[1] Niu , J.,Wang , B.,Rodrigues , J.J., 2015.WicLoc: An Indoor Localization System Based on WiFi Fingerprints and Crowdsourcing”,Proceedings of IEEE International Conference on Communications 3008 -3013
[2] León , O.,HernándezSerrano,J. , and Soriano,M., 2010.,International Journal of Communication Systems 23 633 -652
[3] Zhang , W.,K. , Zhang,W.,Y. , and Gu, 2016.Deep Neural Networks for Wireless Localization in Indoor and Outdoor Environments”, 194 279 -287
[4] Breiman , L., 2001.,Machine Learning 45 5 -32
[5] Yang , S.,Dessai , P.,Verma , M.,Gerla , M.,CalibrationFree Crowdsourced, 2013.,Proccedings of IEEE International Conference on Computer Communications 2481 -2489
[6] Wu , C.,Yang , Z.,Liu , Y.,Xi , W., 2013.Wireless Indoor Localization Without Site Survey”,IEEE Transactions on Parallel and Distributed Systems 24 839 -848
[7] Yasmine , R.,Pei , L., 2016.Indoor Fingerprinting Algorithm for Room Level Accuracy with Dynamic Database”,IEEE 4th International Conference on Ubiquitous Positioning, Indoor Navigation and Location Based Services 113 -121
[8] Ruotsalainen, L., Kuusniemi, H., and Chen, R., “VisualAided
TwoDimensional
Pedestrian Indoor Navigation
with a Smartphone”, Journal of Global Positioning
Systems, Volume 10, No. 1, pp.1118,
Springer
Open, 2011
[9] Khanzada, T.J.S., Memon, S., and Hashmani, A.A., “A
Novel Method to Implement the Matrix Pencil Super
Resolution Algorithm for Indoor Positioning”, Mehran
University Research Journal of Engineering &
Technology, Volume, 30, No. 4, pp. 625634,
Jamshoro,
Pakistan, October, 2011.
[10] Khanzada, T.J.S.,Ali, R.A., and Omar, A.S., “Time
Difference of Arrival Estimation using Super Resolution
Algorithms to Minimize Distance Measurement Error
for Indoor Positioning Systems”, Proceedings of IEEE
MultiTopic
Conference, Karachi, Pakistan, 2324
December, 2008
[11] Khanzada, T.J.S., “Wireless Communication Techniques
for Indoor Positioning and Tracking Applications”, Ph.D.
Dissertation, Faculty Electectrical Engineering &
Information Technology, Magdeburg University,
Magdeburg, Germany, 2010
[12] Oussalah, M., Alakhras, M., and Hussein, M.I.,
“Multivariable Fuzzy Inference System for Fingerprinting
Indoor Localization”, Fuzzy Sets and Systems,
Volume 269, pp.6589,
Elsvier, 2015.
[13] Song, C., Wang, J., and Yuan, G., “Hidden Naive Bayes
Indoor Fingerprinting Localization Based on BestDiscriminating
AP Selection”, ISPRS International
Journal of GeoInformation,
Volume 5, No. 10,
pp. 189, 2016.
[14] Li, N., Chen, J., Yuan, Y., Tian, X., Han, Y., and Xia, M.,
“A WiFi
Indoor Localization Strategy Using Particle
Swarm Optimization Based Artificial Neural Networks”,
International Journal of Distributed Sensor Networks,
Volume 12, No.3, pp. 4583147, SAGE, 2016
[15] Bahl, P., and Padmanabhan, V.N., “RADAR: An InBuilding
RFBased
User Location and Tracking System”,
Proceedings of IEEE 19th Annual Joint Conference on
Computer and Communications Societies, Volume 2,
pp. 775784,
2000
[16] Cooper, M., Biehl, J., Filby, G., and Kratz, S., “LoCo:
Boosting for Indoor Location Classification Combining
WiFi
and BLE”, Personal and Ubiquitous Computing,
Volume 20, No.1, pp. 8396,
Springer, 2016
[17] Wang, C., Wu, F., Shi, Z., and Zhang, D., “Indoor
Positioning Technique by Combining RFID and Particle
Swarm OptimizationBased
Back Propagation Neural
Network”, OptikInternational
Journal for Light and
Electron Optics, Volume 127, No. 17, pp. 68396849,
Elsevier, 2016
[18] Sun, Y., Meng, W., Li, C., Zhao, N., Zhao, K., and Zhang,
N., “Human Localization Using MultiSource
Heterogeneous Data in Indoor Environments”, IEEE
Access, Volume 5, pp. 812822,
2017
[19] Wietrzykowski, J., Nowicki, M., and Skrzypczyñski, P.,
“Adopting the FABMAP
Algorithm for Indoor
Localization with WiFi Fingerprints”, Proceedings of
International Conference Automation, pp. 585594,
Springer, Singapore, March, 2017
[20] Calderoni, L., Ferrara, M., Franco, A., and Maio, D.,
“Indoor Localization in a Hospital Environment Using
Random Forest Classifiers”, Expert Systems with
Applications, Volume 42, No. 1, pp. 125134,
Elsevier,
2015.
[21] Zhang, M., Shen, W., and Zhu, J., “WIFI and Magnetic
Fingerprint Positioning Algorithm Based on KDAKNN”,
Proceedings of IEEE Chinese Control and
Decision Conference, pp. 54095415,
China, May, 2016
[22] Niu, J., Wang, B., Cheng, L., and Rodrigues, J.J., “WicLoc:
An Indoor Localization System Based on WiFi
Fingerprints and Crowdsourcing”, Proceedings of IEEE
International Conference on Communications,
pp. 30083013,
UK, June, 2015
[23] Ding, G., Tan, Z., Zhang, J., and Zhang, L.,
“Fingerprinting Localization Based on Affinity
Propagation Clustering and Artificial Neural Networks”,
Proceeding of IEE Conference on Wireless
Communications and Networking, pp. 23172322,
China,
April, 2013
[24] León, O., Hernández Serrano, J., and Soriano, M.,
“Securing Cognitive Radio Networks”, International
Journal of Communication Systems, Volume 23, No. 5,
pp.633652,
Wiley, 2010
[25] Zhang, W., Liu, K., Zhang, W., Zhang, Y., and Gu, J.,
“Deep Neural Networks for Wireless Localization in
Indoor and Outdoor Environments”, Neurocomputing,
Volume 194, pp. 279287,
Elsevier, 2016.
[26] Breiman, L., “Random Forests”, Machine Learning,
Volume 45, No. 1, pp. 532,
Springer, 2001.
[27] Yang, S., Dessai, P., Verma, M., and Gerla, M., “FreeLoc:
CalibrationFree
Crowdsourced Indoor Localization”,
Proccedings of IEEE International Conference on
Computer Communications, pp. 24812489,
Italy, April,
2013.
[28] Wu, C., Yang, Z., Liu, Y., and Xi, W., “WILL: Wireless
Indoor Localization Without Site Survey”, IEEE
Transactions on Parallel and Distributed Systems,
Volume 24, No. 4, pp. 839848,
2013.
[29] Yasmine, R., and Pei, L., “Indoor Fingerprinting
Algorithm for Room Level Accuracy with Dynamic
Database”, IEEE 4th International Conference on
Ubiquitous Positioning, Indoor Navigation and Location
Based Services, pp. 113121,
2016