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Details of Grant 

EPSRC Reference: EP/R006377/1
Title: Communications Signal Processing Based Solutions for Massive Machine-to-Machine Networks (M3NETs)
Principal Investigator: Chambers, Professor J
Other Investigators:
Chen, Dr G
Researcher Co-Investigators:
Project Partners:
AWTG Limited BT VCE Mobile & Personal Comm Ltd
Department: Engineering
Organisation: University of Leicester
Scheme: Standard Research
Starts: 26 February 2018 Ends: 25 February 2021 Value (£): 275,538
EPSRC Research Topic Classifications:
Digital Signal Processing RF & Microwave Technology
EPSRC Industrial Sector Classifications:
Communications
Related Grants:
EP/R006385/1 EP/R006466/1
Panel History:
Panel DatePanel NameOutcome
19 Jul 2017 EPSRC ICT Prioritisation Panel July 2017 Announced
Summary on Grant Application Form
Future wireless networks should have the capability of serving a wide range of personal wireless devices and appliances with stringent end-to-end delay requirements. These appliances will be equipped with the capabilities to sense various real time events and be able to self-configure via network connections, thereby paving the way for many emerging applications including e-health, intelligent transportation and smart cities. The most important enabling technologies for these applications is seamless machine-to-machine (M2M) wireless communications, which is the key to sustaining large-scale massive interconnections between things. The number of M2M devices has been growing exponentially, and is expected to reach up to 50 billion by 2020. This trend in the market growth for both M2M devices and M2M connectivity segments will further accelerate in the future. Along with it, by 2020, M2M connections will generate 6.7 percent of total mobile traffic-up from 2.7 percent in 2015. As such, M2M communications is envisioned as one of the five disruptive technology directions for fifth generation (5G) wireless networks and beyond.

Despite the importance of machine-type communications, there are many critical challenges that need to be addressed in terms of network congestion and overload due to presence of massive M2M devices with heterogeneous traffic patterns, unprecedented level of inter and intra interference among M2M and human-to-human (H2M) communications, complex resource management due to irregular traffic patterns and energy constraints. The focus of this project is on tackling these critical challenges, by advancing aspects of communications signal processing, stochastic geometry, convex optimizations and game theory. In particular, we will contribute in terms of characterising heterogeneous traffic patterns associated with massive M2M communications, development of distributed random access channel protocols, proposal of convex and game theoretic resource allocation methods and design of energy harvesting constraint based cross-layer optimisation algorithms and protocols. All the concepts and algorithms developed will be integrated and the radio link layer performance will be assessed using a simulation reference system based on LTE-Advanced standards and its evolution towards 5G. Industrial partners will be engaged throughout the project to ensure industrial relevance of our work.

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Organisation Website: http://www.le.ac.uk