Vector Network Analyzer for Spatio-Temporal Noise-Shaped Beamforming and 5G applications

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Antenna arrays have been around since the early 20th century. By properly combining the signals received by each antenna, an array effective radiation pattern (beam) is reinforced in a desired direction while rejecting signals from other directions. The ability to dynamically adjust the beam orientation, and to form more than one beam, resulted in the wide adoption of arrays for satellite communications and military applications. The recent interest in arrays has been driven by the development of the fifth-generation (5G) wireless networks, which promise faster data rates and improved connectivity. While the market for antenna arrays was already $3.5B in 2008, the development of 5G networks will increase this dramatically. Following this opportunity, the applicant's research program, funded by Canada Research Chair, NSERC Discovery, and NSERC Discovery Accelerator, focuses on developing novel antenna arrays to contribute to this rapidly growing market. Antenna arrays require receivers and beamformers. While the traditional designs replicate receivers at each antenna, such approaches ignore the physical constraints on the received electromagnetic waves (EMWs). Specifically, Einstein's Theory of Special Relativity enforces a region of causality (aka the “light cone”) outside of which no propagating EMWs exist. Each receiver inadvertently contaminates incoming signals with its noise and distortions. Unlike the incoming plane waves, however, the noise/distortions can exist outside the light cone. In our research program, we develop receivers that place undesired noise/distortions outside the light cone where they are consequently filtered out by beamformers. This way of removing noise and distortion is similar to the way delta-sigma circuits employ oversampling to shape noise outside the band of the desired signal. We however use signal sparsity in the spatial-temporal frequency space to avoid both spatial and temporal oversampling and predict considerable improvement in their sensitivity and linearity (e.g. >15dB increase in spurious-free dynamic range). This improvement can be traded off against receiver specifications resulting in savings (power, chip area, cost, etc). It is expected that such a novel approach to antenna arrays will attract industrial interest and contribute to the Canadian economy. The RTI funds will be used to replace our malfunctioning, obsolete, and inadequate network analyzer (NA) to enhance HQP training, enable our HQP to experimentally demonstrate their novel antenna arrays, and disseminate the research outcomes at high-impact venues. An NA is a key tool for any radio-frequency laboratory without which most RF measurements are impossible. Experimental demonstration is important in our field and particularly when dealing with complex systems such as beamformers where simulation do not account for all subtleties.