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Multi-Layer Precoding: A Potential Solution for Full-Dimensional Massive MIMO Systems
Ahmed Alkhateeb, Geert Leus, Robert W. Heath
Massive multiple-input multiple-output (MIMO) systems achieve high sum spectral efficiency by offering an order of magnitude increase in multiplexing gains. In time division duplex…
Learning Sparse Graphs Under Smoothness Prior
Sundeep Prabhakar Chepuri, Sijia Liu, Geert Leus +1
In this paper, we are interested in learning the underlying graph structure behind training data. Solving this basic problem is essential to carry out any graph signal processing o…
2-Dimensional Finite Impulse Response Graph-Temporal Filters
Elvin Isufi, Geert Leus, Paolo Banelli
Finite impulse response (FIR) graph filters play a crucial role in the field of signal processing on graphs. However, when the graph signal is time-varying, the state of the art FI…
Subsampling for Graph Power Spectrum Estimation
Sundeep Prabhakar Chepuri, Geert Leus
In this paper we focus on subsampling stationary random processes that reside on the vertices of undirected graphs. Second-order stationary graph signals are obtained by filtering…
Stationary Graph Processes and Spectral Estimation
Antonio G. Marques, Santiago Segarra, Geert Leus +1
Stationarity is a cornerstone property that facilitates the analysis and processing of random signals in the time domain. Although time-varying signals are abundant in nature, in m…
Autoregressive Moving Average Graph Filtering
Elvin Isufi, Andreas Loukas, Andrea Simonetto +1
One of the cornerstones of the field of signal processing on graphs are graph filters, direct analogues of classical filters, but intended for signals defined on graphs. This work…