基于极化信号处理的绿色认知无线电技术

For the spectrum and energy scarcity problem in wireless communications, this project adopts polarization signal processing technique, and investigates energy efficient and spectrum efficient green cognitive radio theory and technology. This study concentrates on searching, optimizing and organizing polarized spectrum opportunities, and proposes blind signal processing based cognitive polarization adaption methods, getting rid of the limit that it is difficult for the secondary users to acquire the prior information of primary users, the polarized spectrum opportunities are acquired and hence secondary users can coexist with the primary users, thus the spectrum efficiency is improved; the cognitive polarization adaption probability and energy efficiency as a function of polarized characteristics are modeled to optimize the utilization of polarized spectrum opportunities, and the system energy efficiency is improved; the environment-adaptive spectrum sharing modes selection mechanism is proposed, the impacts of randomly emerged primary users and dynamically depolarized channels on polarization-enabled green cognitive communication is removed, and the management of polarized spectrum opportunities is realized, where the spectrum efficiency and energy efficiency is further improved. The aim of this study is to propose new methods for green cognitive communications utilizing polarization signal processing, and provide novel solutions for alleviating the spectrum and energy scarcity problem.

针对无线通信中的频谱和能量资源紧缺的问题，项目采取极化信号处理技术，研究高频效和高能效的绿色认知无线电理论和技术。本项目的研究围绕寻找、优化和管理极化域频谱机会展开，提出了基于盲极化信号处理的认知变极化方法，摆脱了次用户难以获取主用户信息的限制，使次用户获得极化域频谱机会而与主用户同时同频共存，提升频谱效率；建立了变极化概率模型和以极化特性为自变量的能效优化模型，优化对极化域频谱机会的利用，提高系统的能量效率；提出了环境自适应的频谱共享方式选择机制，降低主用户出现的随机性和无线信道去极化作用的动态性对绿色认知通信造成的不利影响，实现对极化域频谱机会的管理，进一步改善频谱效率和能量效率。项目旨在通过上述研究，提出利用极化信号处理的绿色认知通信的新方法，为缓解频谱和能量资源紧缺问题，提供新的解决思路。

针对无线通信中的频谱和能量资源紧缺的问题，项目采取极化信号处理技术，研究高频效和高能效的绿色认知无线电理论和技术。首先，针对全双工授权用户采样信号是混合信号的问题，分别提出了基于授权信号极化相似度和极化距离的授权信号空间提取方法。在获得授权信号空间的基础上，认知用户在此信号空间的正交空间内传输自身信号，可以避免对全双工授权用户信号的干扰，从而提升了频谱效率。其次，针对传统频谱共享方法能量效率低下的问题，提出了基于传统混合式频谱共享方法的自适应频谱共享方法。该方法不仅能提升半双工认知用户的最小能量效率，而且可以提升全双工认知用户的整体能量效率。.本项目的研究意义在于探索基于极化信号处理方法的绿色认知通信技术，开发信号极化域上潜在的频谱和能量增益，为解决无线通信频谱和能源紧缺问题提供新的思路。项目研究将虚拟极化技术、最优化方法等相关理论与研究成果应用于绿色认知无线电理论、算法、策略与机制的研究中，对于缓解无线通信的频谱和能源危机具有重要的意义, 为缓解频谱和能量资源紧缺问题，提供新的解决思路。