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Unfortunately, the WiFi received signal strength (RSS) is susceptible by multipath, signal attenuation, and environmental changes, which is the major challenge for accurate indoor localization. To overcome these limitations, we propose the cluster k-nearest neighbor (KNN) algorithm with 5\u2009G WiFi signal to reduce the environmental interference and improve the localization performance without additional equipment. In this paper, we propose three approaches to improve the performance of localization algorithm. For one thing, we reduce the computation effort based on the coarse localization algorithm. For another, according to the detailed analysis of the 2.4\u2009G and 5\u2009G signal fluctuation, we expand the real-time measurement RSS before matching the fingerprint map. More importantly, we select the optimal nearest neighbor points based on the proposed cluster KNN algorithm. We have implemented the proposed algorithm and evaluated the performance with existent popular algorithms. Experimental results demonstrate that the proposed algorithm can effectively improve localization accuracy and exhibit superior performance in terms of localization stabilization and computation effort. <\/jats:p>","DOI":"10.1155\/2014\/247525","type":"journal-article","created":{"date-parts":[[2014,12,18]],"date-time":"2014-12-18T15:59:51Z","timestamp":1418918391000},"page":"247525","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":32,"title":["5\u2009G WiFi Signal-Based Indoor Localization System Using Cluster <i>k<\/i>-Nearest Neighbor Algorithm"],"prefix":"10.1177","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8252-5131","authenticated-orcid":false,"given":"Feng","family":"Yu","sequence":"first","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghua","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Qin","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Auburn University, Auburn, AL 36849, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinrong","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2014,12,16]]},"reference":[{"key":"B1-2014-247525","first-page":"387","volume-title":"Global Positioning System. 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