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How machine learning can improve siting for small cells

October 31, 2019

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Small cell deployments have followed a few broad trends in the past few years. The first wave serve to fill in holes in network coverage; the next wave was used to augment capacity in geographic bottlenecks. The third, and ongoing wave, is partly a continuation of the second wave but bolstered by the sheer density requirements of 5G, particularly 5G that uses millimeter wave frequencies.

Given this paradigm, coupled with the typical site acquisition, backhaul, power, rent issues associated with small cells, operators need to locate small cells in a manner that maximizes return on investment.

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