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0111 · Jan 201819922001200920182026
4 results for Angle-of-Arrival

Deep neural networks improve angle of arrival estimation with lower complexity.

problem Estimating the number of sources and their angles of arrival from a single antenna array observation.
method Apply a deep neural network (DNN) approach to the problem.
result Deep neural networks can attain maximum likelihood performance with feasible complexity and outperform other methods.

This paper tackles mmWave beamforming optimization with active learning.

problem Adaptive and sequential optimization of beamforming vectors during mmWave initial access.
method Hierarchical beamforming codebook, noisy search strategies, and active learning from imperfect labeler.
result Upper bound on search time matches noiseless bisection search, with AoA error probability decaying exponentially.

This paper improves indoor positioning accuracy by deploying reference nodes to ensure Line-of-Sight.

problem Systematic bias errors in indoor positioning due to non-LoS propagation.
method Model indoor service area as a graph, partition into cliques for reference nodes, set minimum distance and angle parameters.
result Guaranteed LoS to reference nodes improves indoor positioning accuracy and precision.

In this paper, we study the problem of multi-band (frequency-variant) covariance interpolation with a particular emphasis towards massive MIMO applications. In a massive MIMO system, the communication between each BS with M1M \gg 1 antennas and each single-antenna user occurs through a collection of scatterers in the e…

2018-01-11abs ↗pdf ↗