The need to cope with the continuously growing number of connected users and the increased demand for mobile broadband services in the Internet of Things has led to the notion of introducing the fog computing paradigm in fifth generation (5G) mobile networks in the form of fog radio access network (F-RAN). The F-RAN approach emphasises bringing the computation capability to the edge of the network so as to reduce network bottlenecks and improve latency. However, despite the potential, the management of computational resources remains a challenge in F-RAN architectures. Thus, this paper aims to overcome the shortcomings of conventional approaches to computational resource allocation in F-RANs. Reinforcement learning (RL) is presented as a method for dynamic and autonomous resource allocation, and an algorithm is proposed based on Q-learning. RL has several benefits in resource allocation problems and simulations carried out show that it outperforms reactive methods. Furthermore, the results show that the proposed algorithm improves latency and thus has the potential to have a major impact in 5G applications, particularly the Internet of Things.
As with previous generations of mobile cellular networks, rural regions are projected to face financial and technological challenges in deploying 5G services. At the time, researchers all around the world are investigating the feasibility of utilizing TV White Spaces (TVWS). TVWS is an underutilized/unused section of television spectrum that might be used as a low-cost alternative to typical licensed wired/wireless broadband networks, as well as to bridge the broadband service availability gap between rural and urban regions. A feasible alternative is to deliver TVWS services via High Altitude Platforms (HAPs) for many developed and developing nations to deliver broadband services to a large proportion of their rural and low-income populations. This article examines the advantages of utilizing TVWS spectrum from HAPs as well as the challenges connected with this type of communication architecture. This article examines the advantages of leveraging TVWS spectrum from HAPs as well as the challenges that come with this type of communication architecture. They distribute messages across a large region while monitoring and optimizing radio resource allocation, owing to their position in the sky and the centralized design of the communication system. The article assesses the performance of such a system using the IEEE 802.22 standard and the ITU-R P.452 free space path-loss model. Moreover, this article pointed out the main challenge of using TVWS spectrum from HAP system.
National regulatory authorities (NRAs) in developing countries need an accelerated means to formulate technical regulations for the telecommunications sector. This will enable countries to gain maximum benefits from the rapid advances in technology. The existing regulation-making processes are time-consuming and do not cope with the emergence of global technological changes. This article presents an efficient and quicker approach to formulate regulatory framework to govern the wireless technologies that are based on the Dynamic Spectrum Access (DSA) technique. The approach utilises Multicriteria Decision Analysis (MCDA) tools. The article uses a case study to evaluate dominant Dynamic Spectrum Management (DSM) frameworks. Finally, a sustainable DSM framework that has potential to address the digital divide challenges in the context of developing countries is proposed.
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