基于空间辨识与跟踪的自主学习型多天线认知无线电技术研究

项目名称： 基于空间辨识与跟踪的自主学习型多天线认知无线电技术研究

项目编号： No.61201187

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 高飞飞

作者单位： 清华大学

项目金额： 27万元

中文摘要： 在多天线认知无线电系统中采用波束成型，可以有效的减小其对授权用户的干扰，进而在保证授权用户权益下提高认知用户发送功率，扩大吞吐量。目前绝大多数相关研究均基于授权用户的配合来获取必要的信道信息，并以此设计认知用户的各类波束成型算法。然而，认知无线电的核心思想要求认知用户对授权用户具有透明性，因此对授权用户配合的需求并不实际。本项目拟在认知用户端以自主学习的方式观测授权用户的空间信息，判断授权用户的存在性以及其存在时的传输空间，由此限定认知用户自身的传输空间以达到抑制干扰的目的。进而设计动态算法跟踪空间信息，使得认知用户在环境变化时能及时调整传输空间，维持对授权用户的干扰不变。在此基础上分析空间测量和跟踪误差带来的性能损失，继而在认知用户端设计鲁棒性的预编码矩阵和资源分配算法以达到最佳传输效果。最终形成基于空间理论的多天线认知无线电传输方法，为未来认知无线电网络的应用提供重要的理论和技术支撑。

中文关键词： 认知无线电；多天线；子空间；资源分配；多功率级

英文摘要： Applying beamforming in multi-antenna cognitive radio system could effectively reduce its interference to the licensed user. Consequently, one can enhance the transmission power at the cognitive radio side and achieve higher transmission throughput. However, most existing works rely on the coordination from the licensed user to obtain necessary channel information before they can design the beamforming algorithms. Unfortunately, such coordination is not consistent with the key concept of the cognitive radio and is, therefore, not practical. In this project, we design the self-learning strategies for cognitive radio system where the cognitive user observes the space information of the licensed user, judges the existence of the licensed user, and measures the transmission space of the licensed user. Then cognitive radio user can then build a proper transmission space in order to limit its interference to the licensed user. Moreover, we will design dynamic algorithm to track the space variation when the environment is changing, such that the interference can always be kept within the limit. Moreover, we will analyze the errors during the space measurement and tracking, based on which we will design robust precoding and the resource allocation algorithms for cognitive user to achieve the best performance. The propos

英文关键词： Cognitive Radio；Multiple Antenna；Subspace；Resource Allocation；Multiple Power Levels