Wireless communication from energy storage cabinet to base station

4 FAQs about [Wireless communication from energy storage cabinet to base station]

Does deep reinforcement learning increase energy consumption in wireless communication systems?

However, the deployment of numerous small cells results in a linear increase in energy consumption in wireless communication systems. To enhance system efficiency and establish green wireless communication systems, this paper investigates base station sleeping and power allocation strategy based on deep reinforcement learning in UDNs.

How to conserve energy in a wireless sensor network?

Various strategies, such as duty cycle scheduling, EE routing, energy harvesting and EE Medium Access Control can be used to conserve energy in a wireless sensor network . Mobile videos are accountable for the rigorous consumption of energy as they involve the usage of screen display, CPU, audio/video decoder and network connectivity.

Are base station sleep and power allocation related?

Each SBS n is considered an agent, and each agent can make decisions based on the surrounding environment to get the reward value for the next round of exploration. In this paper, the base station sleep and power allocation are two closely related mechanisms that jointly optimize the resource management of SBSs through DQN.

How to reduce power-intensive base stations?

To address the issue of power-intensive base stations, proposed a combined approach involving base station sleep and spectrum allocation. This approach aims to discover the most efficient operating state and spectrum allocation for SBS to minimize power consumption and network disturbance.

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