Content Gazette - April 2018 - 4

Beyond Massive MIMO: The Potential of Positioning With Large Intelligent Surfaces

http://dx.doi.org/10.1109/TSP.2018.2795547

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Hu, F. Rusek, and O. Edfors

1761

Fast Block LMS and RLS-Based Parameter Estimation and Two-Dimensional Imaging in Monostatic MIMO RADAR
Systems With Multiple Mobile Targets

http://dx.doi.org/10.1109/TSP.2018.2795571

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Dwivedi, P. Aggarwal, and A. K. Jagannatham
Adaptive Radar Detection Using Two Sets of Training Data

http://dx.doi.org/10.1109/TSP.2017.2778684

1775

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Carotenuto, A. De Maio, D. Orlando, and L. Pallotta

1791

Blind Source Separation Algorithms Using Hyperbolic and Givens Rotations for High-Order QAM Constellations
http://dx.doi.org/10.1109/TSP.2017.2777392

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. A. W. Shah, K. Abed-Meraim, and T. Y. Al-Naffouri

Atomic Norm Minimization for Modal Analysis From Random and Compressed Samples

http://dx.doi.org/10.1109/TSP.2018.2793907

1802

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Li, D. Yang, G. Tang, and M. B. Wakin

1817

Low-Complexity Massive MIMO Subspace Estimation and Tracking From Low-Dimensional Projections
http://dx.doi.org/10.1109/TSP.2018.2795560

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Haghighatshoar and G. Caire

Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity

1832

http://dx.doi.org/10.1109/TSP.2018.2793878

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Liu, P.-Y. Chen, and A. O. Hero

1845

Algorithm and Architecture of a Low-Complexity and High-Parallelism Preprocessing-Based K-Best Detector for
Large-Scale MIMO Systems

http://dx.doi.org/10.1109/TSP.2018.2799191

. . . . . . . . . G. Peng, L. Liu, S. Zhou, Y. Xue, S. Yin, and S. Wei

1860

. . . . . J. E. Cohen and N. Gillis

1876

. . . . . . . . Z. Chen, F. Sohrabi, and W. Yu

1890

Dictionary-Based Tensor Canonical Polyadic Decomposition
Sparse Activity Detection for Massive Connectivity

http://dx.doi.org/10.1109/TSP.2017.2777393

http://dx.doi.org/10.1109/TSP.2018.2795540

The Power of Side-Information in Subgraph Detection

http://dx.doi.org/10.1109/TSP.2017.2786266

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Kadavankandy, K. Avrachenkov, L. Cottatellucci, and R. Sundaresan
Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features

1905

http://dx.doi.org/10.1109/TSP.2017.2781640

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P. Bouboulis, S. Chouvardas, and S. Theodoridis

1920

High-Dimensional MVDR Beamforming: Optimized Solutions Based on Spiked Random Matrix Models
http://dx.doi.org/10.1109/TSP.2018.2799183

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. Yang, M. R. McKay, and R. Couillet

www.signalprocessingsociety.org

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APRIL 2018

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Table of Contents for the Digital Edition of Content Gazette - April 2018
