65 citations · 122 across the 14 of their papers we have counts for
14 papers
RC-Struct: A Structure-based Neural Network Approach for MIMO-OFDM Detection
Jiarui Xu, Zhou Zhou, Lianjun Li +2
In this paper, we introduce a structure-based neural network architecture, namely RC-Struct, for MIMO-OFDM symbol detection. The RC-Struct exploits the temporal structure of the MI…
Learning to Equalize OTFS
Zhou Zhou, Lingjia Liu, Jiarui Xu +1
Orthogonal Time Frequency Space (OTFS) is a novel framework that processes modulation symbols via a time-independent channel characterized by the delay-Doppler domain. The conventi…
Federated Dynamic Spectrum Access
Yifei Song, Hao-Hsuan Chang, Zhou Zhou +2
Due to the growing volume of data traffic produced by the surge of Internet of Things (IoT) devices, the demand for radio spectrum resources is approaching their limitation defined…
Making Intelligent Reflecting Surfaces More Intelligent: A Roadmap Through Reservoir Computing
Zhou Zhou, Kangjun Bai, Nima Mohammadi +2
This article introduces a neural network-based signal processing framework for intelligent reflecting surface (IRS) aided wireless communications systems. By modeling radio-frequen…
Harnessing Tensor Structures -- Multi-Mode Reservoir Computing and Its Application in Massive MIMO
Zhou Zhou, Lingjia Liu, Jiarui Xu
In this paper, we introduce a new neural network (NN) structure, multi-mode reservoir computing (Multi-Mode RC). It inherits the dynamic mechanism of RC and processes the forward p…
Learning with Knowledge of Structure: A Neural Network-Based Approach for MIMO-OFDM Detection
Zhou Zhou, Shashank Jere, Lizhong Zheng +1
In this paper, we explore neural network-based strategies for performing symbol detection in a MIMO-OFDM system. Building on a reservoir computing (RC)-based approach towards symbo…
Pareto Deterministic Policy Gradients and Its Application in 5G Massive MIMO Networks
Zhou Zhou, Yan Xin, Hao Chen +2
In this paper, we consider jointly optimizing cell load balance and network throughput via a reinforcement learning (RL) approach, where inter-cell handover (i.e., user association…
Learning for Integer-Constrained Optimization through Neural Networks with Limited Training
Zhou Zhou, Shashank Jere, Lizhong Zheng +1
In this paper, we investigate a neural network-based learning approach towards solving an integer-constrained programming problem using very limited training. To be specific, we in…
RCNet: Incorporating Structural Information into Deep RNN for MIMO-OFDM Symbol Detection with Limited Training
Zhou Zhou, Lingjia Liu, Shashank Jere +3
In this paper, we investigate learning-based MIMO-OFDM symbol detection strategies focusing on a special recurrent neural network (RNN) -- reservoir computing (RC). We first introd…
CogRF: A New Frontier for Machine Learning and Artificial Intelligence for 6G RF Systems
Tarun Cousik, Rubayet Shafin, Zhou Zhou +3
The concept of CogRF, a novel tunable radio frequency (RF) frontend that uses artificial intelligence (AI) to meet mission requirements for beyond 5G and 6G systems, is introduced.…
Learning for Detection: MIMO-OFDM Symbol Detection through Downlink Pilots
Zhou Zhou, Lingjia Liu, Hao-Hsuan Chang
Reservoir computing (RC) is a special recurrent neural network which consists of a fixed high dimensional feature mapping and trained readout weights. In this paper, we introduce a…
Bayesian Compressive Sensing Using Normal Product Priors
Zhou Zhou, Kaihui Liu, Jun Fang
In this paper, we introduce a new sparsity-promoting prior, namely, the "normal product" prior, and develop an efficient algorithm for sparse signal recovery under the Bayesian fra…
Low-Rank Tensor Decomposition-Aided Channel Estimation for Millimeter Wave MIMO-OFDM Systems
Zhou Zhou, Jun Fang, Linxiao Yang +3
We consider the problem of downlink channel estimation for millimeter wave (mmWave) MIMO-OFDM systems, where both the base station (BS) and the mobile station (MS) employ large ant…
Channel Estimation for Millimeter Wave Multiuser MIMO Systems via PARAFAC Decomposition
Zhou Zhou, Jun Fang, Linxiao Yang +3
We consider the problem of uplink channel estimation for millimeter wave (mmWave) systems, where the base station (BS) and mobile stations (MSs) are equipped with large antenna arr…