Machine to Machine Communications in Cellular Networks

Machine to Machine Communications in Cellular
Networks: Protocols and Algorithms
Guowang Miao,
Starting Time:
Q1/2 2013
With Internet of Things (IoT), smart things become active participants in business and social
processes, as shown in the above pic. IoT is included by the US National Intelligence Council
(NIC) in the list of six “Disruptive Civil Technologies” with potential impacts on US [1]. NIC
considers that “by 2025 Internet nodes may reside in everyday things — food packages,
furniture, paper documents, and more.” IoT developments show that we will have 16 billion
connected devices by the year 2020 [3], which will average out to six devices per person on
earth and to many more per person in digital societies. In wide-area applications, low-cost
and massive machine to machine (M2M) communications provided by cellular networks will
be one main driver for the success of future IoT development.
A first direct consequence of the proliferation of IoT is that large numbers of devices will
produce huge quantities of sporadic data [2] and significantly higher capacity of cellular
networks will be needed – not in terms of megabits transported, but the number of machines
sustained. In this project, we will investigate the feasibility of using existing protocols and
algorithms of LTE systems in supporting M2M communications.
Thesis Work
The goal of the thesis is to investigate how M2M communications can be integrated with
traditional cellular structures from both algorithm and protocol perspectives. The final
definition will be made together with the applicant. The following is what we currently expect
in part of the work:
Literature survey of existing M2M communications algorithms and protocols and analyze
the issues in integrating M2M in cellular networks;
Analyze the signaling overhead in existing LTE systems for data communications.
Implement a simulation platform and observe the performance.
Design or choose a MAC scheme and implement it. Analyze the impact of different
parameters on the performance.
Evaluate the impact of signaling overhead, machine proximity, and traffic load on the
network performance.
You should
be a bright Master of Science student in electrical engineering, applied physics or
similar with excellent grades,
have taken courses and excel in wireless communications, wireless networks,
master a certain programing language (Matlab or C/C++ preferred),
have a keen interest in telecom technologies, programming, and research,
have strong analytical skills,
speak and write outstanding English, and
be self-motivated, self-driven and communicative.
Scope: 30 points (20 weeks), 1 person
Target starting date: within Q1/2 2013, the exact dates will be set together with the selected
Location: Kista, Stockholm, Sweden
[1] ITU Internet Reports, The Internet of Things, November 2005.
[2] Internet 3.0: The Internet of Things. Analyses Mason Limited 2010.
[3] Vision and Challenges for Realising the Internet of Things, European Union 2010, ISBN