Dynamic Spectrum Management for Intercell Interference Coordination in LTE Networks Based on Traffic Patterns

Next-generation cellular networks will provide users with better experience employing smaller cells, which results in high dynamics and strong interference. Conventional intercell interference coordination (ICIC) approaches are based on fixed or dynamic frequency reuse, which more or less underutilize frequency resources or reduce network-wide performance. As a result, the benefit brought by ICIC is questionable in practical networks. In this paper, we tackle this problem from the self-organizing network (SON) viewpoint by optimizing fractional frequency reuse (FFR) and adapting to dynamic traffic maps. The approach proposed by this paper formulates this problem as an optimization problem with multiple key performance indicators (Multi-KPIs), and a traffic-based dynamic spectrum management (DSM) algorithm is proposed to reduce the call drop and block ratio (CDBR) and to also improve the network throughput. To reduce further the cost of spectrum partition and assignment, we conduct data mining for the traffic maps from realistic networks and then obtain traffic stable states for a longer specific period of time. DSM based on the stable states (DSM-SS) approach brings further benefits for Long Term Evolution networks in terms of operational costs. Simulation results show that the proposed schemes significantly outperform the traditional schemes.