Signal processing on antenna arrays has received much recent attention in the mobile and wireless networking research communities, with array signal processing approaches addressing the problems of human movement detection, indoor mobile device localization, and wireless network security. However, there are three important challenges inherent in the design of these systems that must be overcome if they are to be of practical use on commodity hardware. First, phase differences between the radio oscillators behind each antenna can make readings unusable, and so must be corrected in order for most techniques to yield high-fidelity results. Second, in many deployments, access points are elevated to maximize coverage, introducing height differences between the mobile device and antenna array (usually the access point) that can skew results. Third, while the number of antennas on commodity access points is usually limited, most array processing increases in fidelity with more antennas. Worse still, these issues work in synergistic opposition to array processing: without phase offset correction, no phase-difference array processing is possible, and unknown height differences between mobiles and access points make automatic correction of these phase offsets even more challenging. Furthermore, limited numbers of antennas result in poor fidelity, complicating both problems further. We present ArrayPhaser, a system that solves these intertwined problems to make phased array signal processing truly practical on the many WiFi access points deployed in the real world. Our experimental results on threeand five-antenna 802.11-based hardware show that 802.11 NICs can be calibrated and synchronized to a tolerance of 15◦ median phase error, enabling inexpensive deployment of numerous phase-difference based spectral analysis techniques previously only available on costly, special-purpose hardware. This material is based on work supported by the European Research Council under Grant No. 279976. ArrayPhaser: Enabling Signal Processing on WiFi Access Points Jon Gjengset Graeme McPhillips Kyle Jamieson
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