A Scalable Method for Minimizing Beam-Training Overhead in mmWave CommunicationsThe NeedAs mmWave technology becomes the backbone of 5G and other advanced communication systems, the demand for fast, reliable, and scalable beamforming solutions has surged. Traditional beam-training methods are computationally intensive and time-consuming, leading to delays in establishing high-quality connections. A solution that minimizes latency, optimizes signal performance, and supports large-scale antenna arrays is essential for addressing the growing needs of telecommunications, virtual reality, autonomous vehicles, and remote healthcare. The TechnologyThis invention enhances mmWave communications by employing compressive sensing techniques to estimate the direction and complex gain of signal paths, synthesizing the globally optimal beam. The approach significantly reduces the computational overhead and time required for beam-training by narrowing the search space for path parameters. It efficiently distinguishes multipath directions and ensures coherence of complex gains, enabling constructive interference at the receiver. The solution is compatible with Commercial-Off-the-Shelf (COTS) mmWave devices, making it a cost-effective upgrade for existing systems. Designed to scale across various antenna array sizes, it is well-suited for large-scale deployments in future communication networks. Commercial Applications
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Tech IDT2024-307 CollegeLicensing ManagerRandhawa, Davinder InventorsCategories |