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.
