PhD Dissertation Defense Shivang Aggarwal

Location: ISEC 332

“Towards Reliable, High Capacity mmWave Wireless LANs for Mobile Devices”

Abstract:

The IEEE 802.11ad standard, with its 14 GHz of unlicensed spectrum around 60 GHz, is touted as one of the key technologies for building the next generation of WLANs that will enable high throughput demanding mobile applications. However, there have been serious concerns regarding the susceptibility of mmWave links to mobility and blockage as well as smartphone energy consumption at Gigabit scale data rates.

In this dissertation, first, through extensive measurement campaigns with commercial off-the-shelf (COTS) devices as well as a highly configurable software-defined radio (SDR) based testbed, we characterize the performance and energy efficiency of mobile devices operating in 60 GHz WLANs and identify problems that prevent wide adoption of the mmWave technology in such devices. Then, using the insights from these measurement campaigns, we design solutions to tackle these problems and prototype them for real-world evaluation.
This dissertation makes the following contributions:
(i) We extensively study the performance and power consumption of 802.11ad on commercial smartphones. We focus on the specific aspects affected by unique smartphone features, e.g., antenna placement or user mobility patterns, and compare the performance against that achieved by 802.11ad laptops in previous studies. We also compare 802.11ad against its main competitors 802.11ac and 802.11ax. Overall, our results show that 802.11ad is better able to address the needs of emerging bandwidth-intensive applications in smartphones than its 5 GHz counterparts. At the same time, we identify several key research directions towards realizing its full potential.
(ii) We extensively study the two main link adaptation mechanisms in 802.11ad, rate adaptation (RA) and beamforming. We undertake a large measurement campaign using an SDR-based testbed giving us complete access to the PHY and MAC layers. We look at the two link adaptation mechanisms separately and study the effectiveness of a few RA and beamforming heuristics. Further, look at the interaction between the two link adaptation mechanisms, specifically, which mechanism should be triggered when and in what order. We design a practical, standard-compliant link adaptation framework that leverages ML and PHY layer information to determine when to trigger link adaptation and which adaptation mechanism to use.
(iii) To address the issues with mmWave link reliability, we explore the use of multiple frequency bands to couple the performance of 802.11ad with the reliability of legacy WiFi. To accomplish this, we develop a Multipath TCP (MPTCP) scheduler to efficiently use both interfaces simultaneously in order to achieve a higher overall throughput as well as seamlessly switch to a single interface when the other one fails. Further, we port MPTCP to a dual-band (5 GHz/60 GHz) smartphone, evaluate its power consumption, and provide recommendations towards the design of an energy-aware MPTCP scheduler.
(iv) To enable high user QoE, and maintain that in the face of ever-changing network conditions, applications such as virtual reality (VR) and video streaming perform quality adaptation. A key component of quality adaptation is throughput prediction. Thus, we extensively study the predictability of the network throughput of an 802.11ad WLAN in downloading data to an 802.11ad- enabled mobile device under varying mobility patterns and orientations of the mobile device.
(v) With a dramatic increase in throughput requirements of applications and AP-user density in the near future, multi-user multi-stream communication in the 60 GHz band is required. To this end, the IEEE 802.11ay standard, successor to the current 802.11ad standard, includes support for simultaneous transmission over multiple data streams. Using an SDR-based testbed, we extensively study the performance of SU- and MU-MIMO in 60 GHz WLANs in multiple environments, analyze the performance in each environment, identify the factors that affect it, and compare it against the performance of SISO. Finally, we propose two heuristics that perform both beam and user selection with low overhead while outperforming previously proposed approaches

Committee:
Prof. Dimitrios Koutsonikolas (Advisor)
Prof. Kaushik Chowdhury
Prof. Tommaso Melodia