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Alexandra Gallyas-Sanhueza
Researcher at Cornell University
Publications - 15
Citations - 100
Alexandra Gallyas-Sanhueza is an academic researcher from Cornell University. The author has contributed to research in topics: Communication channel & MIMO. The author has an hindex of 5, co-authored 13 publications receiving 58 citations.
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Journal ArticleDOI
Beamspace Channel Estimation for Massive MIMO mmWave Systems: Algorithm and VLSI Design
TL;DR: In this paper, the authors propose a channel estimation algorithm called BEAmspace CHannel EStimation (BEACHES), which adaptively denoises the channel vectors in the beamspace domain using an adaptive shrinkage procedure that relies on Stein's unbiased risk estimator (SURE).
Proceedings ArticleDOI
PPAC: A Versatile In-Memory Accelerator for Matrix-Vector-Product-Like Operations
TL;DR: The Parallel Processor in Associative Content-addressable memory (PPAC) as discussed by the authors is a novel in-memory accelerator that supports a range of matrix-vector-product (MVP)-like operations that find use in traditional and emerging applications.
Posted Content
Beamspace Channel Estimation for Massive MIMO mmWave Systems: Algorithm and VLSI Design
TL;DR: The results show that adaptive channel denoising can be performed at high throughput and in a hardware-friendly manner for massive MU-MIMO mmWave systems with hundreds of antennas.
Proceedings ArticleDOI
BEACHES: Beamspace Channel Estimation for Multi-Antenna mmWave Systems and Beyond
TL;DR: This paper proposes BEAmspace CHannel EStimation (BEACHES), a low-complexity channel estimation algorithm for multi-antenna mmWave systems and beyond that leverages the fact that wave propagation at high frequencies is directional, which enables us to denoise the (approximately) sparse channel state information in the beamspace domain.
Proceedings ArticleDOI
Sparsity-Adaptive Beamspace Channel Estimation for 1-Bit mmWave Massive MIMO Systems
TL;DR: In this paper, a sparsity-adaptive beam-space channel estimation algorithm for 1-bit data converters in all-digital millimeter-wave (mmWave) massive MIMO basestations is proposed.