We propose a decentralized downlink scheduling protocol for wireless cellular networks that allows each base station to control its transmission power. On the beginning of each scheduling period, neighbor base stations exchange their local system states, i.e., channel, traffic and position statistics of their local mobile users. But on each slot of the current scheduling period, the base stations may not be able to receive full information from neighbor cells. Therefore, to enable the base stations to make optimal decisions, for user scheduling and transmission power control, we develop an analytical optimization framework, based on the theory of Partially Observable Markov Decision Process. To help a base station, this decision-theoretic approach uses the history of observations about neighbor base stations system statistics and their scheduling policies. Simulations show that our approach is more efficient than existing centralized scheduling approaches which due to the high complexity they do not allow base stations to communicate with each other.
[1]
Sheldon M. Ross,et al.
Introduction to probability models
,
1975
.
[2]
Vincent K. N. Lau,et al.
Delay-Optimal User Scheduling and Inter-Cell Interference Management in Cellular Network via Distributive Stochastic Learning
,
2010,
2010 IEEE Global Telecommunications Conference GLOBECOM 2010.
[3]
Kevin P. Murphy,et al.
A Survey of POMDP Solution Techniques
,
2000
.
[4]
Yung Yi,et al.
Adaptive multi-pattern reuse in multi-cell networks
,
2009,
2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks.
[5]
Edward J. Sondik,et al.
The Optimal Control of Partially Observable Markov Processes over a Finite Horizon
,
1973,
Oper. Res..
[6]
David Gesbert,et al.
Binary Power Control for Sum Rate Maximization over Multiple Interfering Links
,
2008,
IEEE Transactions on Wireless Communications.