Measurements and Characterization of Twisted Radio Wave Multipath for Indoor Wireless Communication and Security System

Abstract

This paper presents a novel twisted radio wave based wireless communication system that has the capability to discriminate against strong reflections in indoor multipath environment. The twisted wave transmitter is designed using a uniform circular array, which is capable of transmitting different OAM modes simultaneously and the receiver is designed to match to the transmitted OAM mode. The measurement results obtained from the experiments carried out in different indoor environments and different propagation scenarios show that our proposed twisted radio wave system can provide a stable transmission link even in the presence of existing ZigBee and Wi-Fi signals, which are operating in the same frequency band. A good general agreement between the simulations and measurement results shows the accuracy and applicability of our proposed wireless communication system in such indoor multipath environments.

Big Data Scenarios Simulator for Deep Learning Algorithm Evaluation for Autonomous Vehicle

“…Big data is increasingly involved in the development of self driving or autonomous vehicles (AV) [1] especially with the advent of 5G technology and applications [2]- [4]. As manual collection of high volume of data required for training, testing and evaluating a machine learning algorithm [5], [6] used in AV is highly unrealistic with so many possible environment scenarios, one viable way to address is the use of computer graphic simulator systems such as CARLA [7], CAIAS [8] and AirSim [9].…”