A Novel technique for Reference Node Placement in Wireless Indoor Positioning Systems based on Fingerprint Technique

Abstract

Accuracy of location determination is one of the keys to success for any indoor positioning system. This performance metric is influenced by how reference nodes (RNs) are installed. However, most of existing research studies ignored the problem of optimal reference node placement and efficient system design for indoor positioning systems. In this paper, we propose a novel technique using heuristic approach that can design suitable location to install the reference nodes and improve the location determination performance for a single-floor area and the multi-floor building. A mathematical formulation of reference node placement is developed as a Binary Integer Linear Programming (BILP) problem. The proposed formulation aims to minimize the number of reference nodes and derive their suitable locations for the indoor positioning systems. We developed an efficient solution technique based on Simulated Annealing algorithm (SA), called Maximizing Summation of the Maximum RSS for Multi-floor building (MSMR-M). The results from performance study show that by using the proposed RN placement technique, the indoor positioning systems can gain up to five meters of accuracy at 90% precision for single-floor building. Moreover, in the case of the multi-floor building, the proposed technique can improve the error distances up to 20% which is better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters where the grid spacing of fingerprint is 2m2m.