TAES: Traffic-Aware Energy-Saving Base Station Sleeping and Clustering in Cooperative Networks -Technical Report-

The increasing demand for high capacity in cellular networks requires huge energy consumption. Thus, energy efficiency is becoming a vital design goal in cellular networks. We consider energy efficient base station sleeping and clustering problems in cooperative cellular networks where clusters of base stations jointly transmit to users. Our key idea of energy saving is to exploit a spatio-temporal fluctuation of traffic demand, which is to use minimal energy to provide capacity slightly greater than varying traffic demand. Then, energy saving is possible without capacity loss. However, it is highly challenging to design such traffic-aware algorithms without the future traffic demand information. To overcome this, we develop algorithms using queue instead of the future traffic information. For BS clustering problem, we propose an optimal algorithm that has polynomial complexity. For BS sleeping problem, which is a complex combinatorial problem, we propose two algorithms; One finds an optimal solution with reduced complexity compared to the exhaustive search, and the other finds a near-optimal solution with polynomial complexity. The gap between the optimal solution and the near-optimal solution is also derived. Through extensive simulations we show that the proposed algorithms can save significant energy when traffic load is low while guaranteeing the maximum capacity when traffic load is high. Jihwan Kim and Song Chong are with the Department of Electrical Engineering, KAIST, Daejeon, Republic of Korea. (e-mail: [email protected], [email protected]) Hyang-Won Lee is with the Department of Internet & Multimedia Engineering, Konkuk University, Seoul, Republic of Korea. (e-mail: [email protected].)