QoS驱动的能量采集型NB-IoT网络多维资源联合优化与接入理论研究

网络服务性能保障的高效数据传输是能量采集型NB-IoT网络研究的核心模块，其目的是尽可能高效合理地利用有限网络资源以保证NB-IoT用户的服务质量（QoS）。网络环境（如信道、能量采集）的时变性使得高效数据传输实现面临巨大挑战。为了应对这一挑战，本项目的主要目标是面向能量采集型NB-IoT网络，探索QoS驱动的多维网络资源高效利用机理和联合优化策略。具体研究内容包括：从QoS角度探索基于可再生能量和中继等多维网络资源的网络服务资源型--目标函数优化模型；研究基于QoS保证的可再生能量分配策略，从理论和应用角度分别探索可再生能量优化分配算法设计；研究基于网络环境感知的中继接入管理策略，探索高效的大规模NB-IoT新型多址接入机制和分布式中继接入选择算法。本项目的成功完成将在理论基础和实际应用层面解决能量采集型NB-IoT网络的高效数据传输问题，从而保证NB-IoT网络的绿色通信以及服务质量。

Over the past decade, exponential growth in the demand of wireless services has extended beyond broadband-intensive services to computation-intensive and latency-critical NB-IoT services. This trend has been accompanied by high energy consumption and considerable greenhouse gas (such as carbon) emissions with increasing deployment of wireless access networks. The resulting environmental and financial concerns drive the research community to develop innovative solutions for green wireless communications and networking. To this end, energy harvesting (EH) technology has emerged as a promising solution to improve energy efficiency and reduce greenhouse gas emissions in future wireless communication systems. Specifically, the transmission nodes in wireless links are powered by harvesting renewable ambient energy, such as solar, wind, thermoelectric, electromechanical, and ambient radio frequency energy. In addition, relay communication has emerged as a promising technique to enable broader communication coverage and reduced energy consumption in wireless networks. Therefore, it can serve as a potential candidate to further enhance the performance of EH wireless communication networks. Since the wireless resource allocation (such as energy management, time scheduling, and relay selection) can be applied to achieve higher spectral and energy efficiency and better quality of service (QoS), it has been studied extensively in energy harvesting relay communication networks with either finite-size data buffer or finite-size energy storage. However, the problem is still open in the context of time-varying communications, when the energy harvesting node is subject to both finite-size data and energy storage. Therefore, a main goal of this project is to optimize wireless resource allocation based on environmental sensing for energy harvesting NB-IoT networks by resorting the recent advances in optimization. Of particular interest are three key issues to be investigated: the establishment of an optimization framework which jointly optimizes energy.management, time scheduling and relay selection for energy harvesting relay communication networks; (ii) the development of optimal offline, optimal online, sub-optimal online transmission policies for the joint optimization of energy management and time scheduling that maximizes the network performance subject to the data buffer and battery storage limitations; (iii) the development of low-complexity relay access and selection algorithms by exploiting the special features of the formulated problems. To the best of our knowledge, this is a first attempt at.studying the joint optimization of multi-dimensional wireless resource allocation including energy management, time scheduling, and relay management in energy harvesting NB-IoT networks subject to the data buffer and battery storage limitations. We believe that the main contributions of this project are to provide some guidelines on how to efficiently utilize wireless resource in energy harvesting NB-IoT networks, which will be of practical importance to improve the spectral and energy efficiency and reduce the total greenhouse gas.emissions for green wireless communications.