingly. We compared our scheme with the optimal performance in a highly dynamic environment and local coordination‐based routing and spectrum assignment protocol [1]. Our results show that the DTCR tends to perform near optimum. It easily adapts to environmental dynamics. Copyright © 2013 John Wiley & Sons, Ltd.     

基于网络监控器的专用片上网络动态容错路由

针对专用片上网络（Network on Chip,NoC）全局通信事务管理和可靠性设计问题,提出片上网络监控器的概念,用于获取全局网络实时状态信息及执行路径分配算法,基于此提出一种动态路由机制DyRS-NM.该机制能检测和定位NoC中的拥塞和故障链路,并能区分瞬时和永久性链路故障,采用重传方式避免瞬时故障,通过重新路由计算绕开拥塞和永久性故障.设计实现了RTL级网络监控器和与之通信的容错路由器模块,并将MPEG4解码器应用映射至基于网络监控器的4×4Mesh结构NoC体系结构中,验证了系统性能以及面积功耗开销.相比静态XY路由和容错动态路由FADR,DyRS-NM机制在可接受的开销代价下获得了更优的性能.     

基于阈值检测的光突发交换偏射路由算法

光突发交换是适合在当前技术条件下的新交换技术,它比电路交换灵活,带宽利用率高,又比光分组交换易于实现,将成为下一代光IP骨干网的核心技术。在光突发交换网络中,偏射路由算法是有效解决突发竞争、提高网络性能的一种重要措施。首先分析了发送端控制的偏射路由技术,在此基础上提出了一种基于阈值检测的偏射路由的改进算法。该算法通过跳数来控制无效偏射路由并通过有条件地丢弃偏射突发来保证正常突发的丢包率,从而减少偏射路由对网络负荷的影响,使整个网络的丢包率得到一定提高,改善网络性能。     

基于机器学习的光网络路由与频谱分配机制研究

对于光网络而言,路由与频谱分配是制约光层资源利用率和光网络容量的重要问题之一。机器学习迅速发展,为光网络管理与控制的智能化、自动化提供了新的发展方向。本文回顾了近年来基于机器学习的路由频谱分配相关研究,介绍了光网络控制中常见的机器学习算法,描述了基于神经网络和强化学习的路由频谱分配机制,最后分析了当前研究在泛化性和可靠性等方面的潜在挑战。