Cyclic Weighted Centroid Algorithm for Transmitter Localization in the Presence of Interference

Abstract

This paper addresses the problem of localizing a non-cooperative transmitter in the presence of a spectrally overlapped interferer in a Cognitive Receiver (CR) network. It has been observed that the performance of non-cooperative Weighted Centroid Localization (WCL) algorithm degrades in the presence of a spectrally overlapped interferer. We propose Cyclic WCL algorithm that uses cyclic autocorrelation (CAC) of received signals at CRs in the network to estimate the location coordinates of the target transmitter. Performance of the proposed algorithm is further improved by eliminating CRs in the vicinity of the interferer from the localization process. In order to identify and eliminate CRs in the vicinity of the interferer, the ratio of the variance and the mean of the square of absolute value of the CAC, referred to as Feature Variation Coefficient (FVC), is used. Theoretical analysis of the Cyclic WCL algorithm is presented in order to compute the root mean square error in the location estimates. We further study impacts of the interferer's power and location, CR density, and fading environment on the performance of Cyclic WCL. The comparison between Cyclic WCL and traditional WCL is also presented.

Connectivity-Based Centroid Localization Using Distributed Dense Reference Nodes

“…This method was first introduced in [12] and its accuracy was evaluated for an idealized scenario, where the RNs are placed on a grid and have the same spherical communication range. Afterwards, several weighted centroid localization schemes were introduced, in which the coordinates of each RN detecting a target node is weighted as a function of the received signal strength [13]- [16]. The CL method outperforms its variants, since it does not require any additional information other than the binary connectivity information between the target node and each of the RNs.…”

Detection of an unknown radio transmitter using an enhanced K-nearest neighbor algorithm based on virtual reference point and RSSD information

“…First, the RSSD-based fingerprint database needs to be established. According to (3) and 14, the Euclidean distance of RSSD can be obtained by:…”

“…Currently, complex and various kinds of radio signals emitted by radio transmitters have been widely used and existed in our daily life. Most communication systems used in wireless applications, such as mobile searching, emergency communications, location-based interference management, and public safety, rely on radio signals and are susceptible to *Correspondence: thdu@hebut.edu.cn School of Artificial Intelligence, Hebei University of Technology, Hongqiao, Tianjin 300130, China interference by illegal signals [2,3]. Therefore, accurate detection of the radio transmitter, as the focus of considerable research efforts, has received significant recent interest, and it is crucial to strengthen management of radio signals and realize the reasonable use of radio spectrum resources.…”

Study of Hybrid Localization Noncooperative Scheme in Wireless Sensor Network

“…In the algorithm presented in [33], WCL is observed with improvement using cyclic autocorrelation (CAC) of received signal at cognitive receivers (CRs) through eliminating CRs in the vicinity of the interference from the localization process. The observed algorithm provided significantly lower error when there is a spectrally overlapped interference and promised to be robust against shadowing and multipath fading in the environment.…”