Research On Positioning Algorithms In Heterogeneous Wireless Networks

Along with the global process of telecommunication industry and the development of computer network technology, heterogeneous wireless network will be the inevitable trend of wireless communication in the future. A typical scenario of heterogeneous network is the interconnection between 3G network and WLAN. Many functions are achieved by positioning technology in isomorphic networks. In heterogeneous networks positioning technology also plays a decisive role. So study of positioning technology in heterogeneous networks is of great theoretical and practical significance.This paper combines with practical, aiming at studying positioning technology in HWN of WLAN and WCDMA network. Firstly, we discuss the necessity and possibility of improving the positioning precision by integrating respective positioning results of WLAN and WCDMA network. Based on HWN with single WCDMA base station, a localization algorithm is presented. This algorithm utilizes two characteristics of these two networks: First, if there exists LOS path between base station and unknown node, the distance measurement results by TOA algorithm of base station will present a high accuracy. Second, it is very convenient to gain RSSI between beacon nodes and unknown node in WLAN. In this algorithm, we use distance information of base station and position information of beacon nodes to control "gene" during genetic process. RSSI is selected to be parameter in fitness selection function. The analysis and simulation results validate that this strategy can increase the convergence rate and positioning precision. It also shows a good adaptability and robustness to positioning error in our experiments. But this algorithm has a short coming that it is easily converge to local optimum. In order to make up for the previous algorithm we present an algorithm called Centroid location based on modified particle filter in the end of this paper. This algorithm can estimate the posterior probability density of node distribution through WCDMA base station and WLAN beacon nodes information. Then we can gain the area information where the unknown node most likely to appear. According to this area, we can get the location coordinates of unknown node. The simulation results prove that the algorithm is feasible and achieves good positioning result.