UCA-ESPRIT is a recently developed closed-form algorithm for use in conjunction with a uniform circular array (UCA) that provides automatically paired source azimuth and elevation angle estimates. 2-0 unitary ESPRIT is presented as an algorithm providing the same capabilities for a uniform rectangular array (URA). In the final stage of the algorithm, the real and imaginary parts of the ith eigenvalue of a matrix are oneto-one related to the respective direction cosines of the ith source relative to the two major array axes. 2-D u n h y ESPRIT offers a number of advantages over other recently proposed ESPRIT based closed-form 2-D angle estimation techniques. First, except for the final eigenvalue decomposition of dimension equal to the number of sources, it is efficiently formulated in terms of realvalued computation throughout. Second, it is amenable to efficient beamspace implementations that w i l l be presented. Third, it is applicable to array configurations that do not exhibit identical subarrays, e. g., two orthogonal linear arrays. Finally, 2-D u n h y ESPRZT easily handles sources having one member of the spatial frequency coordinate pair in common. Simulation results are presented verifying the efficacy of the method.

No abstract

No abstract

Abstract-Millimeter wave (mmWave) communication is expected to be widely deployed in fifth generation (5G) wireless networks due to the substantial bandwidth available at mmWave frequencies. To overcome the higher path loss observed at mmWave bands, most prior work focused on the design of directional beamforming using analog and/or hybrid beamforming techniques in largescale multiple-input multiple-output (MIMO) systems. Obtaining potential gains from highly directional beamforming in practical systems hinges on sufficient levels of channel estimation accuracy, where the problem of channel estimation becomes more challenging due to the substantial training overhead needed to sound all directions using a high-resolution narrow beam. In this work, we consider the design of multi-resolution beamforming sequences to enable the system to quickly search out the dominant channel direction for single-path channels. The resulting design generates a multilevel beamforming sequence that strikes a balance between minimizing the training overhead and maximizing beamforming gain, where a subset of multilevel beamforming vectors is chosen adaptively to provide an improved average data rate within a constrained time. We propose an efficient method to design a hierarchical multiresolution codebook utilizing a Butler matrix, a generalized discrete Fourier transform (DFT) matrix implemented using analog RF circuitry. Numerical results show the effectiveness of the proposed algorithm.

In this paper, the problem of pilot beam pattern design for channel estimation in massive multiple-input multiple-output systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam pattern design for optimal channel estimation is proposed under the assumption that the channel is a stationary Gauss-Markov random process. The proposed algorithm designs the pilot beam pattern sequentially by exploiting the properties of Kalman filtering and the associated prediction error covariance matrices and also the channel statistics such as spatial and temporal channel correlation. The resulting design generates a sequentially-optimal sequence of pilot beam patterns with low complexity for a given set of system parameters. Numerical results show the effectiveness of the proposed algorithm.Comment: 15 pages, 12 figures, Practical issues such as channel covariance matrix estimation are considere