Abstract-Recent work has shown that mesh networks based on short-range outdoor millimeter (mm) wave links in the unlicensed 60 GHz band are a promising approach to providing an easily deployable broadband infrastructure. In this paper, we investigate the robustness of such links, focusing in particular on the effect of multipath fading resulting from reflections from the ground and building walls for a lamppost deployment of mm wave nodes. Our ray tracing based model shows that, while only a small number of paths are significant for the highly directional links considered, they can cause significant fluctuations in the received signal strength. Our simulations show that 10-20 dB fades below the benchmark of free space propagation can occur quite easily (e.g., 5-15% of the time, averaging across typical deployment scenarios), and that the received power is extremely sensitive to small variations in geometry (e.g., altering the position of the antenna by 1 cm can reduce the received power as much as 46.7 dB). We also demonstrate, however, that extremely robust performance can be obtained by employing multiple antennas at appropriately chosen separations, using standard space-time communications strategies such as transmit precoding (when the transmitter knows the channel) and space-time coding (when the transmitter does not know the channel).

Abstract-We consider the problem of adapting very large antenna arrays (e.g., with 1000 elements or more) for tasks such as beamforming and nulling, motivated by emerging applications at very high carrier frequencies in the millimeter (mm) wave band and beyond, where the small wavelengths make it possible to pack a very large number of antenna elements (e.g., realized as a printed circuit array) into nodes with compact form factors. Conventional least squares techniques, which rely on access to baseband signals for individual array elements, do not apply. Hence the preferred approach is to perform radio frequency (RF) beamsteering, with a single complex baseband signal emerging from a receive array, or going into a transmit array. Further, we are interested in what can be achieved with coarse-grained control of individual elements (e.g., four-phase, or even binary phase, control). In this paper, we propose an adaptation architecture matched to these hardware constraints. Our approach comprises the following two steps. The first step is compressive estimation of a sparse spatial channel using a small number of measurements, each using a different set of randomized weights. However, unlike the standard compressive sensing formulation, we are interested in estimating continuousvalued parameters such as the angles of arrivals of various paths. The second step is quantized beamsteering, where weights for beamforming and nulling, subject to the constraint of severe quantization, are computed using the channel estimates from the first step. We provide promising preliminary results illustrating the efficacy of this approach.

Abstract-Compressed sensing is by now well-established as an effective tool for extracting sparsely distributed information, where sparsity is a discrete concept, referring to the number of dominant nonzero signal components in some basis for the signal space. In this paper, we establish a framework for estimation of continuous-valued parameters based on compressive measurements on a signal corrupted by additive white Gaussian noise (AWGN). While standard compressed sensing based on naive discretization has been shown to suffer from performance loss due to basis mismatch, we demonstrate that this is not an inherent property of compressive measurements. Our contributions are summarized as follows: (a) We identify the isometries required to preserve fundamental estimation-theoretic quantities such as the Ziv-Zakai bound (ZZB) and the Cramér-Rao bound (CRB). Under such isometries, compressive projections can be interpreted simply as a reduction in "effective SNR." (b) We show that the threshold behavior of the ZZB provides a criterion for determining the minimum number of measurements for "accurate" parameter estimation. (c) We provide detailed computations of the number of measurements needed for the isometries in (a) to hold for the problem of frequency estimation in a mixture of sinusoids. We show via simulations that the design criterion in (b) is accurate for estimating the frequency of a single sinusoid.

Abstract-We investigate a computationally and memory efficient algorithm for radio frequency (RF) source-seeking with a single-wing rotating micro aerial vehicle (MAV) equipped with a directional antenna. The MAV is assumed to have no knowledge of its position and to have only an estimate of orientation through a magnetometer. A key novelty of our approach is in exploiting the rotation of the MAV and the directionality of its RF antenna to derive estimates of the angle of arrival (AOA) at each rotation. The MAV then follows the estimated direction until the next rotation is complete. We prove convergence of this greedy algorithm under rather weak assumptions on the noise associated with the AOA estimates, using recent results on the property of recurrence for systems governed by stochastic difference inclusions. These convergence results are supplemented by simulations quantifying the amount of excess travel, relative to the straight line distance to the source. Indoor experiments using Lockheed Martin's Samarai MAV demonstrate the efficacy of the greedy algorithm both for static source-seeking, and for the more challenging problem of tracking a moving source.

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