Effective Resource Allocation in Home Evolved Node Base Station Networks

PhD Thesis Proposal Defence


Title: "Effective Resource Allocation in Home Evolved Node Base Station 
Networks"

by

Miss Ying WANG


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, especially 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 study jointly optimizing user association, 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 the TD-CSMA protocol to enable deployment in WLANs.

Next, identifying the difficulty of implementing X-2 interfaces among HeNBs, we 
propose fully distributed resource allocation solutions for non-cooperative 
distributed closed-access residential networks. We introduced a self-learning 
HeNB MAC protocol to mitigate interference based on exploitation of 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, 
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 OFDMA scheduling with a combination of interference 
mitigation. We proposed two iterative algorithms guaranteed to converge based 
on inter-HeNB communication.


Date:			Wednesday, 27 April 2016

Time:                  	3:00pm - 5:00pm

Venue:                  Room 5560
                         (lifts 27/28)

Committee Members:	Dr. Brahim Bensaou (Supervisor)
  			Dr. Jogesh Muppala (Chairperson)
 			Prof. Gary Chan
  			Prof. Danny Tsang (ECE)


**** ALL are Welcome ****