5G-advanced toward 6G: Past, present, and future
Since the start of 5G work in 3GPP in early 2016, tremendous progress has been made in
both standardization and commercial deployments. 3GPP is now entering the second phase …
both standardization and commercial deployments. 3GPP is now entering the second phase …
Detect to learn: Structure learning with attention and decision feedback for MIMO-OFDM receive processing
The limited over-the-air (OTA) pilot symbols in multiple-input-multiple-output orthogonal-
frequency-division-multiplexing (MIMO-OFDM) systems presents a major challenge for …
frequency-division-multiplexing (MIMO-OFDM) systems presents a major challenge for …
Theoretical foundation and design guideline for reservoir computing-based mimo-ofdm symbol detection
In this paper, we derive a theoretical upper bound on the generalization error of reservoir
computing (RC), a special category of recurrent neural networks (RNNs). The specific RC …
computing (RC), a special category of recurrent neural networks (RNNs). The specific RC …
Channel equalization through reservoir computing: A theoretical perspective
S Jere, R Safavinejad, L Zheng… - IEEE Wireless …, 2023 - ieeexplore.ieee.org
Deep learning practice, including in wireless communications, often relies on trial and error
to optimize neural network (NN) structures and their corresponding hyperparameters. We …
to optimize neural network (NN) structures and their corresponding hyperparameters. We …
Universal Approximation of Linear Time-Invariant (LTI) Systems through RNNs: Power of Randomness in Reservoir Computing
Recurrent neural networks (RNNs) are known to be universal approximators of dynamic
systems under fairly mild and general assumptions. However, RNNs usually suffer from the …
systems under fairly mild and general assumptions. However, RNNs usually suffer from the …
Real-time machine learning for multi-user massive MIMO: Symbol detection using Multi-Mode StructNet
In this paper, we develop a learning-based symbol detection algorithm for massive MIMO-
OFDM systems. To exploit the structure information inherited in the received signals from …
OFDM systems. To exploit the structure information inherited in the received signals from …
Towards explainable machine learning: The effectiveness of reservoir computing in wireless receive processing
Deep learning has seen a rapid adoption in a variety of wireless communications
applications, including at the physical layer. While it has delivered impressive performance …
applications, including at the physical layer. While it has delivered impressive performance …
Learning to estimate: A real-time online learning framework for MIMO-OFDM channel estimation
In this paper we introduce StructNet-CE, a novel real-time online learning framework for
MIMO-OFDM channel estimation, which only utilizes over-the-air (OTA) pilot symbols for …
MIMO-OFDM channel estimation, which only utilizes over-the-air (OTA) pilot symbols for …
Sparse Reconstruction-Based Joint Signal Processing for MIMO-OFDM-IM Integrated Radar and Communication Systems
Y Wang, Y Cao, TS Yeo, Y Cheng, Y Zhang - Remote Sensing, 2024 - mdpi.com
Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM)
technology is widely used in integrated radar and communication systems (IRCSs) …
technology is widely used in integrated radar and communication systems (IRCSs) …
SNNOT: Spiking Neural Network With On-Chip Training for MIMO-OFDM Symbol Detection
Advancing 5G and beyond communications require innovative solutions for symbol
detection in MIMO-OFDM. Our research leverages Spiking Neural Networks (SNNs) …
detection in MIMO-OFDM. Our research leverages Spiking Neural Networks (SNNs) …