NeTS: Small: Toward Distributed Decision Making in Cognitive Radio Ad-hoc Networks Based on Bilevel Equilibrium Programming

该项目的动机是缺乏对分布式控制策略的理论理解，以在网络协议栈的多层共同优化认知无线网络功能。当考虑物理层参数时，得到的优化问题往往是非凸的，因此即使采用集中式算法，一般也不能有效地解决。这个项目的目标是从一个不同的和新颖的角度来看待认知无线电多跳网络的跨层设计。将传感参数、多址方案、路由和速率控制的联合优化问题表述为一个双能级平衡问题，可以高效地分布式解决。这项研究的成功完成将为社区提供一系列新颖的分布式算法，这些算法可以自然地在整个网络中实现垂直和水平分解。这将与众所周知的收敛速度缓慢的网络效用最大化问题的分解算法有很大的不同。该项目将有助于开发新的算法和工具，为下一代认知网络技术奠定基础。拟议的技术对当今社会的影响可以与特设网络的潜在应用一样广泛和强大；例如，搜索和救援行动，按需通信基础设施部署，以及智能交通公路和车辆。拟议的研究与一项教育计划相结合，旨在培养下一代网络专业人员，并促进学术研究与行业需求的交叉发展。

This project is motivated by the lack of theoretical understanding of distributed control strategies to jointly optimize cognitive radio network functionalities at multiple layers of the networking protocol stack. When physical layer parameters are considered, the resulting optimization problem is often nonconvex, and therefore cannot be solved efficiently in general even through centralized algorithms. The objective of this project is then to look at the cross-layer design of cognitive radio multi-hop networks from a different and novel perspective. The problem of jointly optimizing the sensing parameters, multiple-access scheme, routing, and rate control is formulated as a bi-level equilibrium problem, which can be solved efficiently and in a distributed way. Successful completion of this research will provide the community with a family of novel distributed algorithms that naturally implement vertical and horizontal decompositions across the network. This would represent a major departure from well-understood decomposition algorithms for network utility maximization problems that are known to suffer from slow convergence speed.The project will contribute to the development of novel algorithms and tools that will lay the foundation for the next generation of cognitive networking technology. The impact of the proposed technology to today's society can be as broad and as strong as the potential applications of ad hoc networks; for example, search-and-rescue operations, on-demand communications infrastructure deployment, and intelligent transportation highways and vehicles. The proposed research is integrated with an educational plan designed to train the next-generation of networking professionals, as well as promote cross-fertilization of academic research with industry needs.