Embedded substrate noise measurement for mixed-signal/radio frequency/microwave integrated circuits

Due to the ever-growing demand for IC production cost reduction, there are more and more system-on-chip (SoC) designs that require the integration of analog/radio frequency (RF)/microwave and digital circuits on the same die arise and which pose challenges to RF/microwave testing.;Traditional RF/microwave testing that relies on expensive automated test equipment (ATE) systems cannot keep up with the pace of the growing complexity of the testing process without increasing test cost and is becoming one of the major obstacles for overall IC production cost reduction. Embedded testing is a potential solution to answer those challenges. The basic idea of embedded testing is to move high-speed and high-bandwidth portions of expensive ATE system onto the IC device-under-test (DUT) by additional design-for-test (DFT) circuitry, thus reducing the requirements and eventually the cost of external ATE system.;SoC designs suffer from substrate noise coupling due to the finite isolation provided by the semiconductor substrate. The study of substrate coupling effects is especially challenging in terms of circuit design and modeling.;The proposed embedded substrate noise measurement system consists of an off-chip broadband signal source and example test circuits integrated with the DUT. The signal source acts as a noise generator and injects well-controlled signals into the substrate, and then the embedded test circuit will extract useful information from the response of the detector and report the data as baseband signals; the baseband signals are delivered off-chip to an external tester.;First, a low-frequency, on-chip substrate noise measurement test vehicle is designed and used to demonstrate the embedded system feasibility. Next, a system capable of measuring substrate noise coupling over a very wide frequency span up to the millimeter wave range is demonstrated. Finally, an application of the embedded measurement system is presented and a semi-physical macromodel is extracted based on experimental data.