1.1k citations · 3k across the 72 of their papers we have counts for
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Defending Adversarial Attacks on Deep Learning Based Power Allocation in Massive MIMO Using Denoising Autoencoders
Rajeev Sahay, Minjun Zhang, David J. Love +1
Recent work has advocated for the use of deep learning to perform power allocation in the downlink of massive MIMO (maMIMO) networks. Yet, such deep learning models are vulnerable…
Linear Coding for Gaussian Two-Way Channels
Junghoon Kim, Seyyedali Hosseinalipour, Taejoon Kim +2
We consider linear coding for Gaussian two-way channels (GTWCs), in which each user generates the transmit symbols by linearly encoding both its message and the past received symbo…
Massive MIMO Channel Prediction Via Meta-Learning and Deep Denoising: Is a Small Dataset Enough?
Hwanjin Kim, Junil Choi, David J. Love
Accurate channel knowledge is critical in massive multiple-input multiple-output (MIMO), which motivates the use of channel prediction. Machine learning techniques for channel pred…
A Primer on Rate-Splitting Multiple Access: Tutorial, Myths, and Frequently Asked Questions
Bruno Clerckx, Yijie Mao, Eduard A. Jorswieck +4
Rate-Splitting Multiple Access (RSMA) has emerged as a powerful multiple access, interference management, and multi-user strategy for next generation communication systems. In this…
A Neural Network-Prepended GLRT Framework for Signal Detection Under Nonlinear Distortions
Rajeev Sahay, Swaroop Appadwedula, David J. Love +1
Many communications and sensing applications hinge on the detection of a signal in a noisy, interference-heavy environment. Signal processing theory yields techniques such as the g…
Nonparametric Decentralized Detection and Sparse Sensor Selection via Multi-Sensor Online Kernel Scalar Quantization
Jing Guo, Raghu G. Raj, David J. Love +1
Signal classification problems arise in a wide variety of applications, and their demand is only expected to grow. In this paper, we focus on the wireless sensor network signal cla…