activity
20122023
most citedOn the Spectral Efficiency of Full-Duplex Small Cell Wireless Systems

240 citations · 866 across the 44 of their papers we have counts for

collaborators

49 papers

cs.IT2023

Achievable Rate of a STAR-RIS Assisted Massive MIMO System Under Spatially-Correlated Channels

Anastasios Papazafeiropoulos, Le-Nam Tran, Zaid Abdullah +2

Reconfigurable intelligent surfaces (RIS)-assisted massive multiple-input multiple-output (mMIMO) is a promising technology for applications in next-generation networks. However, r…

eess.SP2023★ 1 cited

SCA-Based Beamforming Optimization for IRS-Enabled Secure Integrated Sensing and Communication

Vaibhav Kumar, Marwa Chafii, A. Lee Swindlehurst +2

Integrated sensing and communication (ISAC) is expected to be offered as a fundamental service in the upcoming sixth-generation (6G) communications standard. However, due to the ex…

cs.IT2023★ 1 cited

Optimization of RIS-aided SISO Systems Based on a Mutually Coupled Loaded Wire Dipole Model

Nemanja Stefan Perović, Le-Nam Tran, Marco Di Renzo +1

The electromagnetic (EM) features of reconfigurable intelligent surfaces (RISs) fundamentally determine their operating principles and performance. Motivated by these consideration…

eess.SP2023

A Low-Complexity Solution to Sum Rate Maximization for IRS-assisted SWIPT-MIMO Broadcasting

Vaibhav Kumar, Anastasios Papazafeiropoulos, Muhammad Fainan Hanif +2

This paper focuses on the fundamental problem of maximizing the achievable weighted sum rate (WSR) at information receivers (IRs) in an intelligent reflecting surface (IRS) assiste…

cs.IT2023★ 2 cited

Variational Bayes Inference for Data Detection in Cell-Free Massive MIMO

Ly V. Nguyen, Hien Quoc Ngo, Le-Nam Tran +2

Cell-free massive MIMO is a promising technology for beyond-5G networks. Through the deployment of many cooperating access points (AP), the technology can significantly enhance use…

eess.SP2022★ 8 cited

Mirror Prox Algorithm for Large-Scale Cell-Free Massive MIMO Uplink Power Control

Muhammad Farooq, Hien Quoc Ngo, Le-Nam Tran

We consider the problem of max-min fairness for uplink cell-free massive multiple-input multiple-output (MIMO) subject to per-user power constraints. The standard framework for sol…

eess.SP2022

On the Energy-Efficiency Maximization for IRS-Assisted MIMOME Wiretap Channels

Anshu Mukherjee, Vaibhav Kumar, Derrick Wing Kwan Ng +1

Security and energy efficiency have become crucial features in the modern-era wireless communication. In this paper, we consider an energy-efficient design for intelligent reflecti…

cs.IT2022

On the Achievable Rate of IRS-Assisted Multigroup Multicast Systems

Muhammad Farooq, Vaibhav Kumar, Markku Juntti +1

Intelligent reflecting surfaces (IRSs) have shown huge advantages in many potential use cases and thus have been considered a promising candidate for next-generation wireless syste…

eess.SP2022

A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlink

Vaibhav Kumar, Rui Zhang, Marco Di Renzo +1

In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phase-shifts of the intelligent reflecting surface (IRS) / reconfigurable…

eess.SP2022

Massive MIMO for Serving Federated Learning and Non-Federated Learning Users

Muhammad Farooq, Tung Thanh Vu, Hien Quoc Ngo +1

With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a promising learning framework for beyond 5G wireless networks. It is anticipated…

eess.SP2022★ 2 cited

Serving Federated Learning and Non-Federated Learning Users: A Massive MIMO Approach

Muhammad Farooq, Tung T. Vu, Hien Quoc Ngo +1

Federated learning (FL) with its data privacy protection and communication efficiency has been considered as a promising learning framework for beyond-5G/6G systems. We consider a…

cs.IT2022★ 1 cited

Energy Efficiency Maximization in Large-Scale Cell-Free Massive MIMO: A Projected Gradient Approach

