The increasing demand for cellular network capacity can be mitigated through the installation of nomadic eNodeB, which serve a temporal increase of traffic volume in specific area. When nomadic cells are deployed, the transmission power of neighbour base stations needs to be optimised to limit the inter-cell interferences. The authors analyse the problem of neighbourhood selection for the optimisation, to define what part of the networks needs to be reconfigured when new base station is added. They evaluate the iterative approach, with increasing range of neighbouring cells being reconfigured and propose a novel, sampling-based local TX power reconfiguration method, which is evaluated by a numerical model in both regular (honeycomb) topology and in realistic topology reflecting locations of cells in a city. The analysis confirms that the proposed algorithm allows to select small subset of neighbouring cells to be reconfigured (in majority of the cases <10 cells), and achieve similar efficacy as global optimisation, with total network throughput different by <1% comparing to the global optimisation.