collaborators

11 papers

eess.SP2026

Computationally Efficient Neural Receivers via Axial Self-Attention

SaiKrishna Saketh Yellapragada, Atchutaram K. Kocharlakota, Mário Costa +2

The paper introduces an axial self‑attention transformer neural receiver that reduces computational complexity while achieving state‑of‑the‑art block error rate performance for wir…

math.ST2026

Nuisance parameters and elliptically symmetric distributions: a geometric approach to parametric and semiparametric efficiency

Stefano Fortunati, Jean-Pierre Delmas, Esa Ollila

The paper derives explicit formulas for the projection onto the nuisance tangent space in elliptically symmetric distribution models, enabling exact efficiency analysis for estimat…

cs.LG2026

Finer Parameter Steps for Low-Rank PEFT: A Controlled Study with CP Tensor Adapters

Xinjue Wang, Xiuheng Wang, Yejun Zhang +3

Low-rank adapters are usually compared by sweeping a small set of ranks, but the rank also fixes the resolution of the parameter budget. For a OPT attention proj…

cs.IT2026

Frequency Range 3 for ISAC in 6G: Potentials and Challenges

Gayan Aruma Baduge, Mojtaba Vaezi, Janith K. Dassanayake +3

Spanning 7-24 GHz, frequency range 3 (FR3), is a key enabler for next-generation wireless networks by bridging the coverage of sub-6 GHz and the capacity of millimeter-wave bands.…

eess.SP2026

Efficient Quantization-Aware Neural Receivers: Beyond Post-Training Quantization

SaiKrishna Saketh Yellapragada, Esa Ollila, Mario Costa

As wireless communication systems advance toward Sixth Generation (6G) Radio Access Networks (RAN), Deep Learning (DL)-based neural receivers are emerging as transformative solutio…

cs.IT2026

A Tutorial on AI-Empowered Integrated Sensing and Communications

Mojtaba Vaezi, Gayan Aruma Baduge, Esa Ollila +1

Integrating sensing and communication (ISAC) can help overcome the challenges of limited spectrum and expensive hardware, leading to improved energy and cost efficiency. While full…