认知OFDM系统中基于业务特性的能量有效多播资源分配研究

With the development of wireless communication technologies, the number of wireless networks is rising remarkably, and therefore the energy consumption of wireless systems is increasing dramatically. Meanwhile, the existing fixed spectrum allocation also results in the inefficient spectrum resource utilization. To address the dual challenges of reducing energy consumption and improving spectrum efficiency, this project studies the energy-efficient multicast resource allocation problem based on traffic characteristics in OFDM-based cognitive radio (CR) systems. Driven by various traffic characteristics, this project considers energy-efficient multicast resource allocation respectively with ideal traffic model, general practical-traffic model and mobile video traffic model. For ideal traffic model, the energy efficiency, in which the energy consumption for spectrum sensing and the harvested energy from surroundings are incrementally covered besides the energy consumption for data transmission, is optimized by jointly adjusting durations, spectrum occupation and power. For general practical-traffic model, the energy consumption is reduced by smoothing the dynamics of aggregated traffic with network calculus technology, and moreover the total times of traffic transmission are lessened to promote the energy efficiency by creating multicast opportunities based on both mobile users' interest and their social relationship. For mobile video traffic model, with the energy utilization as the objective function instead of the conventional energy efficiency, the energy-efficient video transmission is achieved by adopting the advanced video coding and multi-antenna technologies. This project concentrates on energy-efficient multicast resource allocation, specifically, from passive multicast exploitation to active multicast opportunity creation, significantly improves the energy efficiency of OFDM-based CR systems, and hence is instrumental in the realization of the national energy conservation and emission reduction targets.

随着无线通信技术的发展，无线网络数目显著增多，无线系统能耗急剧攀升；同时，现有固定频带划分造成了频谱资源的低效利用。针对降低能耗与提升谱效双重挑战，本项目研究认知OFDM系统中基于业务特性的能量有效多播资源分配问题。以业务特性为主线，分别进行理想业务、一般性实际业务、移动视频业务下能量有效多播资源分配研究。对于理想业务，从只考虑数据传输能耗开始，逐步增加考虑频谱感知能耗和外部能量收集，研究联合调整时长、频谱、功率的能效优化；对于一般性实际业务，利用网络微积分技术平滑业务动态性减少能耗，同时基于用户兴趣、社交关系创造多播机会，减少业务传输次数而实现能效提升；对于移动视频业务，设计"能量效用"替代传统的"能量效率"，采用高级编码和多天线技术实现视频业务的能量有效传输。本项目聚焦于多播资源分配，从"被动利用多播"转变为"主动创造多播"，有效提升认知OFDM系统能效，有助于我国节能减排目标的实现。

随着移动和无线通信技术的高速发展，无线通信系统的能量消耗迅速上升。同时，用户业务需求大幅增长，频谱资源紧缺。如何降低无线通信系统能耗和提升频谱利用效率是当前无线通信系统发展亟待解决的双重挑战。认知无线电技术是提升频谱利用效率的重要方式，研究认知无线电系统的能效优化对于无线通信系统的绿色、高速发展非常关键。为此，本项目研究了认知OFDM系统中基于业务特性的能量有效多播资源分配问题，结合频谱、业务和能量认知技术，进一步提高未来无线通信系统的能量效率。.项目以业务特性为主线，针对理想业务、一般性实际业务和视频业务，研究了能量有效多播资源分配问题。首先，对于理想业务，在认知系统能量优化研究中逐步考虑了数据传输能耗、频谱感知能耗和外部能量收集，研究了面向能效的时长、频谱、功率资源的联合优化方法。进一步，将业务一般化，对于一般性实际业务，研究了业务数据特性认知方法，利用业务的时域、空域和用户需求的多重不均匀性进行基于用户意愿的多播机会创造和基于社交网络的协作多播传输，进一步提升系统能效。最后，考虑到视频业务的普遍性，项目以视频业务的节能传输为落地点，研究了采用分层编码等高级编码和多天线技术进行视频业务的能量有效传输问题，利用分式规划和子梯度等方法，设计了相应的低复杂度的资源分配算法。通过上述研究，项目针对频谱低效利用问题，提出了面向能效的认知无线网络的多频带频谱感知和资源利用联合设计方法；针对终端能量短缺问题，提出了基于频谱和能量双重收集技术的频谱能量联合高效利用方法；针对业务不均匀性问题，提出了基于业务数据特性认知的认知无线网络节能方法。项目成果实现了对业务特性的充分利用，提升了无线通信系统的频谱效率和能量效率，为实际认知OFDM系统的性能提升提供了理论基础与技术支持。.经过4年的研究投入，本项目发表相关SCI/EI论文25篇，申请国家专利6项，圆满地完成了申请书预定任务指标。