Efficient and Reliable Design for Extremely Dense Wireless Networks

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence

Title: "Efficient and Reliable Design for Extremely Dense Wireless Networks"

By

Mr. Wei WANG


Abstract

The intense demands for higher data rates and ubiquitous network coverage have 
raised the stakes on developing new network topology and architecture to meet 
these ever-increasing demands in a cost-effective manner. The telecommunication 
industry and international standardization bodies have placed considerable 
attention to the deployment of extremely dense networks, referred to as 
DenseNets, which creates a bundle of opportunities for high spatial reuse and 
energy efficiency by reducing the distance between Access Points (APs) and 
clients. Industrial practices of DenseNets include small-scale femtocells in 
LTE/LTE-A based cellular systems and WiFi hotspots in public places in IEEE 
802.11 based High Efficiency WLAN (HEW). Both empirical experiences and 
theoretical analyses suggest that DenseNets will encompass significant 
technical challenges related to reliable and efficient access and management. 
On the one hand, DenseNets contain a significant number of densely-deployed APs 
with highly overlapped regions, making network maintenance a complicated and 
challenging task. On the other hand, there are normally a crowd of clients in 
DenseNets, and thus efficient access control is expected to meet the high 
per-user-throughput demands with a limited amount of bandwidth.

We have two proposals for DenseNets, where each aims to address one challenge 
as mentioned above. First, we propose a automatic fault management framework 
for dense femtocell networks. Under this framework, we propose three system 
designs for outage detection, fault diagnosis, and self-healing functions. As 
the first step of our automatic management framework, the proposed outage 
detection design exploits signal correlations among multiple femtocells to 
improve detection accuracy for small-size densely-deployed femtocell networks. 
The outage detection system triggers fault diagnostic system. In our diagnostic 
system design, we develop a transfer learning based approach to overcome the 
data scarcity issue in small-size femtocells. After identifying the specific 
fault, outage is compensated by a self-healing scheme. We study the 
interference outage case, and propose a local cooperative grouping architecture 
to iteratively recover the network outage. Second, we propose an efficient 
access framework for WiFi networks with large audience environments. We analyze 
the poor performance of WiFi for large audience environments, and propose a 
PHY/MAC design to improve efficiency in public WLANs. The proposed design 
aggregates multi-user's transmissions into one transmission so as to reduce 
contention overhead. The above studies demonstrate that with appropriate system 
designs, reliable and efficient DenseNets can be achieved to meet high data 
rate and ubiquitous connection demands.


Date:			Friday, 9 January 2015

Time:			9:00am - 11:00am

Venue:			Room 3494
 			Lifts 25/26

Chairman:		Prof. King Lau Chow (LIFS)

Committee Members:	Prof. Qian Zhang (Supervisor)
 			Prof. Kai Chen
 			Prof. Lei Chen
 			Prof. Vincent Lau (ECE)
 			Prof. Dan Wan (Computing, PolyU)


**** ALL are Welcome ****