Zobrazeno 1 - 10
of 877
pro vyhledávání: '"P. Valkama"'
Autor:
Ge, Yu, Kaltiokallio, Ossi, Xia, Yuxuan, García-Fernández, Ángel F., Kim, Hyowon, Talvitie, Jukka, Valkama, Mikko, Wymeersch, Henk, Svensson, Lennart
Simultaneous localization and mapping (SLAM) methods need to both solve the data association (DA) problem and the joint estimation of the sensor trajectory and the map, conditioned on a DA. In this paper, we propose a novel integrated approach to sol
Externí odkaz:
http://arxiv.org/abs/2407.11643
Autor:
Koivunen, Visa, Keskin, Musa Furkan, Wymeersch, Henk, Valkama, Mikko, González-Prelcic, Nuria
This paper addresses the topic of integrated sensing and communications (ISAC) in 5G and emerging 6G wireless networks. ISAC systems operate within shared, congested or even contested spectrum, aiming to deliver high performance in both wireless comm
Externí odkaz:
http://arxiv.org/abs/2406.18476
Autor:
Klus, Roman, Talvitie, Jukka, Vinogradova, Julia, Fodor, Gabor, Torsner, Johan, Valkama, Mikko
Ensuring smooth mobility management while employing directional beamformed transmissions in 5G millimeter-wave networks calls for robust and accurate user equipment (UE) localization and tracking. In this article, we develop neural network-based posi
Externí odkaz:
http://arxiv.org/abs/2406.16519
Autor:
Bayraktar, Murat, González-Prelcic, Nuria, Valkama, Mikko, Chen, Hao, Zhang, Charlie Jianzhong
In this paper, we propose a hybrid precoding/combining framework for communication-centric integrated sensing and full-duplex (FD) communication operating at mmWave bands. The designed precoders and combiners enable multiuser (MU) FD communication wh
Externí odkaz:
http://arxiv.org/abs/2405.09079
Autor:
González-Prelcic, Nuria, Keskin, Musa Furkan, Kaltiokallio, Ossi, Valkama, Mikko, Dardari, Davide, Shen, Xiao, Shen, Yuan, Bayraktar, Murat, Wymeersch, Henk
Future wireless networks will integrate sensing, learning and communication to provide new services beyond communication and to become more resilient. Sensors at the network infrastructure, sensors on the user equipment, and the sensing capability of
Externí odkaz:
http://arxiv.org/abs/2405.01816
Deep SIMO Auto-Encoder and Radio Frequency Hardware Impairments Modeling for Physical Layer Security
This paper presents a novel approach to achieving secure wireless communication by leveraging the inherent characteristics of wireless channels through end-to-end learning using a single-input-multiple-output (SIMO) autoencoder (AE). To ensure a more
Externí odkaz:
http://arxiv.org/abs/2404.19463
Autor:
Kaltiokallio, Ossi, Rastorgueva-Foi, Elizaveta, Talvitie, Jukka, Ge, Yu, Wymeersch, Henk, Valkama, Mikko
The intrinsic geometric connections between millimeter-wave (mmWave) signals and the propagation environment can be leveraged for simultaneous localization and mapping (SLAM) in 5G and beyond networks. However, estimated channel parameters that are m
Externí odkaz:
http://arxiv.org/abs/2404.10291
The use of up to hundreds of antennas in massive multi-user (MU) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) poses a complexity challenge for digital predistortion (DPD) aiming to linearize the nonlinear po
Externí odkaz:
http://arxiv.org/abs/2402.16577
The Internet of Things (IoT) technology uses small and cost-effective sensors for various applications, such as Industrial IoT. However, these sensor nodes are powered by fixed-size batteries, which creates a trade-off between network performance and
Externí odkaz:
http://arxiv.org/abs/2401.00717
Autor:
Rastorgueva-Foi, Elizaveta, Kaltiokallio, Ossi, Ge, Yu, Turunen, Matias, Talvitie, Jukka, Tan, Bo, Keskin, Musa Furkan, Wymeersch, Henk, Valkama, Mikko
In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on end-to-end processing solutions, from raw I/Q samples, via channel parameter estimation to user equipment (UE) and l
Externí odkaz:
http://arxiv.org/abs/2312.13741