A New Paradigm of Radio Resource Management for Future Wireless Communication Networks Integrating Crowd Intelligence

集成群体智能的未来无线通信网络无线资源管理新范式

• 批准号: RGPIN-2018-06022
• 负责人: Cai, Jun
• 金额: $ 3.35万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689192
• 关键词: New; Paradigm; Radio; Resource; Management

Wireless communications have been rapidly penetrating our daily life. It is expected that by 2020, the volume of mobile data will be 1000 times higher than today, and between 10 and 100 times more connected devices. To meet this ever-increasing demand on wireless services, it is critical to manage scarce radio resources in a more efficient way in order to maximize the overall network capacity. The emerging trend of wide deployment of smart devices, such as smart phones, provides opportunities for achieving this goal by facilitating network management through offering crowd intelligence, which includes devices' capabilities in communication, computation, and sensing. However, “How to make full use of such crowd intelligence through suitably designed resource allocation algorithms?” and “How to encourage the participation of selfish mobile devices in network management?” are two key questions we have to answer before we can successfully take advantage of this opportunity.******My research program plans to address the aforementioned questions through studying and developing novel radio resource management techniques for future device-centric and content-centric wireless networks through the integration of crowd intelligence. Together with my HQP, we plan to address two critical open questions, including the development of strategies for proactive scheduling (a new feature introduced by crowd intelligence) based on predicted future information, and incentive mechanism design to encourage the participation of selfish smart devices in network management while at the same time preventing strategic behaviors, such as untruthfulness, from them. Research emphases will be put on addressing challenges raised from practical applications, including potential prediction errors, hierarchy resource management involving multiple entities, multi-dimensional resource allocation, limitation on resource availability, dynamic network environments, and computational complexity. The key tasks in this research involve: 1) development of novel radio resource management algorithms/protocols; 2) mathematical modeling and analyses; and 3) performance evaluation by analysis and simulation.******The proposed research will achieve breakthroughs in wireless communication network technology, is significant to foster a vital competitive edge for Canadian Information and Communication Technology industry in the international market place, and will result in significant benefits to Canadian users, including new wireless services and improved quality of experience.

无线通信一直在迅速穿透我们的日常生活。预计到2020年，移动数据量将比今天高1000倍，连接设备的10到100倍。为了满足这种对无线服务的不断增长的需求，以更有效的方式管理稀缺的无线电资源至关重要，以最大程度地提高整体网络容量。智能手机等智能设备的广泛部署的新兴趋势通过提供人群智能来支持网络管理，为实现这一目标提供了机会，其中包括设备在通信，计算和敏感性方面的功能。但是，“如何通过适当设计的资源分配算法充分利用这种人群智能？”和“如何鼓励自私的移动设备参与网络管理？”在我们成功利用这个机会之前，我们必须回答两个关键问题。与我的HQP一起，我们计划根据预测的未来信息制定两个关键的开放问题，包括制定主动调度策略（人群智能引入的新功能），以及激励机制设计，以鼓励自私的智能设备参与网络管理，同时防止策略行为，例如从这些策略行为，例如从他们那里进行统一的策略行为。研究重点将提出解决实际应用中提出的挑战，包括潜在的预测错误，涉及多个实体的层次结构资源管理，多维资源分配，资源可用性的限制，动态网络环境和计算复杂性。这项研究参与的关键任务：1）开发新型无线电资源管理算法/协议； 2）数学建模和分析； 3）通过分析和仿真进行绩效评估。******拟议的研究将在无线通信网络技术方面取得突破，对于在国际市场上的加拿大信息和通信技术行业促进了至关重要的竞争优势，并将为包括新的无线服务在内的加拿大用户带来重大利益，包括新的无线服务和改善的经验。