MAC/PHY Strategies for Interference Resilient 2.4 GHz Wireless Connectivity Technologies

Abstract

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.