Enhancing Spectrum Utilization in Dynamic Cognitive Radio Systems

Cognitive radio (CR) is regarded as a viable solution to enabling flexible use of the frequency spectrum in future generations of wireless systems by allowing unlicensed secondary users (SU) to access licensed spectrum under the specific condition that no harmful interference be caused to the licensed primary users (PU) of the spectrum. In practical scenarios, the knowledge of PU activity is unknown to CRs and radio environments are mostly imperfect due to various issues such as noise uncertainty and multipath fadings. Therefore, important functionalities of CR systems are to efficiently detect availability of radio spectrum as well as to avoid generating interference to PUs, by missing detection of active PU signals. Typically, CR systems are expected to be equipped with smart capabilities which include sensing, adapting, learning, and awareness concerned with spectrum opportunity access, radio environments, and wireless communications operations, such that SUs equipped with CRs can efficiently utilize spectrum opportunities with high quality of services. Most existing researches working on CR focus on improving spectrum sensing through performance measures such as the probabilities of PU detection and false alarm but none of them explicitly studies the improvement in the actual spectrum utilization. Motivated by this perspective, the main objective of the dissertation is to explore new techniques on the physical layer of dynamic CR systems, that can enhance actual utilization of spectrum opportunities and awareness on the performance of CR systems. Specifically, this dissertation investigates utilization of spectrum opportunities in dynamic scenarios, where a licensed radio spectrum is available for limited time and also analyzes how it is affected by various parameters. The dissertation proposes three new methods for adaptive spectrum sensing which improve dynamic utilization of idle radio spectrum as well as the detection of active PUs in comparison to the conventional method with fixed spectrum sensing size. Moreover, this dissertation presents a new approach for optimizing cooperative spectrum sensing performance and also proposes the use of hidden Markov models (HMMs) to enabling performance awareness for local and cooperative spectrum sensing schemes, leading to improved spectrum utilization. All the contributions are illustrated with numerical results obtained from extensive simulations which confirm their effectiveness for practical applications

KidBright: An Open-Source Embedded Programming Platform with a Dedicated Software Framework in Support of Ecosystems for Learning to Code

The concept of coding at school has enabled educators and parents around the globe to become interested in coding as, these days, coding is regarded as a gateway to computational thinking for children. However, coding education in Thailand appears to lag behind that of many other countries due to the lack of accessible coding learning resources suitable for students as well as the limited number of teachers with coding experience. Regarding these issues, we have developed an open-source hardware-based coding platform named KidBright, based on these requirements: 1. making coding simple for novice learners through the use of graphical blocks with Thai and English support; 2. inspiring young students to develop creative embedded applications with minimal effort; and 3. providing sustainable support for coding education. KidBright is proposed as a coding learning tool that can motivate children to learn to code and develop embedded system projects using its block-based coding environment, the KidBright IDE, in conjunction with its embedded device, the KidBright board. KidBright is distinguished from other embedded programming platforms due to the deployment of a dedicated software framework as the backend of the KidBright IDE. In this article, we introduce KidBright and present the design, architecture, and demonstrations of the software framework, the key roles of which are to conceal low-level hardware issues from learners and to enable makers to develop new command blocks and hardware peripherals in support of KidBright. We claim that, with this particular design, KidBright can help support coding education sustainably. In particular, we present how a small research team introduces coding to a large number of learners who have little or no coding experience, resulting in an impact on coding education in the country