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%.