Millimeter wave (mmWave) wireless networks are envisioned to bring a very high degree of spatial reuse, i.e., multiple links can operate concurrently without interference. The vision, however, is becoming doubtful, as recent studies found that non-negligible interference exists due to imperfect beam patterns generated by commodity mmWave radios and strong reflections. In this paper, we conduct an extensive measurement on the spatial reuse issue in a dense 60 GHz mmWave network consisting of multiple access points (AP) and users. Our measurement quantifies the impact of interference on network performance and finds that the existing prediction-based interference-resolving approaches are insufficient. Motivated by the findings, we propose mmMuxing, which enhances the spatial reuse in 60 GHz mmWave networks. Instead of relying on interference prediction, mmMuxing takes a new measurement principle of building a conflict graph that implicitly takes into account the impact of both beam imperfectness and reflections. Using the conflict graph, mmMuxing designs a joint user-beam selection algorithm, which can determine the optimal user-beam combination and lead to the minimum interference in each schedule. We prototype and evaluate mmMuxing over testbed using commodity mmWave radios. The evaluation results demonstrate that mmMuxing improves network throughput by multi-folds compared with the state-of-the-art.

The emerging millimeter-wave (mmWave) networking technology promises to unleash a new wave of multi-Gbps wireless applications. However, due to high directionality of the mmWave radios, maintaining stable link connection remains an open problem. Users' slight orientation change, coupled with motion and blockage, can easily disconnect the link. In this paper, we propose RoMil, a robotic mmWave relay that optimizes network coverage through wireless sensing and autonomous motion/rotation planning. The robot relay automatically constructs the geometry/reflectivity of the environment, by estimating the geometries of all signal paths. It then navigates itself along an optimal moving trajectory, and ensures continuous connectivity for the client despite environment/human dynamics. We have prototyped RoMil on a programmable robot carrying a commodity 60 GHz radio. Our field trials demonstrate that RoMil can achieve nearly full coverage in dynamic environment, even with constrained speed and mobility region.

Ambient environment information, including reflectors' location, dimension and reflectivity, is a key input to many millimeter-wave (mmWave) networking and sensing applications. It has found versatile applications in optimizing network coverage and robustness, enhancing mobile link performance, and enabling high-accuracy indoor localization and navigation. Recent approaches of deriving mmWave environment information require heavy infrastructure support or non-trivial human labor, and rely on costly software defined radios, which prevent their usage in practice. In this work, we design and implement mmRanger, a system can automatically sense environment without any infrastructure support. mmRanger equips a pair of low-cost off-the-shelf mmWave radios in a commodity robot, which constantly samples the ambient environment by exchanging a series of mmWave signals while it moves and rotates. mmRanger then re-engineers the time-domain signal series to derive the spatial-domain environment structure, through novel reflection path extraction and reflector mapping algorithms. Our experiments verify that mmRanger can accurately sense a given environment with minimal overhead, and the learned information can bring 1.6× and 2.1× performance gain, in terms of network coverage and mobile link throughput, respectively, over empirical approaches in mmWave networks.

The emerging millimeter-wave (mmWave) networking technology promises to unleash a new wave of multi-Gbps wireless applications. However, due to high directionality of the mmWave radios, maintaining stable link connection remains an open problem. Users' slight orientation change, coupled with motion and blockage, can easily disconnect the link. In this paper, we propose miDroid, a robotic mmWave relay that optimizes network coverage through wireless sensing and autonomous motion/rotation planning. The robot relay automatically constructs the geometry/reflectivity of the environment, by estimating the geometries of all signal paths. It then navigates itself along an optimal moving trajectory, and ensures continuous connectivity for the client despite environment/human dynamics. We have prototyped miDroid on a programmable robot carrying a commodity 60 GHz radio. Our field trials demonstrate that miDroid can achieve nearly full coverage in dynamic environment, even with constrained speed and mobility region.