Sudan University of Science and Technology
Collage of Post graduate Studies
M.Sc. in Communication Engineering
Enhanced PHY for Cellular Low Power IoT
Mona Bakri Hassan Dahab.
Prof. Rashid A. Saeed.
Internet of Things (IoT) is a network of smart devices which enables these devices to communicate, collect and exchange data with each other through the internet. IoT can be used in various life application such as industry, transportation, logistics, healthcare, smart environment, smart home, social gaming robot, and city information. 1.
After internet and mobile communication network, Iot has been considered as the third wave of information technology 2.
One of the essential factor of the IoT are the communication protocols and it is categorized into: LPWAN and short range network 1. Low-Power Wide Area Network (LPWAN) is a wireless wide area network technology that uses existing mobile radio networks with characteristics such as large coverage areas, low bandwidth, possibly very small packet and application-layer data sizes, and long battery life operation. LPWAN can be operate up in both licensed frequency spectrum (cellular), and unlicensed frequency spectrum technology variants. Low power wide area network divided into two SigFox and Cellular. SigFox uses a UNB (Ultra Narrow Band) based radio technology to connect devices to its global network. It is a low power technology for wireless communication which consume little power and operate over long distance 1 2.
Cellular IoT connects IoT devices using existing cellular networks. Cellular IoT takes advantages: Low battery life, low device cost, low deployment cost, extended coverage, secure connectivity and strong authentication also support for a massive number of devices. Cellular technology is a tremendous match for applications that required high data throughput and have a power source. It takes advantages of 3G/4G cellular communication capabilities. They are not suitable for M2M or local network communication 3 4.
This research achieves performance by improving coverage, data rate and connectivity while keeping similar level of complexity and power consumption at the node for the access by using EPHYL for cellular IoT.
2. Literature Review and Related Works Covered
In 5, authors provide a detailed evaluation of the coverage performance of narrow-band IoT (NBIoT) system which is a new radio access technology in 3GPP that provides support for IoT devices. The evaluation is based on the hypothesis of a single cell and channel model used is an Urban (TU) channel consisting of 12 taps with a Doppler spread of 1 Hz. They show that compared with existing LTE technology, NB-IoT can operate at 164 dB MCL, which translates to a coverage enhancement of 20 dB in various scenarios as well as good co-existence performance with existing LTE system.
In 6, authors used a new method based on dynamic spectrum using machine learning algorithms to enhance the NB-IoT coverage instead of using a random spectrum access procedure. This algorithms can decrease number of required repetitions, increase the coverage, and reduce the energy consumption compared with random selection procedure is replaced by a more efficient selection method that chooses the channels with the highest prospect to be available, and with the best coverage and the lowest number of required repetitions.
In 7, authors provide an overview of past and ongoing LTE features to address Machine type communications (MTC) services. Describe performance analysis of LTE for cellular IoT is provided for the macro-cell scenario, Performance evaluation shows system capacity, coverage enhancement and battery life. The deployment scenario for suburban macro-cell. The inter-site distance is 1732 meter. The carrier frequency is 900 MHz. Devices are randomly locate on each cell and assumed to be stationary.
3. Problem Statement
Due to increased demand of wireless communication, congestion of radio spectrum is a real problem, the support of IoT communication in cellular networks requires a new features to enable low cost and power also, to enhance coverage. EPHYL for cellular IoT used to reduce the UE complexity and increase coverage, and higher-layer procedures to reduce the power consumption of devices.
4. Proposed Solutions
Enhanced Physical Layer for cellular IoT (EPHYL) is used to improve coverage, data rate and connectivity.
5. Research Aims and Objectives
The general objective of the project Enhanced physical layer for cellular low power IoT is to investigate coming and future Low power wide area network technologies and the aim efficiency and the thesis aim are:
To enhance spectral efficiency.
To enhance the overall system throughput.
To enhance energy efficiency.
To increase data rate.
To decrease the transmission delay.
The Methodology of this research is composed of four phases:
The first phase: concerning background cellular IoT through environment.
The second phase: study EPHYL to enhance Performance
The Third phase: using EPHYL for cellular IoT to enhance performance.
The fourth phase: MATLAB or NS-3 simulation will be used and result will be figured out.
All network will be simulated by using Matlab or NS-3.
8. Time table schedule
Table (1): Project Schedule
chapters 1 2 3 4 5 6
Introduction Literature Review System Design Result and discussion Conclusion and recommendation 9. References
1 Shadi Al-Sarawi, Mohammed Anbar, Kamal Alieyan, Mahmood Alzubaidi, “Internet of Things (IoT) Communication Protocols :Review “, International Conference on Information Technology 2017.
2 Keith E. Nolan, Wael Guibene, Mark Y. Kelly, “An Evaluation of Low Power Wide Area Network Technologies for the Internet Of Things”, IEEE, 2016.
3 Samie, F., Bauer, L. & Henkel, J. 2016, “IoT technologies for embedded computing: A survey”, International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2016.
4 Alliance, L, “A technical overview of LoRa and LoRaWAN. White Paper”, 2015, November.
5 Ansuman Adhikary, Xingqin Lin and Y.-P. Eric Wang, “Performance Evaluation of NB-IoT Coverage”, IEEE, 2016.
6 Marwa Chafii, Faouzi Bader, Jacques Palicot, “Enhancing Coverage in Narrow Band-IoT Using
Machine Learning”, IEEE Wireless Communications and Networking Conference, 2018.
7 Rapeepat Ratasuk, Nitin Mangalvedhe, and Amitava Ghosh, “Overview of LTE Enhancements for Cellular IoT”, International Symposium on Personal, Indoor and Mobile Radio Communications, 2015.