NeTS: Large: Collaborative Research: Practical Foundations for Networking with Many-Antenna Base Stations

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To meet the exponentially growing demand in mobile data, opening up more spectrum for data services is not enough. The wireless industry and research community are desperately searching for technologies that can use spectrum more efficiently. The trend in wireless networks is reducing cell sizes combined with increasing number of antennas per device and especially, per base station. In theory, the efficiency of spectrum use increases proportionally to the number of base-station antennas; a large number of antennas promises not only a large gain in spectral efficiency but also a much simplified system. However, it remains an open question how these theoretical promises can translate into spectral efficiency gains in practice. Indeed, simply increasing the number of base-station antennas will break today's network system designs at many places, across several layers. The goal of this project is to provide the much needed practical foundations for networking with many-antenna base stations. The project will not only explore novel approaches toward scaling up the number of base-station antennas to 10s and even 100s; but also rethink the entire network architecture exploiting the emergent properties as the number of base-station antennas grows large. With emphasis on realizable network designs using the NSF CRI-funded ArgosNet testbed, the project team will work closely with our corporate partners to ensure that project outcomes impact the next-generation of wireless networks. The project will establish a unique inter-university education and research program, that will involve both undergraduate students and underrepresented populations. Toward providing the practical foundations for many-antenna MIMO networks, the project goal will be innovations in three related thrusts. (i) Scalable Control and Coordination: the project will develop scalable designs of control and coordination functions for multi-user multi-input, multi-output (MU-MIMO) networks. In particular, it will design a suite of protocols for network-wide CSI collection that significantly reduce its overhead. (ii) Scalable Resource Allocation. The project will develop novel resource allocation solutions for many- antenna MIMO networks in order to support both high data rates and low-latency requirements. It will contribute a novel scalable scheduling framework that use slow-time-scale information or statistical channel information and design scheduling policies based on MIMO rateless codes. (iii) Empirical Foundations from Measurements. The project will perform previously impossible real-time measurements of MU-MIMO channels in order to understand channel correlation, variation and reciprocity and their relationships with spectrum band, mobility, and hardware impairment. In particular, the project will derive novel models, reciprocity calibration methods, and novel channel state representations that will power research in network designs.