 
								Experimental Performance Analysis and Improvement Techniques for RSSI Based Indoor Localization: RF Fingerprinting and RF Multilateration
								
									
										
											
											
												Md. Al Shayokh,
											
										
											
											
												Ugur Alkasi
											
										
									
								 
								
									
										Issue:
										Volume 2, Issue 2, September 2014
									
									
										Pages:
										15-21
									
								 
								
									Received:
										12 November 2014
									
									Accepted:
										16 November 2014
									
									Published:
										27 November 2014
									
								 
								
								
								
									
									
										Abstract: In this paper, Performance improvement techniques for two popular RSSI based indoor localization methods have been studied experimentally by using Wi-Fi modems. The improvement of RF Fingerprinting and RSSI Multi-lateration methods have been suggested from different aspects for both line-of-sight (LoS) and non-line-of-sight (nLoS) medium in an indoor environment. Various testing scenarios have been examined for comparison of the two methods, as the performance level in RF Fingerprinting is mainly depend on the number of modems, as well as the density of training data and, the multilateration method is mainly depend on correctly modeling of the path loss exponent. Optimizing and defining a unique path loss exponent for each of the wireless transmitter modems, testing in a LoS and a nLoS medium, changing the number of transmitters, etc, have been tried and performance plots have been shown for comparison purposes.
										Abstract: In this paper, Performance improvement techniques for two popular RSSI based indoor localization methods have been studied experimentally by using Wi-Fi modems. The improvement of RF Fingerprinting and RSSI Multi-lateration methods have been suggested from different aspects for both line-of-sight (LoS) and non-line-of-sight (nLoS) medium in an indo...
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