This work demonstrates the potential of deep reinforcement learning techniques for transmit
power control in wireless networks. Existing techniques typically find near-optimal power …

To solve the policy optimizing problem in many scenarios of smart wireless network
management using a single universal algorithm, this letter proposes a universal learning …

Integrating artificial intelligence (AI) into wireless networks has drawn significant interest in
both industry and academia. A common solution is to replace partial or even all modules in …

Many countries and organizations have proposed smart city projects to address the
exponential growth of the population by promoting and developing a new paradigm for …

With the widespread deployment of wireless technologies and IoT, 5G wireless networks will
support various communication connectivity and services for the huge number of wireless …

Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …

Wireless networks have grown into an essential component of modern life as a result of the
proliferation of wireless technology over what has been a decade. The science underlying …

As a new machine learning method, deep reinforcement learning has made important
progress in various fields of people's production and life since it was proposed. However …

This paper presents a deep reinforcement learning (DRL) solution for power control in
wireless communications, describes its embedded implementation with WiFi transceivers for …

With the evolution of Space-based backbone networks, the demand for enhanced efficiency
and stability in network resource allocation has become increasingly critical, presenting a …