Trade-off between node selection and space diversity for accurate uncooperative localization

Abstract We consider Received Signal Strength (RSS) based localization and trade-off between space diversity and node selection approaches in terms of localization accuracy. In LOS/NLOS (Line Of Sight/Non Line Of Sight) mixed environment and uncooperative scenario, we show that when shadowing variance increases, we move from a first region where diversity is preferable to selectivity (use of all RSS leads to better accuracy) to a second region where selective aspect leads to better performance (use of higher RSS). Thus, the idea of computing an optimum threshold σ o p t i m a l 2 on the shadowing variance (respectively γ optimal on the RSS values) which represent the edge between these two regions. This threshold, γ optimal , will indeed help to trade-off between using all nodes or only a subset of them for more accurate localization. The closed form expression for the failure rate, defined as the event when all RSS measures are below a threshold value, ( RSS γ optimal ) is first derived. Then, we proposed a scheme for optimizing the choice between node selection and diversity approaches.