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However, users are more likely to enter from some directions than others (eg, along streets), and beamforming directions (eg, those affected by blockage) may never be used. We exploit the unequal distribution of the entrance direction to speed up the IA procedure, exploring more often the directions wherein the probability of finding new users is higher. Two solutions are proposed: a memory\u2010less random illumination (MLRI) algorithm and a statistical and memory\u2010based illumination (SMBI) algorithm. While in MLRI, the direction to be explored is randomly generated according to an optimized distribution, and independent of previously explored directions, in SMBI a precise exploration sequence is designed, thus we take into account previously explored directions. In the analysis, we include the movement of the user within the cell during the IA process, described by a Markov chain whose states correspond to the beamforming directions associated to the user position at a given IA exploration time. We assess the performance of the proposed methods in terms of average discovery time.<\/jats:p>","DOI":"10.1002\/ett.3683","type":"journal-article","created":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T03:38:44Z","timestamp":1562643524000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Statistical approaches for initial access in mmWave 5G systems"],"prefix":"10.1002","volume":"32","author":[{"given":"Ra\u00fal","family":"Parada","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, Multimedia and Telecommunications Universitat Oberta de Catalunya (UOC)  Barcelona Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hossein","family":"Soleimani","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Faculty of Ghazi Tabatabai, Urmia Branch, Technical and Vocational University (TVU)  Urmia Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Federico","family":"Moretto","sequence":"additional","affiliation":[{"name":"Department of Information Engineering University of Padova  Padova Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3253-6793","authenticated-orcid":false,"given":"Stefano","family":"Tomasin","sequence":"additional","affiliation":[{"name":"Department of Information Engineering University of Padova  Padova Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michele","family":"Zorzi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering University of Padova  Padova Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,7,8]]},"reference":[{"volume-title":"Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2017\u20132022","year":"2017","key":"e_1_2_7_2_1"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2014.2299397"},{"key":"e_1_2_7_4_1","unstructured":"Third Generation Partnership Project (3GPP) Technical Specification Group Radio Access Network.NR \u2010 Multi\u2010connectivity \u2010 overall description (Stage 2) TS37.340.2018."},{"key":"e_1_2_7_5_1","doi-asserted-by":"crossref","unstructured":"DesaiV KrzymienL SartoriP XiaoW SoongA AlkhateebA.Initial beamforming for mmWave communications. 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