EARS: Future Wireless Broadband Access: Cross-Optimizing Hardware, Physical and Network Layers

可负担得起且无处不在的宽带连接是繁荣的必要条件，因为宽带无线接入几乎影响到社会和经济的所有部门，包括教育、医疗保健、交通和安全。在像美国这样一个巨大的城乡混合国家，通过有线基础设施提供高速宽带数据访问可能是昂贵的。另一方面，无线可以覆盖大面积，非常有效地覆盖大量人群。此外，无线是我们连接到互联网并享受娱乐、教育、医疗保健、电子商务、社交网络和远程工作等丰富服务的首选媒介。在这种情况下，处理预期的无线数据需求急剧增长的能力不仅对无线行业至关重要，而且更普遍地说，对我们的经济增长至关重要。虽然无线连接在过去几十年里有了显著的改善，但它远远落后于理论和技术可实现的极限，无法满足未来的需求。考虑到这一点，该项目为具有密集部署基站的下一代蜂窝网络开发了一种创新的多层分层基础设施，以及一套用于干扰管理和系统优化的良好集成的跨层设计技术。该方法可以显著提高速率性能和用户容量，有望弥合宽带无线接入理论与实践之间的差距。为了支持无线宽带业务中急剧增加的移动数据流量，本工作侧重于系统的跨层系统优化方法，该方法依赖于三个主要支柱：1)在物理层，使用具有大量多输入多输出天线系统的基站；2)在无线网络架构层面，选择了多层异构网络方式，实现了前所未有的空间频谱复用；3)在跨层优化层面，提出了一种整体网络效用最大化方法，从全局优化解的结构中系统地获得分层协议体系结构。就上述支柱而言，本项目将解决的基本挑战是：1)基于混合波束形成概念的集成和节能可重构大规模多输入多输出前端天线系统的设计，即数字基带处理和模拟射频波束形成之间的多用户预编码和小区间干扰管理功能的最佳分割；2)设计混合波束形成方案，利用长期信道统计信息进行小区间协调干扰管理，利用瞬时信道状态信息实现小区空间复用增益；3)根据用户体验质量要求、信道统计和可移动性对用户空间进行聚类，将网络效用函数分配给不同的用户群，解决组合网络效用最大化问题，并根据优化方案的结构特性系统地推导出分层协议体系结构。此外，这项工作将显著扩展当前无线网络的数学性能分析，基于随机几何和随机矩阵理论的先进工具，以便定量评估所提出方法相对于当前技术的性能增益。最后，将使用软件定义无线电进行小规模实验，该无线电将配备将开发的前端。

The availability of affordable and ubiquitous broadband connectivity is a necessary condition for prosperity since broadband wireless access impacts virtually all sectors of society and economy including education, healthcare, transportation, and security. In a vast and mixed urban/rural country such as the United States, providing high-speed broadband data access through the wired infrastructure can be costly. On the other hand, wireless can cover large areas and reach a large number of people very effectively. In addition, wireless is the preferred medium through which we connect to the Internet and enjoy a whole wealth of services such as entertainment, education, healthcare, e-commerce, social networking, and remote working. In this context, the ability to handle the predicted dramatic increase of demand for wireless data has become crucial not only for the wireless industry but, more in general, for the growth of our economy. While wireless connectivity has significantly improved over the past few decades, it is quite behind the theoretical and technological achievable limits and it cannot address future demand. With this in mind, this project develops an innovative multi-tier hierarchical infrastructure for next-generation cellular networks with densely deployed base stations, along with a set of well-integrated cross-layer design techniques for interference management and system optimization. This proposed approach may considerably improve the rate performance and user capacity, and is promising in bridging the gap between theory and practice for broadband wireless access. To support the drastically increased mobile data traffic in wireless broadband services, this work focuses on a systematic cross-layer system optimization approach that relies on three major pillars: 1) at the physical layer, base stations with massive multiple-input multiple-output antenna systems are used; 2) at the wireless network architecture level, a multi-tier heterogeneous network approach is selected, achieving unprecedented spatial spectrum reuse; 3) at the cross-layer optimization level, a holistic network utility maximization approach is proposed, that systematically obtains layered protocol architectures from the structure of the global optimization solution. In relation to the above pillars, the fundamental challenges that will be addressed in this project are: 1) the design of integrated and power-efficient reconfigurable massive multiple-input multiple-output front-end antenna systems based on the concept of hybrid beamforming, i.e., on the optimal splitting of multiuser precoding and inter-cell interference management functions between digital baseband processing and analog radio frequency beamforming; 2) the design of hybrid beamforming schemes that exploit long-term channel statistics for inter-cell coordinated interference management, and instantaneous channel state information to achieve spatial multiplexing gain in each cell; 3) a user partitioning and scheduling approach based on clustering the user space according to quality of experience requirements, channel statistics and mobility, assigning network utility functions to the different user groups, solving the combined network utility maximization problem and systematically deriving a layered protocol architecture from the structural properties of the optimization solution. In addition, the work will significantly extend current mathematical performance analysis of wireless networks, based on advanced tools from stochastic geometry and random matrix theory, in order to assess quantitatively the performance gains over current technology of the proposed approach. Last, small-scale experiments will be conducted with software-defined radios equipped with the front end that will be developed.