Spectrum breathing and cell load balancing for self organizing wireless networks

Abstract

In this paper, we develop a self organizing mechanism for spectrum breathing and user association in cellular networks employing fractional frequency reuse. In doing this we specifically focus on flow-level cell load balancing under spatially inhomogeneous traffic distributions. Our work adaptively changes the spectrum bandwidth of each base station (BS) so that spectrums of the BSs breathe in and out to balance the loads of the BSs. Spectrum breathing is further combined with α-optimal user association for better load balancing. Our problem is challenging in the sense that the problem is not necessarily a convex optimization. To tackle the difficulty we decouple spectrum breathing and user association by introducing the concept of reference load, which is independent of the spectrum bandwidth. We propose an iterative algorithm that always converges to a fixed point, which is possibly an optimal solution. We verify that the proposed algorithm achieves the optimality by performing exhaustive search. Our extensive simulations demonstrate that the proposed algorithm significantly improves the system performs: decreasing the delay more than 10 times or increasing the admittable traffic load by more than 125%.