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20182020
most citedDeep Learning-Based Channel Estimation for High-Dimensional Signals

28 citations · 31 across the 5 of their papers we have counts for

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7 papers · 1 filter

eess.SP2020

Wideband Channel Estimation with A Generative Adversarial Network

Eren Balevi, Jeffrey G. Andrews

Communication at high carrier frequencies such as millimeter wave (mmWave) and terahertz (THz) requires channel estimation for very large bandwidths at low SNR. Hence, allocating a…

eess.SP2020

High Dimensional Channel Estimation Using Deep Generative Networks

Eren Balevi, Akash Doshi, Ajil Jalal +2

This paper presents a novel compressed sensing (CS) approach to high dimensional wireless channel estimation by optimizing the input to a deep generative network. Channel estimatio…

eess.SP2019

Two-Stage Learning for Uplink Channel Estimation in One-Bit Massive MIMO

Eren Balevi, Jeffrey G. Andrews

We develop a two-stage deep learning pipeline architecture to estimate the uplink massive MIMO channel with one-bit ADCs. This deep learning pipeline is composed of two separate ge…

eess.SP2019

Massive MIMO Channel Estimation with an Untrained Deep Neural Network

Eren Balevi, Akash Doshi, Jeffrey G. Andrews

This paper proposes a deep learning-based channel estimation method for multi-cell interference-limited massive MIMO systems, in which base stations equipped with a large number of…

eess.SP2019★ 28 cited

Deep Learning-Based Channel Estimation for High-Dimensional Signals

Eren Balevi, Jeffrey G. Andrews

We propose a novel deep learning-based channel estimation technique for high-dimensional communication signals that does not require any training. Our method is broadly applicable…

eess.SP2018★ 3 cited

Enabling Aloha-NOMA for Massive M2M Communication in IoT Networks

Mohamed Elkourdi, Asim Mazin, Eren Balevi +1

The Internet of things (IoT), which is the network of physical devices embedded with sensors, actuators, and connec- tivity, is being accelerated into the mainstream by the emergen…

eess.SP2018

ALOHA-NOMA for Massive Machine-to-Machine IoT Communication

Eren Balevi, Faeik T. Al Rabee, Richard D. Gitlin

This paper proposes a new medium access control (MAC) protocol for Internet of Things (IoT) applications incorporating pure ALOHA with power domain non-orthogonal multiple access (…