Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

On modeling coverage and rate of random cellular networks under generic channel fading

In this paper we provide an analytic framework for computing the expected downlink coverage probability, and the associated rate of cellular networks, where base stations are distributed in a random manner. The provided expressions are in computable integral forms that accommodate generic channel fading conditions. We develop these expressions by modeling the cellular interference using stochastic geometry analysis, then we employ them for comparing the coverage resulting from various channel fading conditions namely Rayleigh and Rician fading, in addition to the fading-less channel. Furthermore, we expand the work to accommodate the effects of random frequency reuse on the cellular coverage and rate. Monte-Carlo simulations are conducted to validate the theoretical analysis, where the results show a very close match.     

A Survey on Dynamic Spectrum Access for LTE-Advanced

Increasing utilization of LTE-Advanced (LTE-A) to meet the rapid growth in wireless bandwidth demand is an important focus for current research. Dynamic spectrum access (DSA) is a promising approach that can be utilized to improve bandwidth utilization in LTE-A systems and networks. The application of DSA is not limited to commercial use but can also be applied to provide access to other systems including public safety communication systems and device to device communications. This paper provides a general overview of DSA and a review of the recent research into the use of DSA to improve bandwidth utilization in LTE-A networks. DSA is a flexible technique that is being applied to different network technologies including cognitive radio, mobile cellular femtocells and wireless relay.