1 research outputs found
Opportunistic traffic Offloadings Mechanisms for Mobile/4G Networks
In the last few years, it has been observed a drastic surge of data traffic demand from
mobile personal devices (smartphones and tablets) over cellular networks [1]. Even
though a significant improvement in cellular bandwidth provisioning is expected with
LTE-Advanced systems, the overall situation is not expected to change significantly. In
fact, the diffusion of M2M and IoT devices is expected to increase at an exponential pace
(the share of M2M devices is predicted to increase 5x by 2018 [1]) while the capacity of
the cellular network is expected to increase linearly [1]. In order to meet such a high
demand and to increase the capacity of the channel, multiple offloading techniques are
currently under investigation, from modifications inside the cellular network architecture,
to integration of multiple wireless broadband infrastructures, to exploiting direct
communications between mobile devices. All these approaches can be diveded in two
main classes:
- To develop more sophisticated physical layer technologies (e.g. massive MIMO,
higher-order modulation schemes, cooperative multi-period transmission/reception)
- To offload part of the traffic from the cellular to another complementary network.
From this perspective the thesis contributes on both areas. On the one hand we discuss
our investigations about the performance of the LTE channel capacity through the development
of a unified modelling framework of the MAC-level downlink throughput of
a sigle LTE cell, which caters for wideband CQI feedback schemes, AMC and HARQ
protocols as defined in the LTE standard. Furthemore we also propose a solution, based
on reinforcement learning, to improve the LTE Adaptive Modulation and coding Scheme
(MCS).
On the other hand we have proposed and validated offloading mechanisms which are
minimally invasive for users' mobile devices, as they use only minimally their resources.
Furthemore, as opposed to most of the literature, we consider the case where requests
for content are non-synchronised, i.e. users request content at random points in time