activity
20162021
most citedFederated Dynamic Spectrum Access

9 citations · 17 across the 8 of their papers we have counts for

collaborators

12 papers

eess.SP2021

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…

eess.SP20219 cited

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…

eess.SP2021

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…

cs.LG2021

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…

eess.SP2020

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…

cs.LG20201 cited

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…