Femtocell Scheduling as a Restless Multiarmed Bandit Problem Using Partial Channel State Observation

In this paper, we address the problem of channel allocation for femtocells that share the use of regular macrocell spectrum. The femto basestation (FBS) scheduling problem is formulated in the form of restless multiarmed bandit (RMAB) framework. Our goal is to choose the arms/channels that maximize the total expected discounted reward over infinite horizon while minimizing the induced interference due to channel sharing with macrocell. Without direct observation of true channel state, we use the available macrocell user feedback known as channel quality indicator (CQI). In general, the RMAB problem is P-SPACE hard. We propose a heuristic low complexity indexing policy referred as approximated Whittle index to rank available channels for FBS. Although finding a closed form channel ranking solution typically involve dynamic programming, we show that based on the partial channel information within CQI, there exists a closed form for the channel index. Moreover, we demonstrate the performance advantage of the proposed indexing policy over a myopic policy.