Design and Analysis of Uplink Transmission Performance Enhancement Methods for Data Collection in Internet-of-Things Networks
Date
2020-04-28
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Abstract
With the increasing demands for the services provided by the Internet-of-Things (IoT) networks, tremendous efforts have been dedicated to enhance the performance of machine-to-machine (M2M) communications. However, due to the limited spectrum resources available for IoT networks, the uplink transmissions that are commonly used for data collection suffer performance degradation when the traffic load increases. To improve the uplink network performance under high traffic load, we propose new enhancement methods for the IoT networks with both single-hop and multi-hop configurations.Specifically, for single-hop networks, this thesis addresses three research objectives. First, successive interference cancellation (SIC) is implemented on top of the pure Aloha (PA) medium access control (MAC) mechanism. The problem is to perform the SIC under an unsynchronized packet transmission framework, and without introducing extra signaling overhead. To this end, a window-based SIC algorithm is presented for the network’s single gateway (GW). Second, in order to evaluate the performance of the SIC-based PA, a throughput model is developed and analyzed to study both the throughput and the packet delivery ratio (PDR) performance metrics. Third, the problem of enabling the SIC-based PA in an IoT network with multiple GWs is solved. The SIC algorithm for PA is redesigned to accommodate single-hop multi-GW networks. A throughput model is also proposed for the newly designed PA-based SIC in multi-GW networks. For the multi-hop IoT networks, the main research objective in this thesis is to allocate proper bandwidth for the nodes in the mesh networks. As a solution, a new distributed bandwidth allocation algorithm is designed. The proposed new design significantly improves the mesh network’s uplink transmission performance at high traffic load. Meanwhile, the new algorithm does not require the configuration of the hysteresis quantum, which makes it more practical than the current state-of-the-art distributed bandwidth allocation algorithms. The performance evaluation results obtained for both the single-hop and multi-hop IoT networks indicate that the proposed enhancement methods can significantly improve the uplink PDR, throughput, and latency for high traffic load scenarios.
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Keywords
Wireless communication, Internet-of-Things, Machine-to-Machine, Successive Interference Cancellation, Scheduling function
Citation
Wang, H. (2020). Design and Analysis of Uplink Transmission Performance Enhancement Methods for Data Collection in Internet-of-Things Networks (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.