Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Continuously growing energy consumption in cellular networks motivates the research towards energy saving approaches. Among previous work, many studies suggest different base station shutdown strategies to reduce the transmission por in case of low or no traffic. Besides the strategy that shutdown base stations completely, our work suggests and evaluates the usage of partial shutdown strategy for multi-antenna base station systems, which allows a better adaptation of por to the network traffic which required by the users.  use Markov Chain to model user traffic and select appropriate state beten different por-states of the multi-antenna base station.  evaluate the dependency of the energy saving on the number of antennas and the radius of cells, preserving the coverage of a certain region. The results show that systems with higher number of antennas can better adapt the por to the user traffic requirements. Further,  search for optimal cell radius, showing that it has more important role in case of higher user traffic.
['Iztok Humar', 'Jing Zhang', 'Zg Wu', 'Lin Xiang']
I am writing a research paper on a idea Energy Savings Modeling and Performance Analysis in Multi-Power-State Base Station Systems
[{"from": "human", "value": "I am writing a research paper on a idea Energy Savings Modeling and Performance Analysis in Multi-Power-State Base Station Systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Continuously growing energy consumption in cellular networks motivates the research towards energy saving approaches. Among previous work, many studies suggest different base station shutdown strategies to reduce the transmission por in case of low or no traffic. Besides the strategy that shutdown base stations completely, our work suggests and evaluates the usage of partial shutdown strategy for multi-antenna base station systems, which allows a better adaptation of por to the network traffic which required by the users.  use Markov Chain to model user traffic and select appropriate state beten different por-states of the multi-antenna base station.  evaluate the dependency of the energy saving on the number of antennas and the radius of cells, preserving the coverage of a certain region. The results show that systems with higher number of antennas can better adapt the por to the user traffic requirements. Further,  search for optimal cell radius, showing that it has more important role in case of higher user traffic."}]