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Analysis of Wireless Feature Sets for Commercial IoT Devices

This paper proposes an adaptive algorithm to maximize energy efficiency in cellular network considering a dynamic user clustering technique. First, a base station (BS) sleeping algorithm is designed, which minimizes the energy consumption to almost more than half. Then a Linear Radius User Clustering algorithm is modeled. Using feedback channel state information to the base station, the algorithm varies the mobile cell radius adaptively to minimize a total energy consumption of overall cellular network based on the threshold user density. The minimum distance where a Mobile Station can get a signal from the base station without a significant effect on human health can be located. Since the Base Station with modern scanner installed on its transmitter part can scan 390 times per second, the time scale to marginalize users from the coverage under threshold densities is in milliseconds. As a result, there is no significant effect on quality of services when the cell coverage is zoomed in/out periodically. Numerical results show that the proposed algorithm can considerably reduce energy consumption compared with the cases where a base station is always turned on with constant maximum transmit power.

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