Objective To explore the application of deep neural networks (DNNs) and deep
reinforcement learning (DRL) in wireless communication and accelerate the development of …

Efficient spectrum resource management in cognitive radio networks (CRNs) is a promising
method that improves the utilization of spectrum resource. In particular, the power control …

Various quality assessment parameters for multimedia traffic in the wireless network
depends on reckoning Quality of Experience (QoE) from Quality of Service (QoS). Mean …

Cognitive radios (CRs) use artificial intelligence algorithms to obtain an improved quality of
service (QoS). CRs also benefit from meta-cognition algorithms that enable them to …

This chapter discusses the use of machine learning to perform distributed resource
allocation in cognitive radio (CR) networks. There are many reinforcement learning …

As a real-time representation of physical entities in the digital world, digital twin (DT) has
been widely used in many industrial fields, which has brought remarkable efficiency …

With the development of wireless communication and Internet of Things (IoT), there are
massive wireless devices that need to share the limited spectrum resources. Dynamic …

In this paper, a resource allocation algorithm in two-way orthogonal frequency division
multiplexing (OFDM) based cognitive radio networks with quality of experience (QoE) and …

Cognitive Radio (CR) is a next-generation wireless communication system that exploits
underutilized licensed spectrum to optimize the utilization of the overall radio spectrum. A …

Cognitive radio networks (CRNs) are the solution for the problem of underutilizing the
licensed spectrum for which there are more requests in the last couple of decades. In CRNs …