Automatic design for analog/RF front-end system in 802.11ac receiver

Although automatic optimization for individual analog/RF modules has been studied for many years, design automation for analog/RF systems that contain a complicated hierarchy of mixed-signal modules is still very challenging as the lack of an efficient way to bridge between different level descriptions in the design hierarchy. In this paper, we applied sparse regression as a modeling tool to model the modules that need to be optimized and embedded the modules in a large system to accomplish a realistic 802.11ac system design. The wireless system specification (e.g. bit error rate) for comprehensively evaluating the analog/RF front-ends is used as the optimization objective. The proposed method is implemented by linking the block-level performance metrics to the wireless system using mixed-signal simulation platform with performance modeling and Pareto optimal fronts. By this method, the receiver for 802.11ac systems is successfully designed and the worst error vector magnitude (EVM) is decreased by 34% from coarse design.

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