S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Electrical and Computer Engineering (전기·정보공학부) Theses (Ph.D. / Sc.D._전기·정보공학부)
MAC/PHY Strategies for Interference Resilient 2.4 GHz Wireless Connectivity Technologies
2.4 GHz 무선 연결 기술의 간섭 강인성 향상을 위한 MAC/PHY 기법
- 공과대학 전기·컴퓨터공학부
- Issue Date
- 서울대학교 대학원
- 학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2017. 2. 최성현.
- Performance degradation due to ambient interference is emerging as a prominent problem for the wireless connectivity technologies at increasingly crowded 2.4 GHz
unlicensed band, e.g.,Wi-Fi, classic Bluetooth (BT), and Bluetooth Low Energy (BLE). They suffer from severe performance degradation due to both homogeneous (i.e., from the same type of technology) and heterogeneous (from different types of technologies) interference. How to efficiently and effectively manage the interference has
been a major technical issue for the wireless connectivity technologies at 2.4 GHz unlicensed band. In this dissertation, we will consider three research topics, i.e., 1) faster Wi-Fi direct device discovery, 2) better BT and Wi-Fi coexistence, and 3) robust BLE-based
indoor localization, by focusing on how to deal with the ambient interference in order to substantially improve the performance of the 2.4 GHz wireless connectivity technologies.
Firstly, Wi-Fi Direct, now part of Android smartphones, makes it possible for Wi-Fi devices to communicate directly without passing through an access point. Before
starting actual data exchange, two devices should apparently find each other through a device discovery process, called find phase. We identify an inherent drawback of the legacy find phase in terms of the resilience towards the ambient interference, whereby
the device discovery delay tends to become intolerable. Accordingly, we propose a simple and efficient scheme, called Listen Channel Randomization (LCR), in order to
expedite the device discovery. Both the legacy find phase and LCR are evaluated with absorbing Markov chain model, NS-3 simulation, and prototype-based experiments to
corroborate the delay reduction achieved by LCR.
Secondly, dense Wi-Fi and BT environments become increasingly common so that the coexistence issues between Wi-Fi and BT are imperative to solve. We propose BlueCoDE, a coordination scheme for multiple neighboring BT piconets, to make them collision-free and less harmful to Wi-Fi. BlueCoDE does not require any modification
of BT's existing PHY and MAC design, and is practically feasible. We implement a prototype of BlueCoDE on Ubertooth One platform, and corroborate the performance
gain via analysis, NS-3 simulation, and prototype-based experiments. Our experimental results show that with merely 10 legacy BT piconets, neighboring Wi-Fi network becomes useless achieving zero throughput, while BlueCoDE makes the Wi-Fi throughput always remain above 12 Mb/s. We expect BlueCoDE to be a breakthrough solution for coexistence in dense Wi-Fi and BT environments.
Finally, BLE has recently attracted enormous attention for its usage in indoor localization system. Most BLE based indoor localization systems utilize Received Signal
Strength Indication (RSSI) of the received BLE packets to infer current location. We experimentally find out that, when there exist Wi-Fi networks in vicinity, the performance of BLE based indoor localization system heavily degrades due to the ambient Wi-Fi interference causing BLE packet losses. To mitigate the performance degradation, we propose RESCUE, a robust BLE packet detection scheme for RSSI acquisition in indoor localization system. It exploits characteristics of the received signal's estimated Carrier Frequency Offset (CFO) values and timing information. We implement
RESCUE on Ubertooth platform, and demonstrate its performance gain via real environment indoor localization experiments.
In summary, from Chapter 2 to Chapter 4, the aforementioned three pieces of the research work, i.e., LCR for fasterWi-Fi Direct device discovery, BlueCoDE for better Wi-Fi and BT coexistence, and RESCUE for robust BLE-based indoor localization system, will be presented, respectively.