面向5G频谱共享的群智频谱数据统计学习方法研究

项目名称： 面向5G频谱共享的群智频谱数据统计学习方法研究

项目编号： No.61501510

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 丁国如

作者单位： 中国人民解放军陆军工程大学

项目金额： 19万元

中文摘要： 5G频谱共享是当前无线通信领域国际研究前沿，引起学术界、工业界、标准化组织、政府频谱管理部门等多方力量的密切关注，被认为是解决5G系统中“频谱赤字日益严峻”这一问题直接有效的手段之一。本项目从5G频谱共享所呈现的新特征（即共享方式的多样化、共享频段的异构化、共享设备的智能化、共享网络的超密集化）出发，针对群智频谱数据分析面临的数据来源不可靠、检测结果不准确、历史数据不完整、信息更新不及时、机会发现不充分等新问题与新挑战，从无线通信、统计信号处理和机器学习等多学科交叉融合的角度展开基础理论与关键技术攻关，从（被动的）群智稳健频谱感知、（主动的）群智协同频谱推理和（集成的）群智实时频谱数据库三个方面展开系统研究，旨在构建面向5G频谱共享的群智频谱数据统计学习的理论与方法体系，为实现5G频谱高效利用提供理论支撑与技术支持，同时取得一批高质量研究成果，形成若干有影响力的发明专利和国际标准化提案。

中文关键词： 第五代移动通信；频谱共享；群智频谱数据分析；统计学习

英文摘要： 5G spectrum sharing is one of the international research fronts in the filed of wireless communications, which has gained increasing interest of academia, industry, standard associations, and governmental spectrum regulators, and has been recognized as one of the most direct and efficient methods to resolve the issue of ever-increasing serious spectrum deficit/shortage in future 5G systems. This proposal begins with discussing the potential new features of 5G spectrum sharing, including diversity in sharing patterns, heterogeneity in sharing bands, intelligence in sharing devices, and hyper-densification in sharing networks. Then, new problems and new challenges are highlighted, such as unreliable spectrum data sources, inaccurate detection outputs, incomplete historical data, out-dated information update, insufficient sharing opportunity discovery, etc. Furthermore, this proposal proposes to perform the research on basic theories and key technologies from a interdisciplinary perspective of wireless communications, statistical signal processing and machine leering. Notably, this proposal depicts a systematic research map from the following three aspects: (reactive) crowd robust spectrum sensing, (proactive) crowd cooperative spectrum prediction/inference and (compositive) crowd real-time spectrum database. The dominating objective of this proposal is to build a theoretical and methodological system of statistical learning of crowd spectrum data for 5G spectrum sharing, which can be employed to significantly improve the 5G spectrum utilization. Meanwhile, this proposal aims to output a number of international-recognized research results, including papers of high-quality, patents and standard proposals of international high-impact.

英文关键词： 5G mobile communications;Spectrum sharing;Crowd spectrum data analytics;Statistical learning