THESIS
2016
xi, 124 pages : illustrations ; 30 cm
Abstract
Thanks to their ability to enhance transmission quality by offloading LTE Evolved Node Base
Station (eNB) traffic, Home eNB (HeNB) deployment has progressed dramatically in recent years.
Despite this popularity, the deployment of HeNBs has also introduced a new set of resource inefficiency
problems, caused mainly by inter-cell interference and indoor traffic load fluctuation. A
large body of previous work has been devoted to improving the utilization of network resources in
HeNBs, including, frequency planning, time division, power control, and space division. Nevertheless,
many problems not addressed adequately by these studies remain open, in particular those
related to communication overhead, computational complexity, and service quality.
In the absence of standardized re...[
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Thanks to their ability to enhance transmission quality by offloading LTE Evolved Node Base
Station (eNB) traffic, Home eNB (HeNB) deployment has progressed dramatically in recent years.
Despite this popularity, the deployment of HeNBs has also introduced a new set of resource inefficiency
problems, caused mainly by inter-cell interference and indoor traffic load fluctuation. A
large body of previous work has been devoted to improving the utilization of network resources in
HeNBs, including, frequency planning, time division, power control, and space division. Nevertheless,
many problems not addressed adequately by these studies remain open, in particular those
related to communication overhead, computational complexity, and service quality.
In the absence of standardized resource allocation mechanisms for LTE HeNBs, in this work
we focus on designing effective solutions to the resource allocation problem in HeNB networks;
and address three operational environments: i) open-access enterprise networks, ii) closed-access
residential networks, and iii) open-access residential networks.
First, we focus on improving the resource utilization in centrally-controlled open-access enterprise
networks such as enterprise HeNB networks and Wireless Local Area Networks (WLAN). To
the best of our knowledge, our work is the first to jointly optimize user association, antenna beam
selection, link scheduling, and power adaptation in such networks. We proposed a unified conflict-free scheduling algorithm, that can be directly implemented in HeNB networks, and also designed a
coordination protocol, the so-called TD-CSMA protocol to enable deployment over uncoordinated
WLAN MAC protocol.
Next, identifying the difficulty of implementing X-2 interfaces among HeNBs, we proposed
fully distributed resource allocation solutions for non-cooperative distributed closed-access residential
networks. We introduced a self-learning HeNB MAC protocol to mitigate interference by
relying on historical user feedback. The learning process is modelled as a cluster-structural regret-based
learning game, where the users within one HeNB form a cluster to share information.
Finally, we examined the problem of the energy cost of running a massive number of always-on
HeNBs worldwide and focused on designing an energy efficient, Quality of Servic (QoS) constrained
MAC protocol for cooperative distributed open-access residential HeNB networks. Since
most previous work has failed to properly consider interference mitigation when designing such
protocols, we manipulate user association and Orthogonal Frequency Division Multiple Access
(OFDMA) scheduling with a combination of interference mitigation measures. Within a potential
game framework, we proposed iterative algorithms guaranteed to converge based on inter-HeNB
communication.
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