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Small cell networks offer a promising and viable approach to meeting the increasing demand for high-data-rate wireless applications. With the expected increase in the number of small cell deployments, energy efficiency (EE) is a crucial system design parameter that demands consideration from an eco-sustainability perspective. One way to improve EE is to switch off small cell base stations (BSs) or to keep them in energy-saving mode while preserving the quality of service (QoS) experienced by users. With “bits/joule” as the metric, we aim to optimize EE with the introduction of several levels of sleep depths. Using a stochastic geometry-based heterogeneous cellular network (HCN) model, we derive coverage probability, average achievable rate, and EE in heterogeneous K-tier wireless networks with different sleep modes for small cells. Then, we try to maximize EE under 1) a random sleeping policy and 2) a strategic sleeping policy, with constraints on both coverage probability and wake-up times. Due to the nonconvexity of EE, we propose an alternative low-complexity near-optimal solution by maximizing the lower bound of EE. We use an alternating iterative approach to solve the resulting multivariable optimization problem. Simulation results confirm the effectiveness of the scheme. With improvements of approximately 30% in EE with random sleeping policy, simulation indicates that instantaneous EE can be further improved by 15% with a strategic sleeping policy.
Liu et al. (Fri,) studied this question.