… This paper proposes a deep reinforcement learning (DRL) based framework, with the goal
of maximizing the long-term tradeoff between energy efficiency (EE) and spectral efficiency (…

… This article proposes a distributed deep reinforcement learning (DRL)-based power allocation
(DDPA) scheme based on DRL to maximize the network SE of the RSMA-enabled F-RAN …

… leverage deep reinforcement learning (RL) in spectrum management, including both spectrum
… For feasibility and practicability, the feedback processes of spectral efficiency information …

… We, then, adopt an independent learning framework and solve the sum spectral efficiency
maximization problem using deep Q-Learning; • Finally, we evaluate the performance of the …

… algorithm via deep reinforcement learning… efficiency or spectral efficiency. Further, we
develop a beam training strategy which can maximise either energy efficiency or spectral efficiency …

… spectrum constraints, the Power Control and Resource Allocation (PCRA) are other significant
issues in UDN, which affect the Energy Efficiency (EE) and the Spectrum Efficiency (… Deep …

… To further illustrate this point, in Table III, we show the spectral efficiency in bps/Hz achieved
when the number of available frequency bands varies from 2 to 8. It is clear that the DDQN …

… management in wireless communication, such as spectrum sharing [6], access … on spectral
efficiency, power efficiency, network convergence, etc., which call for more efficient spectrum …

… Abstract—In this letter, we present a deep reinforcement learn… imperfection in the SIC on
spectral efficiency. As compared to the … is to maximize spectral efficiency and allocate resources …

… where σ2 is the additive white Gaussian noise power spectral density at receiver n. Assuming
normalized bandwidth, the downlink spectral efficiency achieved by link n on subband m …