291 citations · 508 across the 23 of their papers we have counts for
23 papers
End-to-end Learning of Probabilistic and Geometric Constellation Shaping with Iterative Receivers
Harindu Jayarathne, Dileepa Marasinghe, Nandana Rajatheva +1
An end-to-end learning method for constellation shaping with a shaping-encoder assisted transceiver architecture is presented. The shaping encoder, which produces shaping bits with…
A CNN-based End-to-End Learning for RIS-assisted Communication System
Nipuni Ginige, Nandana Rajatheva, Matti Latva-aho
Reconfigurable intelligent surface (RIS) is an emerging technology that is used to improve the system performance in beyond 5G systems. In this letter, we propose a novel convoluti…
Efficient Channel Prediction for Beyond Diagonal RIS-Assisted MIMO Systems with Channel Aging
Nipuni Ginige, Arthur Sousa de Sena, Nurul Huda Mahmood +2
Novel reconfigurable intelligent surface (RIS) architectures, known as beyond diagonal RISs (BD-RISs), have been proposed to enhance reflection efficiency and expand RIS capabiliti…
Waveform Learning under Phase Noise Impairment for Sub-THz Communications
Dileepa Marasinghe, Le Hang Nguyen, Jafar Mohammadi +3
The large untapped spectrum in sub-THz allows for ultra-high throughput communication to realize many seemingly impossible applications in 6G. Phase noise (PN) is one key hardware…
Machine Learning-Based Channel Prediction for RIS-assisted MIMO Systems With Channel Aging
Nipuni Ginige, Arthur Sousa de Sena, Nurul Huda Mahmood +2
Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology to enhance the performance of sixth-generation (6G) and beyond communication systems. The passive…
5G-Advanced AI/ML Beam Management: Performance Evaluation with Integrated ML Models
Nalin Jayaweera, Andrea Bonfante, Mark Schamberger +6
The legacy beam management (BM) procedure in 5G introduces higher measurement and reporting overheads for larger beam codebooks resulting in higher power consumption of user equipm…
Constellation Shaping under Phase Noise Impairment for Sub-THz Communications
Dileepa Marasinghe, Le Hang Nguyen, Jafar Mohammadi +3
The large untapped spectrum in the sub-THz allows for ultra-high throughput communication to realize many seemingly impossible applications in 6G. One of the challenges in radio co…
GDOP Based BS Selection for Positioning in mmWave 5G NR Networks
A. Indika Perera, K. B. Shashika Manosha, Nandana Rajatheva +1
The fifth-generation (5G) of mobile communication supported by millimetre-wave (mmWave) technology and higher base station (BS) densification facilitate to enhance user equipment (…
Decomposition Based Interference Management Framework for Local 6G Networks
Samitha Gunarathne, Thushan Sivalingam, Nurul Huda Mahmood +2
Managing inter-cell interference is among the major challenges in a wireless network, more so when strict quality of service needs to be guaranteed such as in ultra-reliable low la…
Minimizing Energy Consumption in MU-MIMO via Antenna Muting by Neural Networks with Asymmetric Loss
Nuwanthika Rajapaksha, Jafar Mohammadi, Stefan Wesemann +2
Transmit antenna muting (TAM) in multiple-user multiple-input multiple-output (MU-MIMO) networks allows reducing the power consumption of the base station (BS) by properly utilizin…
Predictive Resource Allocation for URLLC using Empirical Mode Decomposition
Chandu Jayawardhana, Thushan Sivalingam, Nurul Huda Mahmood +2
Effective resource allocation is a crucial requirement to achieve the stringent performance targets of ultra-reliable low-latency communication (URLLC) services. Predicting future…
Automatic and Flexible Transmission of Semantic Map Images using Polar Codes for End-to-End Semantic-based Communication Systems
Hossein Rezaei, Thushan Sivalingam, Nandana Rajatheva
Semantic communication represents a promising roadmap toward achieving end-to-end communication with reduced communication overhead and an enhanced user experience. The integration…
Wireless End-to-End Image Transmission System using Semantic Communications
Maheshi Lokumarambage, Vishnu Gowrisetty, Hossein Rezaei +3
Semantic communication is considered the future of mobile communication, which aims to transmit data beyond Shannon's theorem of communications by transmitting the semantic meaning…
A Low Complexity Learning-based Channel Estimation for OFDM Systems with Online Training
Kai Mei, Jun Liu, Xiaoying Zhang +3
In this paper, we devise a highly efficient machine learning-based channel estimation for orthogonal frequency division multiplexing (OFDM) systems, in which the training of the es…
Deep Contextual Bandits for Fast Neighbor-Aided Initial Access in mmWave Cell-Free Networks
Insaf Ismath, Samad Ali, Nandana Rajatheva +1
Access points (APs) in millimeter-wave (mmWave) and sub-THz-based user-centric (UC) networks will have sleep mode functionality. As a result of this, it becomes challenging to solv…
Scoring the Terabit/s Goal:Broadband Connectivity in 6G
Nandana Rajatheva, Italo Atzeni, Simon Bicais +26
This paper explores the road to vastly improving the broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, with peak data rates up…
White Paper on Broadband Connectivity in 6G
Nandana Rajatheva, Italo Atzeni, Emil Bjornson +22
This white paper explores the road to implementing broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, from extreme capacity wit…
Performance Analysis on Machine Learning-Based Channel Estimation
Kai Mei, Jun Liu, Xiaochen Zhang +2
Recently, machine learning-based channel estimation has attracted much attention. The performance of machine learning-based estimation has been validated by simulation experiments.…
An Alternating Algorithm for Uplink Max-Min SINR in Cell-Free Massive MIMO with Local-MMSE Receiver
W. A. Chamalee Wickrama Arachchi, K. B. Shashika Manosha, N. Rajatheva +1
The problem of max-min signal-to-interference plus noise ratio (SINR) for uplink transmission of cell-free massive multiple-input multiple-output (MIMO) system is considered. We as…
Contextual Bandit Learning for Machine Type Communications in the Null Space of Multi-Antenna Systems
Samad Ali, Hossein Asgharimoghaddam, Nandana Rajatheva +2
In this paper, a novel approach based on the concept of opportunistic spatial orthogonalization (OSO) is proposed for interference management between machine type communications (M…
A Directed Information Learning Framework for Event-Driven M2M Traffic Prediction
Samad Ali, Walid Saad, Nandana Rajatheva
Burst of transmissions stemming from event-driven traffic in machine type communication (MTC) can lead to congestion of random access resources, packet collisions, and long delays.…
Infrastructure Sharing for Mobile Network Operators: Analysis of Trade-offs and Market
Tachporn Sanguanpuak, Sudarshan Guruacharya, Ekram Hossain +2
The conflicting problems of growing mobile service demand and underutilization of dedicated spectrum has given rise to a paradigm where mobile network operators (MNOs) share their…
Multi-Operator Spectrum Sharing for Small Cell Networks : A Matching Game Perspective
Tachporn Sanguanpuak, Sudarshan Guruacharya, Nandana Rajatheva +2
One of the many problems faced by current cellular network technology is the under utilization of the dedicated, licensed spectrum of network operators. An emerging paradigm to sol…