activity
20242026
collaborators

8 papers

eess.SP2026

Distributed Massive MIMO with 1-Bit Radio-over-Fiber Fronthaul: Uplink Spectral Efficiency and Power Control

Alireza Bordbar, Anzhong Hu, Giuseppe Durisi

We analyze the uplink spectral efficiency achievable in a distributed multiple-input multiple-output (D-MIMO) architecture employing a 1-bit radio-over-fiber fronthaul. This archit…

cs.IT2026

Minimum Energy per Bit of Unsourced Multiple Access with Location-Based Codebook Partitioning

Deekshith Pathayappilly Krishnan, Kaan Okumus, Khac-Hoang Ngo +1

We derive finite-blocklength bounds on the minimum achievable energy per bit over a Gaussian unsourced multiple access (UMA) channel in the presence of heterogeneous path-loss cond…

cs.IT2026

Type-Based Unsourced Multiple Access Over Fading Channels in Distributed MIMO With Application to Multi-Target Localization

Kaan Okumus, Khac-Hoang Ngo, Giuseppe Durisi +2

We consider the problem of type estimation over unsourced multiple access fading channels in distributed multiple-input multiple-output (D-MIMO) systems. Unlike classical unsourced…

cs.IT2026

Type-Based Unsourced Federated Learning With Client Self-Selection

Kaan Okumus, Khac-Hoang Ngo, Unnikrishnan Kunnath Ganesan +3

We address the client-selection problem in federated learning over wireless networks under data heterogeneity. Existing client-selection methods often rely on server-side knowledge…

cs.IT2025

Prediction-Powered Communication with Distortion Guarantees

Matteo Zecchin, Unnikrishnan Kunnath Ganesan, Giuseppe Durisi +2

The development of 6G wireless systems is taking place alongside the development of increasingly intelligent wireless devices and network nodes. The changing technological landscap…

cs.IT2025

Online Conformal Compression for Zero-Delay Communication with Distortion Guarantees

Unnikrishnan Kunnath Ganesan, Giuseppe Durisi, Matteo Zecchin +2

We investigate a lossy source compression problem in which both the encoder and decoder are equipped with a pre-trained sequence predictor. We propose an online lossy compression s…