认知无线电技术及应用

认知无线电技术是目前无线传输领域的主要研究热点之一。对认知无线电的不同定义进行了讨论,并从认知无线电系统组成及认知无线电与其他无线电(特别是自适应无线电和智能无线电)的关系2方面分析了其内涵,重点介绍了无线频谱感知、智能资源管理、自适应传输和跨层设计等认知无线电系统主要关键技术;最后给出了认知无线电可能的应用场景。     

LTE-A基于资源利用率的接纳控制跨层设计

为了能有效提高网络性能,提高资源利用率,使得信息交流更加直接简单。提出了一种LTE-A基于资源利用率的接纳控制跨层设计。该方法将资源利用率和业务QoS满意度联合考虑,同时提出跨层的设计方法,该方法与现存的方法相比,不仅提高了资源利用率也能更好地满足业务的QoS需求。仿真结果表明,该设计能有效提高网络性能,满足各个业务的服务质量。     

一种无线视频业务的应用层跨层优化技术研究

在深入分析了仿真结果后,本文发现引入应用层Raptor FEC技术,将在无线传输方面(物理层)带来了最优操作点,在最优操作点及其附近,无线资源的利用率得到进一步的提高,且无需增加发射功率以降低BLER目标值.也就是说,采用同样的发射功率,在应用层使用了Raptor FEC编码技术之后,MBMS业务的覆盖面积可进行较大幅...     

认知无线Mesh网络跨层设计研究

传统网络的分层设计不能满足具有特殊QoS需求的无线宽带业务,无法应对动态频谱接入的无线通信环境。采用联合开放、架构灵活的跨层设计研究无线Mesh网络接入技术日渐成为热点。本文首先介绍了跨层设计的起源、分类,然后分析了认知无线Mesh网络跨层研究的挑战、难点及最新进展,并提出利用跨层设计实现路由及频谱管理的一种构想,最后展望了认知无线Mesh网络跨层研究的新方向。     

多跳认知无线Mesh网络中频谱决策与路由的跨层设计

灵活高效的频谱共享技术能够实现频谱资源的最大化利用,有效地缓解了无线频谱紧缺的现状。在一个与TDMA/FDMA蜂窝网络共存的多跳认知无线Mesh网络环境下,基于覆盖式（Underlay）与机会式（Overlay）相结合的频谱共享机制,提出了一种有效的链路层频谱决策与网络层路由的跨层设计方案。仿真结果表明,该方案比基于最小跳数的随机信道选择算法在网络端到端传输性能上有显著的优势。     

基于网络编码的多径路由策略

针对无线传感器网络节点能量受限制的特点,提出基于网络编码的多径路由策略.该策略在数据传输过程当中通过增加跨层协作机制,减少对单个数据包的依赖,降低数据包重传次数,使得网络带宽得到优化,同时数据在传输路径中进行随机编码使得数据包安全传输.分析表明,该策略可以保证数据传输的有效性和安全性.     

基于中继的OFDMA网络中可扩展编码视频流传输的权衡优化(英文)

To achieve an optimal trade-off between video quality and energy efficiency in the uplink streaming of multi-user Scalable Video Coding (SVC) videos in relay-based Orthogonal Frequency Division Multiple Access (OFDMA) cellular networks, a cross-layer design framework that jointly selects the Transmission Policy (TP) for SVC video frames, assigns OFDMA subcarriers, and allocates power for each subcarrier is proposed. We apply the dual decomposition method to the problem, and obtain a TP selection subproblem for each SVC video adaptation and a resource allocation subproblem of Joint Subcarrier, Relay and Power Allocation (JSRPA). A second level of dual decomposition is used to divide the JSRPA problem into independent subcarrier subproblems. The proposed Crosslayer Trade-off Optimization (CTO) algorithm is sub-distributed with significantly low complexity. A performance evaluation with typical SVC video traces demonstrates that the proposed algorithm is able to converge and efficiently achieve the optimal trade-off between the video quality and energy consumption at the MSs for uplink SVC streaming.     

Collision avoidance in TV white spaces: a cross-layer design approach for cognitive radio networks

One of the most promising applications of cognitive radio networks (CRNs) is the efficient exploitation of TV white spaces (TVWSs) for enhancing the performance of wireless networks. In this paper, we propose a cross-layer design (CLD) of carrier sense multiple access with collision avoidance (CSMA/CA) mechanism at the medium access control (MAC) layer with spectrum sensing (SpSe) at the physical layer, for identifying the occupancy status of TV bands. The proposed CLD relies on a Markov chain model with a state pair containing both the SpSe and the CSMA/CA from which we derive the collision probability and the achievable throughput. Analytical and simulation results are obtained for different collision avoidance and SpSe implementation scenarios by varying the contention window, back off stage and probability of detection. The obtained results depict the achievable throughput under different collision avoidance and SpSe implementation scenarios indicating thereby the performance of collision avoidance in TVWSs-based CRNs.     

Mobile Cloud for Personalized Any-Media Services

In this paper,we define mobile cloud computing and describe how it can be used for delivering advanced any-media services to both nomadic and mobile users.We focus on service delivery that is localized and personalized and suggest that virtualization and tighter cross-layer communication allows for convergence and seamless transition of services.These are also creating new and never-before seen ways of developing and delivering personalized any-media services.We discuss current paradigms for implementing cloud-based any-media services that generate revenue.Future research topics and requirements for evolving network and service elements are also discussed.     

SLCRM：无线网格网络中一种基于主观逻辑的跨层信誉机制

Wireless Mesh Networks (WMNs) are vulnerable to various security threats because of their special infrastructure and communication mode, wherein insider attacks are the most challenging issue. To address this problem and protect innocent users from malicious attacks, it is important to encourage cooperation and deter malicious behaviors. Reputation systems constitute a major category of techniques used for managing trust in distributed networks, and they are effective in characterizing and quantifying a node狆s behavior for WMNs. However, conventional layered reputation mechanisms ignore several key factors of reputation in other layers; therefore, they cannot provide optimal performance and accurate malicious node identification and isolation for WMNs. In this paper, we propose a novel dynamic reputation mechanism, SLCRM, which couples reputation systems with a cross-layer design and node-security-rating classification techniques to dynamically detect and restrict insider attacks. Simulation results sho that in terms of network throughput, packet delivery ratio, malicious nodes' identification, and success rates, SL-CRM implements security protection against insider attacks in a more dynamic, effective, and efficient manner than the subjective logic and uncertainty-based reputation model and the familiarity-based reputation model.