NeTS: Small: Designing an Advanced Mobility Management and Utilization Framework for Enabling mmWave Multi-Band Ultra-Dense Cellular Networks of Future

利用毫米波频谱可以解决移动蜂窝网络中两个长期存在的、相互关联的问题：频谱稀缺和干扰。因此，使用毫米波和5ghz以下频谱部署密集的小型蜂窝网络是缓解当前无线容量问题的一种方法。虽然这种多频段超密集网络的出现可以解决这两个问题，但它也产生了一个新的具有挑战性的问题：在这种由不同大小的小区组成的密集网络中，高效无缝地管理用户的移动性，这些小区在广泛的频段上具有完全不同的传播特性。由于处理用户移动性在移动网络中至关重要，因此确保新兴蜂窝网络架构中无缝高效移动性的可行性要求改变当前管理用户移动性的方式。该项目的总体目标是通过开发先进的移动管理和利用框架（AM-MUF），将移动管理从被动过程转变为主动过程，从而引发这种转变。该项目提供了强有力的劳动力培训，为开展拟议的研究提供了急需的多学科技能，同时确保妇女和其他代表性不足的群体的参与，以及K-12的外展。该项目还利用与蜂窝生态系统中关键的国家和国际利益相关者的合作：1)用实时网络的数据验证移动预测模型；2)在全尺寸户外5G测试平台上评估所提出的解决方案；3)在真实网络上进行现场试验；4)通过基于试验台的成果示范，促进5G标准化机构对项目成果的适应。AM-MUF将通过三个相互关联的研究重点来发展：1)首先，该项目将开发实际可实施的模型，用于预测超密集多频段网络中用户移动性的一系列属性；2)第二，利用预测模型开发敏捷和可扩展的下一代解决方案、算法和协议，用于基于主动移动的鲁棒优化和基于主动移动的负载平衡；3)第三，该项目将得出：不同系统配置（包括小区密度和移动性场景）下预测算法精度的基本限制；在给定的预测精度下，所开发的解的性能界。为了实现这一雄心勃勃的目标，研究人员将利用一种系统的方法，包括分析建模、系统级仿真、基于合成数据的培训和测试、基于真实数据的验证、基于全面5G测试平台的评估和真实网络的现场试验。

Harnessing millimeter-wave spectrum can solve the two long-standing, interlocked problems in mobile cellular networks: spectrum scarcity and interference. Therefore, deploying dense small-cell networks using millimeter wave and sub-5GHz spectrum is being pursued as a way to mitigate current wireless capacity problems. While advent of such multi-band ultra-dense networks may solve these two problems, it gives birth to a new challenging problem: managing user mobility efficiently and seamlessly in such a dense network consisting of cells of varying sizes on a wide range of frequency bands with entirely different propagation characteristics. As handling user mobility is essential in a mobile network, ensuring the viability of seamless and efficient mobility in emerging cellular network architectures calls for a shift from the way user mobility is currently managed. The overarching goal of this project is to trigger this shift by transforming mobility management from being a reactive to a proactive process by developing an Advanced Mobility Management and Utilization Framework (AM-MUF). This project offers strong workforce training in a highly sought-after multi-disciplinary skill set needed to conduct proposed research, while ensuring participation of women and other underrepresented groups, and K-12 outreach. The project also leverages collaboration with key national and international stakeholders in cellular ecosystems to: 1) validate the mobility prediction models with data from a live network; 2) evaluate proposed solutions on a full scale outdoor 5G testbed; 3) conduct field trials on a real network; 4) promote adaptation of the project outcomes by 5G standardization bodies through a testbed-based demonstration of results.AM-MUF will be developed through three interlinked research thrusts: 1) First, the project will develop practically implementable models for predicting a range of attributes of user mobility in ultra-dense multi-band networks; 2) Second, the prediction models will be leveraged to develop agile and scalable next generation solutions, algorithms and protocols for proactive mobility-based robust optimization and proactive mobility-based load balancing; 3) Third, the project will derive: the fundamental limits of accuracy of the prediction algorithms under different system configurations including cell density and mobility scenarios; and performance bounds of the developed solutions for a given prediction accuracy. To achieve this ambitious goal, the researchers will leverage a systematic methodology consisting of analytical modeling, system level simulations, synthetic data based training and testing, real data based validation, a full scale 5G test-bed based evaluations and field trials on a real network.