Dynamic spectrum sharing techniques for next-generation wireless networks

该项目旨在开发新的和可实现的动态频谱共享技术，以支持新兴的宽带、人和机器类型的无线应用。特别是，考虑到现有硬件的实际局限性，我们考虑了集中式和分散式网络体系结构下的宽带频谱感知和接入算法的联合设计。该项目建立在国家研究机构研究团队和行业合作伙伴(Nutaq)之间现有合作的基础上，它利用了国家研究机构现有的专业知识和最先进的设施。该研究的长期目标是为高速无线网络开发健壮而高效的宽带频谱感知和动态频谱共享技术。为此，其短期目标是设计i)宽带频谱感知解决方案，该解决方案对包括噪声不确定性和无线衰落在内的各种不良因素具有健壮性；ii)有效集成频谱感知功能的分散式动态频谱共享协议；以及iii)集中式动态频谱共享技术，利用许可和非许可频谱并支持用户的服务质量和差异化服务。这个项目的独特之处在于它统一了频谱感知和接入算法的设计，这两个算法在现有文献中通常是分开处理的。此外，它还包括基础研究和设计问题的研究以及实验研究活动，在这些活动中，选择开发的算法在硬件平台上实施，以进行真实世界的性能评估。

This project aims to develop novel and implementable dynamic spectrum sharing techniques to support emerging broadband human and machine-type wireless applications. In particular, we consider the joint design of wideband spectrum sensing and access algorithms for both centralized and decentralized network architectures considering practical limitations of state-of-the-art hardware. This project is based on the existing collaboration between the INRS research team and industry partner (Nutaq) and it exploits the expertise and state-of-the-art facility available at INRS. The long term objective of the proposed research is to develop robust and efficient wideband spectrum sensing and dynamic spectrum sharing techniques for high-speed wireless networks. Toward this end, its short-term objectives are to design i) wideband spectrum sensing solutions that are robust against different undesirable factors including noise uncertainty and wireless fading; ii) decentralized dynamic spectrum sharing protocols efficiently integrating the spectrum sensing function; and iii) centralized dynamic spectrum sharing techniques exploiting both licensed and unlicensed spectrum and supporting users' QoS and differentiated services. This project is unique in that it unifies the design of spectrum sensing and access algorithms, which are usually treated separately in the existing literature. In addition, it comprises the study of fundamental research and design issues as well as experimental research activities where selective developed algorithms are implemented on hardware platforms for real-world performance evaluation.