High-resolution ADCs are essential components in many biomedical and environmental sensing applications. As the demands for wearable, miniature and point-of-care systems keep increasing, the design requirements for high-resolution ADCs also get more stringent, with strong emphasis on energy efficiency, reliability, and low cost. Over the past few years, many design techniques have been developed to excel the figure-of-merit (FoM) of high-resolution ADCs, where the state-of-the-arts has gotten really close to the theoretical limit.

ESPRIT-based high-resolution parameter estimation algorithms in DFT beamspace have been proposed as efficient gridless channel estimation schemes for MIMO OFDM systems in the millimeter wave (mmWave) band. Compared to conventional ESPRIT-based algorithms in element space, the DFT beamspace approach can be applied to MIMO systems with hybrid analog-digital architectures. Moreover, this approach significantly reduces the training overhead for communication systems operating in the mmWave band. It involves coarse and fine estimation steps. 

The architecture and deployment of mobile networks has experienced dramatic transformation in the past decade, enabled through embracing “disaggregation” at different levels. This in turn has led to diversification of the ecosystem. At the same time, disaggregation of mobile networking systems introduces new challenges. In this talk, I’ll start by giving my perspective on the key drivers (economic and beyond) behind the remarkable transformation of the mobile networking landscape and outline three levels of disaggregation that played a pivotal role.