Collaborative Research: SWIFT: Small: Cross-Layer Interference Management: Bringing Interference Alignment to Reality

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The demand for wireless data traffic along with the scale of users grows exponentially, while the current approach to meet such scaling is to avoid interference. Unfortunately, interference avoidance techniques cannot accommodate these scaling needs. To support large-scale deployments, there is a need to enable multiple users to share the same spectrum. In other words, the interference must be mitigated and exploited rather than avoided. However, prior theoretical efforts have resulted in minimal gains in practice. This project bridges the gap in theory and practice, and jointly designs and develops antennas and algorithms in PHY and MAC layers enabling orders of magnitude more spectrum-efficient communications. The designed solutions would enable connectivity to all classes of devices, autonomous driving, health-care, and IoT, and will make the connectivity cheaper for all segments of society. The project will result in training graduate students and fosters interdisciplinary research. The proposed activities are designed to engage students from all backgrounds focusing on those from underrepresented groups.The proposal focuses on developing Interference Alignment (IA) techniques that work at the finite Signal-to-Noise (SNR) regime. The proposal has two thrusts - one focused on the uplink and another focused on the downlink. The PIs plan to use quasi-randomly oriented antenna elements to accomplish the desired objectives. (1) Present new transmit and receive antenna hardware structures at base-stations to create favorable environments for interference management; (2) Develop new physical-layer algorithms that exploit the characteristics of the proposed antennas and increase by order(s) of magnitude the number of users sharing the same frequency slot, without needing channel information at the transmitter; (3) Develop PHY-layer algorithms and MAC-layer protocols to exploit the proposed antenna designs to enable interference alignment for a large number of users; (4) Develop novel algorithms that enable deploying the proposed research easily on existing next-generation cellular (5G) and WiFi (WiFi-6) protocols; (5) Evaluate the proposed techniques through simulations and real-world experiments with hardware and software implementation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.