Search results for "nearest neighbor"
showing 3 items of 63 documents
Radio frequency fingerprinting for outdoor user equipment localization
2017
The recent advancements in cellular mobile technology and smart phone usage have opened opportunities for researchers and commercial companies to develop ubiquitous low cost localization systems. Radio frequency (RF) fingerprinting is a popular positioning technique which uses radio signal strength (RSS) values from already existing infrastructures to provide satisfactory user positioning accuracy in indoor and densely built outdoor urban areas where Global Navigation Satellite System (GNSS) signal is poor and hard to reach. However a major requirement for the RF fingerprinting to maintain good localization accuracy is the collection and updating of large training database. The Minimization…
Smart prototype selection for machine learning based on ignorance zones analysis
2018
The size of databases has been considerably growing over recent decades and Machine Learning algorithms are not ready to process such large volume of information. Being one of the most useful algorithms in Data Mining the Nearest neighbor classifier suffers from high storage requirements and slow response when working with large data sets. Prototype Selection methods help to alleviate this problem by choosing a subset of data with a smaller size. In this thesis, the overview of existing instance selection methods is provided together with the introduction of a new approach. The majority of current methods select a subset experimentally by checking whether certain point affects classificatio…
Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Outdoor Signals
2015
In this paper we evaluate user-equipment (UE) positioning performance of three cluster-based RF fingerprinting methods using LTE and WLAN signals. Real-life LTE and WLAN data were collected for the evaluation purpose using consumer cellular-mobile handset utilizing ‘Nemo Handy’ drive test software tool. Test results of cluster-based methods were compared to the conventional grid-based RF fingerprinting. The cluster-based methods do not require grid-cell layout and training signature formation as compared to the gridbased method. They utilize LTE cell-ID searching technique to reduce the search space for clustering operation. Thus UE position estimation is done in short time with less comput…