Design of Self Calibrating and Error Resilient Mixed-Signal Systems for Signal Processing, Communications and Control

Modern real-time systems encompassing signal processing, communications and control are being increasingly designed in ways that allow them to dynamically adapt to changing workload conditions for reasons of minimizing power consumption and extending system lifetime. Such adaptive systems need to carefully calibrated for process variability, thermal, electrical degradation, noise and failure conditions that impact the fidelity of the signals involved and the Quality of Service (QoS) delivered to the end customer. We consider two sources of errors in such adaptive systems: (a) parametric variations in the performances of analog/RF electronics, sensors/transducers and timing of digital circuitry and (b) noise in analog and digital circuitry that result in loss of analog signal quality and digital soft errors. First, failure mechanisms and associated fault models are discussed for both permanent failures as well as transient errors particularly in the light of the adaptive nature of such systems (vis.a. vis. low power operation). Next, built-in testing and diagnosis of digital, analog and mixed-signal/RF circuits and subsystems is discussed, covering both catastrophic defects as well as parametric failure conditions. Advanced methods for post-manufacture tuning of digital and analog/RF devices to maximize manufacturing yield and field reliability are presented. Issues related to testing and tuning of adaptive systems with analysis of test cases are analyzed. Finally, we present on-line testing and error correction methods for robustness of end-to-end mixed-signal systems to transient errors and induced noise. Applications to signal processing, wireless communications and control systems are discussed.