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While crowdsourcing is an attractive approach to collect large-scale wireless measurements, understanding the quality and variance of the resulting data is difficult. Our work analyzes the quality of crowdsourced cellular signal measurements in the context of basestation localization, using large international public datasets (419M signal measurements and ∼1M cells) and corresponding ground truth values. Performing localization using raw received signal strength (RSS) data produces poor resultsdoi:10.1145/3038912.3052563 dblp:conf/www/LiNZZYZZ17 fatcat:p473oxsfr5he7pfmre3psxt6aa