{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:32:02Z","timestamp":1761744722296,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,2,13]],"date-time":"2018-02-13T00:00:00Z","timestamp":1518480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>In the Fifth Generation (5G) wireless standard, the Internet of Things (IoT) will interconnect billions of Machine Type Communications (MTC) devices. Fixed and mobile wearable devices and sensors are expected to contribute to the majority of IoT traffic. MTC device mobility has been considered with three speeds, namely zero (fixed) and medium and high speeds of 30 and 100 kmph. Different values for device mobility are used to simulate the impact of device mobility on MTC traffic. This work demonstrates the gain of using distributed antennas on MTC traffic in terms of spectral efficiency and fairness among MTC devices, which affects the number of devices that can be successfully connected. The mutual use of Distributed Base Stations (DBS) with Remote Radio Units (RRU) and the adoption of the millimetre wave band, particularly in the 26 GHz range, have been considered the key enabling technologies for addressing MTC traffic growth. An algorithm has been set to schedule this type of traffic and to show whether MTC devices completed their traffic upload or failed to reach the margin. The gains of the new architecture have been demonstrated in terms of spectral efficiency, data throughput and the fairness index.<\/jats:p>","DOI":"10.3390\/computers7010016","type":"journal-article","created":{"date-parts":[[2018,2,13]],"date-time":"2018-02-13T11:00:41Z","timestamp":1518519641000},"page":"16","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Improved Capacity and Fairness of Massive Machine Type Communications in Millimetre Wave 5G Network"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6133-5048","authenticated-orcid":false,"given":"Naser","family":"Al-Falahy","sequence":"first","affiliation":[{"name":"School of Computing, Science, and Engineering, University of Salford, Salford M5 4WT, UK"},{"name":"College of Engineering, University of Anbar, P.O. Box 55431, Anbar, Iraq"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5848-9107","authenticated-orcid":false,"given":"Omar","family":"Alani","sequence":"additional","affiliation":[{"name":"School of Computing, Science, and Engineering, University of Salford, Salford M5 4WT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,13]]},"reference":[{"key":"ref_1","unstructured":"Cisco (2018, February 12). Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2015\u20132020. Available online: https:\/\/www.cisco.com\/c\/dam\/m\/en_in\/innovation\/enterprise\/assets\/mobile-white-paper-c11-520862.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1109\/MWC.2014.6812298","article-title":"Emerging Technologies and Research Challenges for 5G Wireless Network","volume":"21","author":"Chin","year":"2014","journal-title":"IEEE Wirel. 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