Document Type
Dissertation
Degree
Doctor of Philosophy (PhD)
Major/Program
Electrical Engineering
First Advisor's Name
Arif I. Sarwat
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Ismail Guvenc
Second Advisor's Committee Title
Co-Committee Chair
Third Advisor's Name
Kemal Akkaya
Third Advisor's Committee Title
Committee Member
Fourth Advisor's Name
Leonardo Bobadilla
Fourth Advisor's Committee Title
Committee Member
Fifth Advisor's Name
Mehdi Bennis
Fifth Advisor's Committee Title
Committee Member
Keywords
5G, Spectrum sharing, Latency, Data security, Smartgrid, IoT, Machine learning, LTE, WiFi, ZigBee
Date of Defense
10-22-2018
Abstract
The surge of mobile devices, such as smartphones, and tables, demands additional capacity. On the other hand, Internet-of-Things (IoT) and smart grid, which connects numerous sensors, devices, and machines require ubiquitous connectivity and data security. Additionally, some use cases, such as automated manufacturing process, automated transportation, and smart grid, require latency as low as 1 ms, and reliability as high as 99.99\%. To enhance throughput and support massive connectivity, sharing of the unlicensed spectrum (3.5 GHz, 5GHz, and mmWave) is a potential solution. On the other hand, to address the latency, drastic changes in the network architecture is required. The fifth generation (5G) cellular networks will embrace the spectrum sharing and network architecture modifications to address the throughput enhancement, massive connectivity, and low latency.
To utilize the unlicensed spectrum, we propose a fixed duty cycle based coexistence of LTE and WiFi, in which the duty cycle of LTE transmission can be adjusted based on the amount of data. In the second approach, a multi-arm bandit learning based coexistence of LTE and WiFi has been developed. The duty cycle of transmission and downlink power are adapted through the exploration and exploitation. This approach improves the aggregated capacity by 33\%, along with cell edge and energy efficiency enhancement. We also investigate the performance of LTE and ZigBee coexistence using smart grid as a scenario.
In case of low latency, we summarize the existing works into three domains in the context of 5G networks: core, radio and caching networks. Along with this, fundamental constraints for achieving low latency are identified followed by a general overview of exemplary 5G networks. Besides that, a loop-free, low latency and local-decision based routing protocol is derived in the context of smart grid. This approach ensures low latency and reliable data communication for stationary devices.
To address data security in wireless communication, we introduce a geo-location based data encryption, along with node authentication by k-nearest neighbor algorithm. In the second approach, node authentication by the support vector machine, along with public-private key management, is proposed. Both approaches ensure data security without increasing the packet overhead compared to the existing approaches.
Identifier
FIDC007027
ORCID
https://orcid.org/0000-0002-5134-3797
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Parvez, Imtiaz, "Spectrum Sharing, Latency, and Security in 5G Networks with Application to IoT and Smart Grid" (2018). FIU Electronic Theses and Dissertations. 3879.
https://digitalcommons.fiu.edu/etd/3879
Included in
Electrical and Electronics Commons, Power and Energy Commons, Systems and Communications Commons
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