2019
DOI: 10.1109/tsp.2019.2955828
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Design of Large Effective Apertures for Millimeter Wave Systems Using a Sparse Array of Subarrays

Abstract: We investigate synthesis of a large effective aperture using a sparse array of subarrays. We employ a multi-objective optimization framework for placement of subarrays within a prescribed area dictated by form factor constraints, trading off the smaller beam width obtained by spacing out the subarrays against the grating and side lobes created by sparse placement. We assess the performance of our designs for the fundamental problem of bearing estimation for one or more sources, comparing performance against es… Show more

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Cited by 14 publications
(18 citation statements)
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References 28 publications
(33 reference statements)
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“…Beam angles in a codebook do not affect one another because of the orthogonal beam principle. In accordance with (33), we know that the lower bound of the estimated angle is related to SNR and the number of pilots of CSI-RS N s , given a fixing codebook. Figure 6 shows the estimation errors of the four-, three-, and two-beam codebooks.…”
Section: A Simulationsmentioning
confidence: 86%
See 1 more Smart Citation
“…Beam angles in a codebook do not affect one another because of the orthogonal beam principle. In accordance with (33), we know that the lower bound of the estimated angle is related to SNR and the number of pilots of CSI-RS N s , given a fixing codebook. Figure 6 shows the estimation errors of the four-, three-, and two-beam codebooks.…”
Section: A Simulationsmentioning
confidence: 86%
“…Any algorithm with high accuracy [30], [31] can be used in Fast-ABS to estimate the ToA, AoA, and gain of multipath. In this paper, we employ the Newtonized orthogonal matching pursuit (NOMP) algorithm [32] in Fast-ABS, because we find that NOMP provides better performance and lower complexity than many existing algorithms [33].…”
Section: Path Parameter Estimation Algorithmmentioning
confidence: 99%
“…Under the constraints of array element spacing, heuristic algorithms have to filter the solutions at each iteration, which leads to decrease in both accuracy and speed. Moreover, it is worth noting that the SLL and MLW are usually trade-offs to be made in the optimization, as illustrated by studies in [22], [24]. Their objective functions often contain multiple metrics weighted together, like αSLL + βMLW, essentially turning the constrained optimization problem into an unconstrained one, which can then be readily solved by heuristic algorithms.…”
Section: Introductionmentioning
confidence: 99%
“…The impact of the threshold effect on antenna selection can be alleviated by adding constraints on the peak sidelobe level (PSL) and leveraging convex optimization tools to minimize the CRLB [13], [14]. In spite of the great performance, the application of a fixed threshold level across the whole DOA range does not guarantee optimality since the threshold value is DOA-dependent.…”
Section: Introductionmentioning
confidence: 99%