Benchmark of MEO Multibeam Satellite Adaptive Antenna and Payload Architectures for Broadband Systems

Vidal, Florian; Legay, Hervé; Goussetis, George; Strober, Thomas; Gayrard, Jean-Didier

doi:10.1109/asms/spsc48805.2020.9268898

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…In this case, at most V corresponding DFT vectors per cycle are sufficient to be selected. After the DFT operation 2 , and due to finite precision (q ≤ p), the power spread of Y is limited in the frequency domain 3 . Therefore, we can replace H in the delay domain by a sparse matrix using information about the user spatial distribution as handled by the scheduler: Ĥ ← SH + ϵ : ϵ ∼ CN (0, Ω), where Ω is the delay power spread and S = [s 1 , s 2 , .., 0 L×(B−L) ] T is the spatial-user-adjacency matrix of size M × M having L < B distinct rows with non-zero values.…”

Section: A Matlab Simulationmentioning

confidence: 99%

“…LEO satellites also have a shorter "user dwell" period because of their high radial speed. Medium Earth orbit (MEO) constellations, which normally require between ten to twenty satellites to provide operational coverage, seem to be an appealing solution that attains a reasonable trade-off between LEO constellations and GEO systems [3]. Additionally, MEO offers a latency of 180 ms (at an altitude of 8000 km) which is less than the GEO.…”

Section: Introductionmentioning

confidence: 99%

“…In the infinite case, the DFT matrix W B L is proven to be the eigenvector matrix of the correlation matrix X B L . A crucial result from this statement is that the column vectors of H become approximately sparse after the DFT operation 3. Achieving orthogonality, Y B L is a unitary matrix if we consider infinitely long repetitions of the cycle period.…”

mentioning

confidence: 99%

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FPGA Implementation of Efficient Beamformer for On-Board Processing in MEO Satellites

Palisetty,

Garces Socarras,

Chaker

et al. 2023

2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

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Medium Earth orbit (MEO) constellation is an appealing solution between geostationary equatorial orbit (GEO) and lower Earth orbit (LEO) in terms of latency and number of satellites required. On-board processing of digital beamformer in MEO satellites is an efficient solution for achieving wider bandwidth, increased flexibility, and lower latency. Power constraints, however, make it impractical to digitally create thousands of beams at once. In this paper, area-power efficient digital beamformer architectures are proposed considering key metrics of a typical MEO scenario. The proposed efficient digital beamformer is comprised of a sparse-matrix-based user selection, a 2D discrete Fourier transform (DFT)-based digital beam generation, which is implemented by a fast Fourier transform (FFT) algorithm, and a spatial windowing module for selecting the antenna pattern. Furthermore, architectures of digital beamformer using conventional 2D-FFT approach, fully unrolled 2D-FFT, and an area-power efficient twiddle factor (TF) quantized fully unrolled 2D-FFT are proposed. The spatial windowing architecture concerning 10 × 10 radio frequency chains and sparse matrix architecture for user selection is also proposed. The proposed architectures are implemented targeting Virtex ultrascale FPGA and the area-power utilization is reported. It is noticed that more than 50%-reduction in area and power is achieved with the beamformer incorporating the proposed TF quantized fully unrolled 2D-FFT.

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Section: A Matlab Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%