Optimisation methods for dynamic frequency planning in OFDMA networks

To overcome interference, OFDMA networks support different but fixed frequency reuse schemes and subchannel allocation techniques. However, these fixed schemes and techniques are not the most suitable solutions in mobile scenarios, where the behaviour of the channel and the users are continuously changing during the day-time. This paper presents a new approach to the frequency assignment problem adapted to OFDMA networks, called Dynamic Frequency Planning, which in turn may decrease the interference and increase the capacity of the network by around 20%. DFP operates in a regular basis, adapting the network configuration to the time-dependent channel conditions and user requirements. On the other hand, DFP uses novel algorithms to estimate the inputs of the frequency assignment problem and tailored versions of meta-heuristic such as Simulated Annealing and Tabu Search, or Greedy Algorithms to solve it. Further discussion about the trade off between the quality of the solution and computing time when using meta-heuristic or greedy algorithm is provided. This paper also indicates, when running DFP, how to check the improvements in the network performance. Experimental evaluations carried out using system level simulations show the boost in the capacity when using DFP.