Traffic-aware power adaptation and base station sleep control for energy-delay tradeoffs in green cellular networks

Abstract

Traffic-aware resource allocation and base station (BS) sleep control are key methods for energy saving in cellular networks. In this paper, first, we consider the control problem of how to adapt transmit power according to flow-level traffic variations, which leverages the tradeoff between energy consumption and delay performance. Based on different time scales of traffic variations, two power adaptation strategies are investigated: load-aware and queue-aware. The two strategies adapt transmit power according to flow arrival rate and instantaneous number of flows, respectively. Optimal solutions are given for both strategies. Since the optimal solution of the queue-aware strategy has no explicit form, tight bounds are derived as an approximation. Simulation results show that the two strategies perform closely in terms of energy consumption and average delay, while the queue-aware strategy is better in the tail distribution of delay and is more robust to system parameter variations. Secondly, for the load-aware strategy, with more practical concerns like the total BS energy consumption and BS sleep control taken into account, the relationship between energy consumption and delay is explored and energy-optimal rate can be obtained under certain conditions. Two threshold-based BS sleep strategies are investigated where the optimal threshold and rate are derived respectively.