activity
20152026
most citedPolarBear: A 28-nm FD-SOI ASIC for Decoding of Polar Codes

50 citations · 65 across the 17 of their papers we have counts for

collaborators
Showing eess.SPShow all

15 papers · 1 filter

eess.SP2026

Centralized RAN for Future Low-Power Wide-Area Networks: A LoRa Case Study

Joachim Tapparel, Amavi Dossa, El Mehdi Amhoud +1

In recent years, low-power wide-area network (LPWAN) technologies have gained significant traction as a connectivity option for Internet of Things (IoT) applications. While these n…

eess.SP202510 cited

ComplexBeat: Breathing Rate Estimation from Complex CSI

Sitian Li, Andreas Toftegaard Kristensen, Andreas Burg +1

In this paper, we explore the use of channel state information (CSI) from a WiFi system to estimate the breathing rate of a person in a room. In order to extract WiFi CSI component…

eess.SP2025

Training Channel Selection for Learning-based 1-bit Precoding in Massive MU-MIMO

Sitian Li, Andreas Burg, Alexios Balatsoukas-Stimming

Learning-based algorithms have gained great popularity in communications since they often outperform even carefully engineered solutions by learning from training samples. In this…

eess.SP2021

On the Implementation Complexity of Digital Full-Duplex Self-Interference Cancellation

Andreas Toftegaard Kristensen, Alexios Balatsoukas-Stimming, Andreas Burg

In-band full-duplex systems promise to further increase the throughput of wireless systems, by simultaneously transmitting and receiving on the same frequency band. However, concur…

eess.SP2020

A Maximum-Likelihood-based Multi-User LoRa Receiver Implemented in GNU Radio

Mathieu Xhonneux, Joachim Tapparel, Orion Afisiadis +2

LoRa is a popular low-power wide-area network (LPWAN) technology that uses spread-spectrum to achieve long-range connectivity and resilience to noise and interference. For energy e…

eess.SP2020

On the Advantage of Coherent LoRa Detection in the Presence of Interference

Orion Afisiadis, Sitian Li, Andreas Burg +1

It has been shown that the coherent detection of LoRa signals only provides marginal gains of around 0.7 dB on the additive white Gaussian noise (AWGN) channel. However, ALOHA-base…