Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Indoor localization based on cellular telephony RSSI fingerprints containing very large numbers of carriers | Oussar et al. EURASIP Journal on Wireless Communications and Networking 2011 2011 81 EURASIP Journal on . http content 2011 1 8i Wireless Communications and Networking a SpringerOpen Journal RESEARCH Open Access Indoor localization based on cellular telephony RSSI fingerprints containing very large numbers of carriers r 1 1 1 Yacine Oussar Iness Ahriz Bruce Denby and Gérard Dreyfus Abstract A new approach to indoor localization is presented based upon the use of Received Signal Strength RSS fingerprints containing data from very large numbers of cellular base stations-up to the entire GSM band of over 500 channels. Machine learning techniques are employed to extract good quality location information from these high-dimensionality input vectors. Experimental results in a domestic and an office setting are presented in which data were accumulated over a 1-month period in order to assure time robustness. Room-level classification efficiencies approaching 100 were obtained using Support Vector Machines in one-versus-one and one-versus-all configurations. Promising results using semi-supervised learning techniques in which only a fraction of the training data is required to have a room label are also presented. While indoor RSS localization using WiFi as well as some rather mediocre results with low-carrier count GSM fingerprints have been discussed elsewhere this is to our knowledge the first study to demonstrate that good quality indoor localization information can be obtained in diverse settings by applying a machine learning strategy to RSS vectors that contain the entire GSM band. 1. Introduction The accurate localization of persons or objects both indoors and out of doors is an interesting scientific challenge with numerous practical applications 1 . With the advent of inexpensive implantable GPS receivers it is tempting to suppose that the localization problem is today solved. Such receivers however require a minimum number of .
