Zhong, Lin2019-09-162019-09-162019-052019-08-13May 2019Ding, Jian. "Software-based Baseband Processing for Massive MIMO." (2019) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/107406">https://hdl.handle.net/1911/107406</a>.https://hdl.handle.net/1911/107406Large-Scale multiple-input multiple-output (MIMO) is a key technology for improving spectral efficiency. However, it requires massive, real-time computation. All existing solutions are based on dedicated, specialized hardware, e.g., FPGA, that is expensive, inflexible and difficult to program. This thesis investigates a software-only solution that exploits recent CPU development supporting many cores and architectural extensions for fine-grained parallelism. We present a high-performance framework for real-time, large-scale baseband processing on a many-core server. To achieve the high data rate and low latency promised by 5G, the framework utilizes data parallelism and exploits architecture features, including memory hierarchy and SIMD extensions, to accelerate computations and data movements. We report a prototype on a 36-core server and evaluate its performance.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.baseband processingmassive MIMOparallel computing5GThesis2019-09-16