基于多层次协作的移动认知网络智能化数据传输理论与关键技术研究

Data transmission in mobile cognitive networks is seriously challenged by dynamic and unbalanced resources among cognitive nodes and node mobility. The overall objective of this project is to make full use of network reousrces, optimize network performance and improve communication quality. Focusing on the adaptability to dynamical network environment and quite different transmission requirements, we extend cooperative cummunication technologies in both vertical and horizontal dimensions, and expand cognition targets from traditional node level to network and application levels, together with combining these two technologies efficiently. .In this project, we will intensively investigate theories and techniques on data transmission in mobile cooperative-cognitive networks as follows. Firstly, we are going to study and establish models and techniques of multi-layer cooperative communication, where we apply the cooperation to each layer in the network model, to fully use various network elements based on both cross-layer design in a single node and transmission cooperation among multiple nodes. Mechanisms for demand-driven cooperation flow promulgation will also be set up. Seccondly, we will propose extended multi-dimension cognition models, and mechanisms to inter-drive among the multil-layer cooperation and the multi-dimension cognition, laying the foundation for intelligent data transmission. Thirdly, a set of data transmission techniques will be developed through adaptive network reconstruction, based on joint multi-layer cooperation and topology control. In this stage, we will set up demand-driven adaptive data transmission techniques and network optimization models. In conclusion, this project will found a set of new theories and key technologies of intelligent data transmission for mobile cooperative-cognitive networks and can deliver innovative results with high impact. These results can effectively support and are widely applied to emerging broadband mobile communication.

认知节点资源(可用信道、带宽等) 的动态性与不平衡性、节点移动性，对认知网络数据传输带来了严峻挑战。本项目以充分利用资源、优化网络性能、改善通信质量为目标，以自适应网络环境与传输需求为主线，将协作通信进行纵向与横向扩展，将认知范围从节点环境扩展到网络与应用环境，在多层次上将协作与认知有机结合，深入研究移动协作认知网络数据传输理论与方法。主要研究：(1)多层次协作通信模型与方法，通过各个网络层次上的协作，以单节点跨层设计与多节点协同思想，充分使用各种网络元素；建立需求驱动的协作流传递机理。(2)多维度认知模型以及协作与认知的交互机制，为智能数据传输奠定理论基础。(3)联合多层协作、拓扑控制的数据传输方法，通过自主网络重构与联合设计，建立需求驱动的自适应数据传输与网络优化模型。本项目将形成全新的移动协作认知网络智能数据传输若干理论与关键技术，取得系统前沿的创新成果，为宽带移动通信形成有效支持。

移动认知网络中，认知节点的可用资源（特别是信道与带宽）和负荷存在着较大的差异并随着时间、地点持续变化；同时，由于用户高度移动，导致网络拓扑动态性极强，这些特征对现有的数据传输理论带来了严峻挑战。本项目以提高网络资源利用率为主线，以多层次协作为手段，研究了移动认知网络的高效数据传输理论和关键技术，主要成果如下：(1) 研究了频谱协商与协作转发的联合设计方法，提出了面向移动认知网络的新型路由度量机制与信号干扰图。(2) 提出了移动性控制与预测模型，设计了联合信道分配的自适应数据传输算法J-SRCA；实验证明：我们的J-SRCA算法比国际公认的PCTC和AODV协议在路径稳定性、路径长度、网络吞吐量、传输时延、丢包率、路由开销等方面均有较大的提升，特别是在主节点多、移动性高的网络环境下。(3) 研究了基于QoS的自适应服务模型和联合的资源分配方法。在此基础上，研究了相关支撑技术，实现了大数据网络中负载均衡路由算法和高效数据分析方法；研究了移动软件的动态生成与验证技术。研究工作实现了理论与技术创新，突破了部分关键技术，为未来的宽带移动数据传输提供了重要支持。相关研究成果在重要的国际期刊和国际学术会议上发表论文8篇(其中CCF A类IEEE TPDS论文2篇、IEEE TII论文1篇、CCF B类论文1篇)。此外，项目组还参与主办和承办了国际学术会议FFC 2013，与众多国内外知名学者交流了研究工作。