Search
Results
-
Decentralized beamforming for massive MU-MIMO on a GPU cluster
(2016)2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)In the massive multi-user multiple-input multiple-output (MU-MIMO) downlink, traditional centralized beamforming (or precoding), such as zero-forcing (ZF), entails excessive complexity for the computing hardware, and generates raw baseband data rates that cannot be supported with current interconnect technology and chip I/O interfaces. In this paper, we present a novel decentralized beamforming approach that partitions the base-station ...Conference Paper -
Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity
(2016)Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016)Conventional algorithms for sparse signal recovery and sparse representation rely on l1-norm regularized variational methods. However, when applied to the reconstruction of sparse images, i.e., images where only a few pixels are non-zero, simple l1-norm-based methods ignore potential correlations in the support between adjacent pixels. In a number of applications, one is interested in images that are not only sparse, but also have a support ...Conference Paper