Improving Performance for CSMA/CA Based Wireless Networks

Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) based wireless networks are becoming increasingly ubiquitous. With the aim of supporting rich multimedia applications such as high-definition television (HDTV, 20Mbps) and DVD (9.8Mbps), one of the technology trends is towards increasingly higher bandwidth. Some recent IEEE 802.11n proposals seek to provide PHY rates of up to 600 Mbps. In addition to increasing bandwidth, there is also strong interest in extending the coverage of CSMA/CA based wireless networks. One solution is to relay traffic via multiple intermediate stations if the sender and the receiver are far apart. The so called “mesh” networks based on this relay-based approach, if properly designed, may feature both “high speed” and “large coverage” at the same time. This thesis focusses on MAC layer performance enhancements in CSMA/CA based networks in this context. Firstly, we observe that higher PHY rates do not necessarily translate into corresponding increases in MAC layer throughput due to the overhead of the CSMA/CA based MAC/PHY layers. To mitigate the overhead, we propose a novel MAC scheme whereby transported information is partially acknowledged and retransmitted. Theoretical analysis and extensive simulations show that the proposed MAC approach can achieve high efficiency (low MAC overhead) for a wide range of channel variations and realistic traffic types. Secondly, we investigate the close interaction between the MAC layer and the buffer above it to improve performance for real world traffic such as TCP. Surprisingly, the issue of buffer sizing in 802.11 wireless networks has received little attention in the literature yet it poses fundamentally new challenges compared to buffer sizing in wired networks. We propose a new adaptive buffer sizing approach for 802.11e WLANs that maintains a high level of link utilisation, while minimising queueing delay. Thirdly, we highlight that gross unfairness can exist between competing flows in multihop mesh networks even if we assume that orthogonal channels are used in neighbouring hops. That is, even without inter-channel interference and hidden terminals, multi-hop mesh networks which aim to offer a both “high speed” and “large coverage” are not achieved. We propose the use of 802.11e’s TXOP mechanism to restore/enfore fairness. The proposed approach is implementable using off-the-shelf devices and fully decentralised (requires no message passing)

Prioritised Random Access Channel Protocols for Delay Critical M2M Communication over Cellular Networks

With the ever-increasing technological evolution, the current and future generation communication systems are geared towards accommodating Machine to Machine (M2M) communication as a necessary prerequisite for Internet of Things (IoT). Machine Type Communication (MTC) can sustain many promising applications through connecting a huge number of devices into one network. As current studies indicate, the number of devices is escalating at a high rate. Consequently, the network becomes congested because of its lower capacity, when the massive number of devices attempts simultaneous connection through the Random Access Channel (RACH). This results in RACH resource shortage, which can lead to high collision probability and massive access delay. Hence, it is critical to upgrade conventional Random Access (RA) techniques to support a massive number of Machine Type Communication (MTC) devices including Delay-Critical (DC) MTC. This thesis approaches to tackle this problem by modeling and optimising the access throughput and access delay performance of massive random access of M2M communications in Long-Term Evolution (LTE) networks. This thesis investigates the performance of different random access schemes in different scenarios. The study begins with the design and inspection of a group based 2-step Slotted-Aloha RACH (SA-RACH) scheme considering the coexistence of Human-to-Human (H2H) and M2M communication, the latter of which is categorised as: Delay-Critical user equipments (DC-UEs) and Non-Delay-Critical user equipments (NDC-UEs). Next, a novel RACH scheme termed the Priority-based Dynamic RACH (PD-RACH) model is proposed which utilises a coded preamble based collision probability model. Finally, being a key enabler of IoT, Machine Learning, i.e. a Q-learning based approach has been adopted, and a learning assisted Prioritised RACH scheme has been developed and investigated to prioritise a specific user group. In this work, the performance analysis of these novel RACH schemes show promising results compared to that of conventional RACH

A Remote Capacity Utilization Estimator for WLANs

In WLANs, the capacity of a node is not fixed and can vary dramatically due to the shared nature of the medium under the IEEE 802.11 MAC mechanism. There are two main methods of capacity estimation in WLANs: Active methods based upon probing packets that consume the bandwidth of the channel and do not scale well. Passive methods based upon analyzing the transmitted packets that avoid the overhead of transmitting probe packets and perform with greater accuracy. Furthermore, passive methods can be implemented locally or remotely. Local passive methods require an additional dissemination mechanism in order to communicate the capacity information to other network nodes which adds complexity and can be unreliable under adverse network conditions. On the other hand, remote passive methods do not require a dissemination mechanism and so can be simpler to implement and also do not suffer from communication reliability issues. Many applications (e.g. ANDSF etc) can benefit from utilizing this capacity information. Therefore, in this thesis we propose a new remote passive Capacity Utilization estimator performed by neighbour nodes. However, there will be an error associated with the measurements owing to the differences in the wireless medium as observed by the different nodes’ location. The main undertaking of this thesis is to address this issue. An error model is developed to analyse the main sources of error and to determine their impact on the accuracy of the estimator. Arising from this model, a number of modifications are implemented to improve the accuracy of the estimator. The network simulator ns2 is used to investigate the performance of the estimator and the results from a range of different test scenarios indicate its feasibility and accuracy as a passive remote method. Finally, the estimator is deployed in a node saturation detection scheme where it is shown to outperform two other similar schemes based upon queue observation and probing with ping packets