Cost-Aware Green Cellular Networks with Energy and Communication Cooperation

Energy cost of cellular networks is ever-increasing to match the surge of wireless data traffic, and the saving of this cost is important to reduce the operational expenditure (OPEX) of wireless operators in future. The recent advancements of renewable energy integration and two-way energy flow in smart grid provide potential new solutions to save the cost. However, they also impose challenges, especially on how to use the stochastically and spatially distributed renewable energy harvested at cellular base stations (BSs) to reliably supply time- and space-varying wireless traffic over cellular networks. To overcome these challenges, in this article we present three approaches, namely, {\emph{energy cooperation, communication cooperation, and joint energy and communication cooperation}}, in which different BSs bidirectionally trade or share energy via the aggregator in smart grid, and/or share wireless resources and shift loads with each other to reduce the total energy cost.Comment: Submitted for possible publicatio

VINS-mono Optimized: A Monocular Visual-inertial State Estimator with Improved Initialization

State estimation is one of the key areas in robotics. It touches a variety of applications in practice such as, aerial vehicle navigation, autonomous driving, augmented reality, and virtual reality. A monocular visual-inertial system (VINS) is one of the popular trends in solving state estimation. By fusing a monocular camera and IMU properly, the system is capable of providing the position and orientation of a vehicle and recovering the scale. One of the challenges for a monocular VINS is estimator initialization due to the inadequacy of direct distance measurement. Based on the work of Hong Kong University of Technology on monocular VINS, a checkerboard pattern is introduced to improve the original initialization process. The checkerboard parameters are used along with the calculated 3D coordinates to replace the original initialization process, leading to higher accuracy. The results demonstrated lowered cross track error and final drift, compared with the original approach