Coordination and Interference in 802.11 Networks: Inference, Analysis and Mitigation

In the last decade, 802.11 wireless devices data-rates have increased by three orders of magnitude, while communications experiencing low throughput are still largely present. Such throughput loss is a fundamental problem of wireless networking that is difficult to diagnose and amend. My research addresses two key causes of throughput loss: MAC layer protocol overhead and destructive link interference. First, I design WiFi-Nano reducing the channel access overhead by an order of magnitude leveraging an innovative speculative technique to transmit preambles. This new concept is based on simultaneous preamble transmission and detection via a self-interference cancellation design, and paves the way to the realization of the collision detection paradigm in wireless networks. Next, I propose 802.11ec (Encoded Control), the first 802.11-based protocol that eliminates the overhead of control packets. Instead, 802.11ec coordinates node transmissions via a set of predefined pseudo-noise codewords, resulting in the dramatic increase of throughput and communication robustness. Finally, I design MIDAS, a model-driven network management tool that alleviates low throughput wireless links identifying key corrective actions. MIDAS' key contribution is to reveal the fundamental role of node transmission coordination in characterizing destructive interference. I implement WiFi-Nano, 802.11ec, and MIDAS using a combination of WARP FPGA-based radio boards, custom emulation platforms, and network simulators. The results obtained show that WiFi-Nano increases the network throughput by up to 100%, 802.11ec improves network access fairness by up to 90%, and MIDAS identifies corrective actions with a prediction error as low as 20%

Practical interference mitigation for Wi-Fi systems

Wi-Fi's popularity is also its Achilles' heel since in the dense deployments of multiple Wi-Fi networks typical in urban environments, concurrent transmissions interfere. The advent of networked devices with multiple antennas allows new ways to improve Wi-Fi's performance: a host can align the phases of the signals either received at or transmitted from its antennas so as to either maximize the power of the signal of interest through beamforming or minimize the power of interference through nulling. Theory predicts that these techniques should enable concurrent transmissions by proximal sender-receiver pairs, thus improving capacity. Yet practical challenges remain. Hardware platform limitations can prevent precise measurement of the wireless channel, or limit the accuracy of beamforming and nulling. The interaction between nulling and Wi-Fi's OFDM modulation, which transmits tranches of a packet's bits on distinct subcarriers, is subtle and can sacrifice the capacity gain expected from nulling. And in deployments where Wi-Fi networks are independently administered, APs must efficiently share channel measurements and coordinate their transmissions to null effectively. In this thesis, I design and experimentally evaluate beamforming and nulling techniques for use in Wi-Fi networks that address the aforementioned practical challenges. My contributions include: - Cone of Silence (CoS): a system that allows a Wi-Fi AP equipped with a phased-array antenna but only a single 802.11g radio to mitigate interference from senders other than its intended one, thus boosting throughput; - Cooperative Power Allocation (COPA): a system that efficiently shares channel measurements and coordinates transmissions between independent APs, and cooperatively allocates power so as to render received power across OFDM subcarriers flat at each AP's receiver, thus boosting throughput; - Power Allocation for Distributed MIMO (PADM): a system that leverages intelligent power allocation to mitigate inter-stream interference in distributed MIMO wireless networks, thus boosting throughput