Optimized spectrum sharing of ultra-dense networks

本课题主要研究超密集网络的新型优化技术。我们考虑蜂窝接入点和/或设备对设备链路的密集部署，其中多个发射和接收对相互干扰，并提出了一种基于称为分数规划的优化技术的频谱共享新方法。该方法能够有效地找到整个网络中协调调度、波束形成和功率控制问题的局部最优解。数值上，分式规划解决方案本质上是迭代的，但每个迭代步骤通常涉及一个封闭形式的解决方案，因此易于实现。优化协调传输是保证超密集网络频谱兼容带宽共享的关键。作为具体应用，本研究将研究基于分数规划的灵活双工蜂窝网络协调调度方案，其中上行和下行同时传输可以显著提高区域频谱效率。本文还将分式规划技术应用于大规模多天线系统的空间复用和零化优化。该方法也可应用于蜂窝网络中中继链路的最优调度以消除干扰。最后，提出的研究将调查信令和信道状态获取策略，以允许分式编程技术的分布式实现。在即将到来的大数据时代，无线行业正在经历深刻变革。引入网络智能，动态实时地优化和适应网络运营，将是满足智能家居、智能办公、智能城市和自动驾驶汽车等重要应用领域日益增长的需求的关键技术步骤。************

This research project focuses on novel optimization technique for ultra-dense networks. We consider a dense deployment of cellular access-points and/or device-to-device links, where multiple transmit and receive pairs mutually interfere with each other, and propose a novel method for spectrum sharing based on an optimization technique called fractional programming. The proposed method is capable of efficiently finding locally optimal solutions to the coordinated scheduling, beamforming, and power control problem across the entire network. Numerically, the fractional programming solution is iterative in nature, but each iteration step typically involves a closed-form solution and is therefore easy to implement. Optimized coordinated transmission is the key to ensuring spectrally compatible bandwidth sharing in ultra-dense networks. As a concrete application, the proposed research will investigate fractional programming based coordinated scheduling scheme for cellular networks with flexible duplex capability, where simultaneous transmissions in uplink and downlink can significantly improve area spectral efficiency. The proposed research will also apply the fractional programming technique to the optimization of spatial multiplex and nulling in large-scale multiple-antenna systems. The proposed method can also be applied to the optimal scheduling of relay links for interference cancellation in cellular networks. Finally, the proposed research will investigate signaling and channel state acquisition strategies to allow distributed implementation of fractional programming techniques. The wireless industry is undergoing profound transformation in the upcoming Big Data era. The introduction of network intelligence in optimizing and adapting network operations dynamically and in real-time will be a key technological step in meeting the increasing demands in important application areas such as smart home, smart office, smart city, and self-driving cars.************