The classical approach to wireless communication is to isolate communication links by maximizing signal strength and minimizing interference between users. This simple philosophy is supported by a rich theoretical foundation which has inspired powerful coding techniques and protocols that lie at the heart of modern wireless systems. However, these systems have recently become victims of their own success as the rising density and data requirements of wireless devices have led to a surge in interference. Fortunately, an emerging body of work indicates that the phenomenon of interference may in fact represent an untapped opportunity for increasing the spectral and energy efficiency of next-generation wireless systems. Although many interference-aware communication strategies have been proposed in the literature, the promised gains have been mostly limited to the theoretical realm.
The objective of this project is to create practical interference-aware wireless protocols that can operate near the performance predicted by theoretical bounds in terms of throughput, energy efficiency, and reliability. The project is organized into three complementary thrusts that encompass theory, algorithms, and practice. The first thrust investigates lattice-based constellations and low-complexity codes for the compute-and-forward strategy, which enables receivers to decode linear combinations of transmitted codewords. Compute-and-forward can in turn be used as a building block for realizing interference-aware protocols such as physical-layer network coding and multiple-user MIMO (multi-input-uulti-output) systems. The second thrust aims to implement these protocols on a three-node WARP (Wireless Open-Access Research Platform) testbed. A series of carefully designed experiments will be used to compare the performance of interference-aware strategies while accounting for overhead costs. The third thrust leverages the data collected from these experiments to revise channel models to capture key features that impact the performance of interference-aware strategies such as asynchronism and channel fluctuations. These models will be used to revisit the theoretical foundations of interference-aware strategies and tailor them to the channels encountered in practice. This project features several outreach efforts including undergraduate research experiences connected to the WARP testbed and a public repository of training modules and videos.
