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035 _a(FR-PaOEC)
040 _aFR-PaOEC
_cES-MaONT
100 1 _aKumar, Ambuj
_93356
245 1 0 _aArtificial intelligence for place-time convolved wireless communication networks /
_cAmbuj Kumar
260 _aGeneva :
_bInternational Telecommunication Union,
_c2018.
300 _a9 p.
336 _atexto (visual)
_2isbdcontent
337 _aelectrónico
_2isbdmedia
338 _arecurso en línea
_2rdacarrier
520 3 _aPrevious work have brought to light the dynamic and variable motions of potential network users, and other environmental factors, are the perennial and perpetual challenge to present and future wireless communications. The phenomena coined as place time capacity (PTC), and place time coverage (PTCo), with both collectively known as place time coverage and capacity (PTC.2), are derived as the outcomes of dynamics that can be expressed as the functions of place and time. These phenomena degrade the efficiency of any wireless communication network (WCN) to that lowest point, from where, a network service provider (NSP) may not have any choice but to revamp the network. Artificial intelligence (AI), on the other hand, has been striding profoundly for the past several decades, fanning out its influence in various sectors of scientific and technological developments. However, AI is almost absent in the area of WCN dimensioning and optimization, especially for place-time events. This paper revisits the two place-time functions as WCN phenomena and, with the backdrop of these aspects, shall investigate the inevitable need for AI in WCNs, as well as demonstrating how AI can be part of present and future wireless communications.
650 0 _aTecnologías habilitadoras digitales
_918
653 4 _aScience and Technology
773 0 _04843
_tITU Journal: ICT Discoveries
_gVol. 2018, no. 1, p. 85-93
_q2018:1<85
_x2616-8375
856 4 0 _aitu-ilibrary.org
_uhttps://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I1-2018-10-PDF-E.pdf
_yAcceso al documento
_x0
_qpdf
942 _cART
_2udc