Abstract Deep Reinforcement Learning (DRL) has gained significant adoption in diverse
fields and applications, mainly due to its proficiency in resolving complicated decision …

In traditional cognitive radio networks (CRNs), users are generally divided into two
categories: primary users (PUs) and secondary users (SUs). The transmission rates of …

Due to the ever‐growing applications and services of the Internet of Things (IoT), designing
energy‐efficient and spectral‐efficient transmission schemes to support IoT devices for the …

This paper investigates the problem of spectral efficiency maximization in an underlay
cognitive radio network (CRN) utilizing rate-splitting multiple access (RSMA) transmission …

Background: Radio spectrum is natural and the most precious means in wireless
communication systems. Optimal spectrum utilization is a key concern for today's cutting …

The rapid development of mobile devices and wireless network technologies have made
them indispensable. This has created a demand for faster networks and longer battery life …

Electric vehicle (EV) fast charging stations often experience high peak charging loads and
strong fluctuations. Therefore, developing an energy management strategy for the energy …

Aiming at the problem that the downlink of the aerospace measurement and control system
has weak anti-dynamic interference performance in the dynamic interference environment …

In this paper, a multi-user, multi-task and multi-server scenario for low earth orbit (LEO)
satellite edge computing system is established, and a joint optimization algorithm for …

In cognitive radio systems, cooperative spectrum sensing (CSS) can effectively improve the
sensing performance of the system. At the same time, it also provides opportunities for …