BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Australia/Canberra BEGIN:DAYLIGHT DTSTART:20161002T030000 TZOFFSETFROM:+1000 TZOFFSETTO:+1100 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=10 TZNAME:AEDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20160403T020000 TZOFFSETFROM:+1100 TZOFFSETTO:+1000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=4 TZNAME:AEST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20160821T234603Z UID:F2E15495-E5B6-11E7-833E-0050568D7F66 DTSTART;TZID=Australia/Canberra:20160819T110000 DTEND;TZID=Australia/Canberra:20160819T120000 DESCRIPTION:By 2020 there will be 20-50 billion devices connected to cellul ar networks around the world\, and less than a third of those will be the cell phones and tablets that dominate cellular networks today. This massiv e growth will be driven by the Internet of Things (IoT)\, the name given t o the ubiquitous connectivity of everything everywhere. In domains from he althcare\, industry\, agriculture\, manufacturing\, energy and entertainme nt\, embedded devices will be seamlessly monitoring\, calculating and comm unicating wirelessly. To thrive in this new world of IoT\, cellular networ ks must evolve to handle the new ways in which these devices will connect and communicate. Machine-to-Machine (M2M) communications aims to provide t he most efficient communication infrastructure for enabling IoT. Providing this infrastructure will require a dramatic shift from the current protoc ols designed for a much smaller number of very different users\, which are mostly for human-to-human (H2H) applications.\n\nDespite huge efforts of 3GPP towards making M2M communications a reality\, there are still open ch allenges where efficient solutions must be proposed. Among others\, the ra ndom access channel of LTE has been identified as a key area where improve ments for M2M traffic are needed. In current cellular standards\, the user s wishing to communicate with the base station first request an access thr ough the random access (RA) procedure. That is each user randomly chooses a preamble and sends it via the random access channel. Once the base stati on has detected the preambles\, orthogonal radio resources are allocated t o the users\, to then transmit in separate channels. This is however ineff icient for M2M communications with a large number of devices\, as many dev ices may select the same preamble in the random access procedure\, thus th eir data transmission will collide making the base station unable to decod e them. Even if the devices choose separate preambles\, there will most li kely not be sufficient radio resources to orthogonally allocate to all use rs. A major challenge in current cellular systems is then to ensure that a large number of devices involved in M2M applications can be supported.\n\ nIn this regard\, we overview the current random access procedure proposed for LTE-Advanced and discuss the challenges and issues related to it. We then represent the basic concept of an alternative uplink non-orthogonal m ultiple access (NOMA) technique. The issues and challenges of random NOMA are then explored. Channel coding techniques are also discussed as an esse ntial part of NOMA.\n\nCo-sponsored by: Salman Durrani\n\nSpeaker(s): Mahy ar Shirvanimoghaddam\, \n\nCanberra\, New South Wales\, Australia LOCATION:Canberra\, New South Wales\, Australia ORGANIZER:salman.durrani@anu.edu.au SEQUENCE:0 SUMMARY:[Legacy Report] Massive Multiple Access Techniques for Machine-to-M achine Communications URL;VALUE=URI:https://events.vtools.ieee.org/m/136058 X-ALT-DESC:Description: <br /><p>By 2020 there will be 20-50 billion device s connected to cellular networks around the world\, and less than a third of those will be the cell phones and tablets that dominate cellular networ ks today. This massive growth will be driven by the <em>Internet of Things </em>(IoT)\, the name given to the ubiquitous connectivity of everything everywhere. In domains from healthcare\, industry\, agriculture\, manufact uring\, energy and entertainment\, embedded devices will be seamlessly mon itoring\, calculating and communicating wirelessly. To thrive in this new world of IoT\, cellular networks must evolve to handle the new ways in whi ch these devices will connect and communicate. <em>Machine-to-Machine </em >(M2M) communications aims to provide the most efficient communication inf rastructure for enabling IoT. Providing this infrastructure will require a dramatic shift from the current protocols designed for a much smaller num ber of very different users\, which are mostly for human-to-human (H2H) ap plications.</p>\n<p>Despite huge efforts of 3GPP towards making M2M commun ications a reality\, there are still open challenges where efficient solut ions must be proposed. Among others\, the random access channel of LTE has been identified as a key area where improvements for M2M traffic are need ed. In current cellular standards\, the users wishing to communicate with the base station first request an access through the random access (RA) pr ocedure. That is each user randomly chooses a preamble and sends it via th e random access channel. Once the base station has detected the preambles\ , orthogonal radio resources are allocated to the users\, to then transmit in separate channels. This is however inefficient for M2M communications with a large number of devices\, as many devices may select the same pream ble in the random access procedure\, thus their data transmission will col lide making the base station unable to decode them. Even if the devices ch oose separate preambles\, there will most likely not be sufficient radio r esources to orthogonally allocate to all users. A major challenge in curre nt cellular systems is then to ensure that a large number of devices invol ved in M2M applications can be supported.</p>\n<p>In this regard\, we over view the current random access procedure proposed for LTE-Advanced and dis cuss the challenges and issues related to it. We then represent the basic concept of an alternative uplink non-orthogonal multiple access (NOMA) tec hnique. The issues and challenges of random NOMA are then explored. Channe l coding techniques are also discussed as an essential part of NOMA.</p> END:VEVENT END:VCALENDAR