生物友好的认知水声网络频谱管理与路由机制研究

Underwater communication has become more and more important in data transmission, widely applied in commercial and military water environments. The need for underwater communications exists in applications such as pollution monitoring, collection of scientific data recorded at ocean--bottom stations, disaster detection, remote control in the offshore oil industry and early warning, national security and defense, as well as for discovery of new natural resources.. Thus, research on underwater communication techniques plays a most important role in further exploring oceans and other aquatic environments. Compared with terrestrial wireless radio communications, underwater wireless networks and communication channels can be significantly affected by marine environments, noise, limited bandwidth and power resources. . In oceans, both the natural acoustic systems and artificial acoustic systems (such as underwater sensor networks and sonar users) use acoustic signal for communication, echolocation, sensing, monitoring and detection. In addition, underwater acoustic channel features high background noise, narrow band and long propagation delay. Therefore, researches of UWSNs face great challenges.. In this proposal, we will first analyze the interaction among cooperative sensing, media access control and routing mechanism of UWSNs. Then the performance of related joint algorithms can be evaluated in the cognitive UWSNs. Based on the theory of cognitive acoustic, we can conduct researches on underwater acoustic channel and the cooperative sensing strategy among sensors which aims to detect the use of spectrum resource by marine mammals with high efficiency and accuracy. With the spectrum sensing result, the network can extract signal’s features and then predict the occupation of acoustic channels by marine mammals and other networks, which can be used for developing the MAC mechanisms and algorithms for cognitive UWSNs.. To optimize the overall performance of networks, we plan to apply Network Utility Maximization theory to model the cognitive UWSNs. Based on the NUM theory, the access game among multi systems will be proposed. Furthermore, the novel MAC mechanism will take a consideration of directional propagation of acoustic modem, maximization of spatial reuse to improve performance. . In network layer, the proposal will include the researches of the connectivity model, avoidance of routing voids and obstacles of the network which consists of nodes equipping directional transducers. All these researches are based on the analysis of time-spatial topology control, intermittence connectivity model with the help of computational geometry and random graph theory. With such research, we will propose a high efficient 3D routing algorithm in an ECO-friendly way.. This project can achieve theoy progress in the design of mechanism and algorithms of cognitive UWSNs. The proposed mechanism and algorithms will be tested and evaluated in a real world.

水声信道环境噪声高、带宽窄、传输时延长，且人工系统和自然水声系统存在频谱干扰和冲突。项目将分析UWSN协作认知机制、MAC机制及路由机制的相互作用机理，揭示相关算法在认知UWSN中联合使用的性能。基于认知理论，研究水声信道及水生生物频谱多节点协作感知机制。对节点信道占用和变化、水声生物信道使用等重要特性进行特征提取与预报，构建适用于认知水下网络的多用户接入机制及算法。应用网络效用最大化理论对水声认知网络进行建模和问题分解，提出多系统接入博弈机制和算法。设计融合方向性传输的MAC层时、空复用最大化接入算法，形成高效可靠的频谱管理和MAC接入新机制。研究考虑方向性传输的网络连通性模型及相应的路由空洞和障碍物避免策略。借助计算几何、随机图论对网络时空变化的拓扑结构、间歇连通模型等进行分析。在生物友好条件下，提出3D高效路由算法。项目将在认知水下网络机制设计与算法上获得理论进展并进行实验验证。

针对水下声传感网络面临的水声信道环境噪声高、带宽窄、传输时延长等约束条件，而且人工声学系统与水下生物水声系统存在频谱干扰和冲突等问题，本项目设计与实现了UWSN协作认知机制、频谱决策机制、水下信道MAC机制及路由机制，并且进行了联合设计与跨层优化。基于认知理论与稀疏信道分析与相关技术，率先提出了面向信道容量优化的生物友好频谱协作感知机制。通过认知与生物友好机制，实现了高效的频谱决策与功率控制，并且提供了跨层服务接口。设计了对节点信道占用和变化、水声生物信道使用等重要特性进行特征提取与预报算法，构建了适用于认知水下网络的多用户接入机制及算法。设计与实现了融合方向性传输的MAC层时、空复用最大化接入算法，形成高效可靠的频谱管理和MAC接入新机制。研究考虑方向性传输的网络连通性模型及相应的路由空洞和障碍物避免策略。并且提出了AUV/Glider等水下移动节点构成的异构水下网络的MAC机制与路由机制。项目还提出了MAC与时间同步一体的高效新机制，并且进一步融合了节点定位机制，有效实现了一体化的通信与定位。进一步，基于Q-learning等机器学习方法，在生物友好条件下，提出了3D高效路由算法。为了对有关算法与协议性能进行验证与改进，项目还改进了基于NS-2的水下网络仿真系统。项目形成了频谱决策、信道接入机制、时间同步与节点定位、路由机制等水下传感器网络关键技术与总体方案，并且构建了仿真与实验平台。