A Target-Following Regime using Similarity Measure for Coverage and Capacity Optimization in Self-Organizing Cellular Networks with Hot-Spot

The Self-Organizing Network (SON) has been seen as one of the promising areas to save OPerational EXpenditure (OPEX) and to bring real efficiency to the wireless networks. Though the studies in literature concern with local interaction and distributed structure for SON, study on its coherent pattern has not yet been well-conducted. We consider a target-following regime and propose a novel approach of goal attainment using Similarity Measure (SM) for Coverage & Capacity Optimization (CCO) use-case in SON. The methodology is based on a self-optimization algorithm, which optimizes the multiple objective functions of UE throughput and fairness using performance measure, which is carried out using SM between target and measured KPIs. After certain epochs, the optimum results are used in adjustment and updating modules of goal attainment. To investigate the proposed approach, a simulation in downlink LTE has also been set up. In a scenario including a congested cell with hot-spot, the joint antenna parameters of tilt/azimuth using a 3D beam pattern is considered. The final CDF results show a noticeable migration of hot-spot UEs to higher throughputs, while no one worse off.