AbstractExisting communication technologies are designed with speciÿc use cases in mind, however, ex-tending these use cases usually throw up interesting challenges. For example, extending the use of existing cellular networks to emerging applications such as Internet of Things (IoT) devices throws up the challenge of handling massive number of devices. In this thesis, we are motivated to investigate existing schemes used in LTE and Wi-Fi for supporting massive machine devices and improve on observed performance gaps by designing new ones that outperform the former.
This thesis investigates the existing random access protocol in LTE and proposes three schemes to combat massive device access challenge. The ÿrst is a root index reuse and allocation scheme which uses link budget calculations in extracting a safe distance for preamble reuse under vari-able cell size and also proposes an index allocation algorithm. Secondly, a dynamic subframe optimization scheme that combats the challenge from an optimisation solution perspective. Thirdly, the use of small cells for random access. Simulation and numerical analysis shows performance improvements against existing schemes in terms of throughput, access delay and probability of collision. In some cases, over 20% increase in performance was observed. The proposed schemes provide quicker and more guaranteed opportunities for machine devices to communicate.
Also, in Wi-Fi networks, adaptation of the transmission rates to the dynamic channel condi-tions is a major challenge. Two algorithms were proposed to combat this. The ÿrst makes use of contextual information to determine the network state and respond appropriately whilst the second samples candidate transmission modes and uses the e˛ective throughput to make a deci-sion. The proposed algorithms were compared to several existing rate adaptation algorithms by simulations and under various system and channel conÿgurations. They show signiÿcant per-formance improvements, in terms of throughput, thus, conÿrming their suitability for dynamic channel conditions.
|Date of Award||2017|
|Supervisor||Zuoyin Tang (Supervisor) & Jianhua He (Supervisor)|
- IEEE 802.11
- rate adaptation
Design and analysis of LTE and wi-fi schemes for communications of massive machine devices
Ilori, A. (Author). 2017
Student thesis: Doctoral Thesis › Doctor of Philosophy