Trang C. Mai, Hien Quoc Ngo, Le-Nam Tran

This paper considers the fundamental power allocation problem in cell-free massive mutiple-input and multiple-output (MIMO) systems which aims at maximizing the total energy effici…

eess.SP2022★ 4 cited

Power Control for Multigroup Multicast Cell-Free Massive MIMO Downlink

Muhammad Farooq, Markku Juntti, Le-Nam Tran

We consider a multigroup multicast cell-free multiple-input multiple-output (MIMO) downlink system with short-term power constraints. In particular, the normalized conjugate beamfo…

eess.SP2022★ 10 cited

Accelerated Projected Gradient Method for the Optimization of Cell-Free Massive MIMO Downlink

Muhammad Farooq, Hien Quoc Ngo, Le-Nam Tran

We consider the downlink of a cell-free massive multiple-input multiple-output (MIMO) system where large number of access points (APs) simultaneously serve a group of users. Two fu…

cs.IT2021★ 41 cited

Achievable Rate Maximization for Underlay Spectrum Sharing MIMO System with Intelligent Reflecting Surface

Vaibhav Kumar, Mark Flanagan, Rui Zhang +1

In this letter, the achievable rate maximization problem is considered for intelligent reflecting surface (IRS) assisted multiple-input multiple-output (MIMO) systems in an underla…

cs.IT2021★ 47 cited

On the Maximum Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel

Nemanja Stefan Perović, Le-Nam Tran, Marco Di Renzo +1

Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation and thus offers a great variety of possible performance and implemen…

cs.IT2021★ 22 cited

A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access

Vaibhav Kumar, Muhammad Fainan Hanif, Markku Juntti +1

To mitigate computational power gap between the network core and edges, mobile edge computing (MEC) is poised to play a fundamental role in future generations of wireless networks.…

cs.IT2021

Secrecy Rate Maximization for Intelligent Reflecting Surface Assisted MIMOME Wiretap Channels

Anshu Mukherjee, Vaibhav Kumar, Le-Nam Tran

Intelligent reflecting surface (IRS) has gained tremendous attention recently as a disruptive technology for beyond 5G networks. In this paper, we consider the problem of secrecy r…

cs.IT2021

On the Secrecy Rate under Statistical QoS Provisioning for RIS-Assisted MISO Wiretap Channel

Vaibhav Kumar, Mark F. Flanagan, Derrick Wing Kwan Ng +1

Reconfigurable intelligent surface (RIS) assisted radio is considered as an enabling technology with great potential for the sixth-generation (6G) wireless communications standard.…

cs.IT2021

On the Optimality of the Stationary Solution of Secrecy Rate Maximization for MIMO Wiretap Channel

Anshu Mukherjee, Vaibhav Kumar, Eduard Jorswieck +2

To achieve perfect secrecy in a multiple-input multiple-output (MIMO) Gaussian wiretap channel (WTC), we need to find its secrecy capacity and optimal signaling, which involves sol…

cs.IT2021

On the Secrecy Rate of Downlink NOMA in Underlay Spectrum Sharing with Imperfect CSI

Vaibhav Kumar, Mark F. Flanagan, Daniel Benevides da Costa +1

In this paper, we present the ergodic sum secrecy rate (ESSR) analysis of an underlay spectrum sharing non-orthogonal multiple access (NOMA) system. We consider the scenario where…

cs.IT2021★ 4 cited

On the Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel

Nemanja Stefan Perović, Le-Nam Tran, Marco Di Renzo +1

Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation and thus offers a great variety of possible performance and implemen…

cs.IT2021

Efficient Numerical Methods for Secrecy Capacity of Gaussian MIMO Wiretap Channel

Anshu Mukherjee, Björn Ottersten, Le Nam Tran

This paper presents two different low-complexity methods for obtaining the secrecy capacity of multiple-input multiple-output (MIMO) wiretap channel subject to a sum power constrai…

cs.NI2021

Dynamic Federated Learning-Based Economic Framework for Internet-of-Vehicles

Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen +3

Federated learning (FL) can empower Internet-of-Vehicles (IoV) networks by leveraging smart vehicles (SVs) to participate in the learning process with minimum data exchanges and pr…