Zobrazeno 1 - 10
of 1 665
pro vyhledávání: '"Kazemi,Mohammad"'
Autor:
Kazemi, Mohammad, Duman, Tolga M.
We develop bounds on the capacity of Poisson-repeat channels (PRCs) for which each input bit is independently repeated according to a Poisson distribution. The upper bounds are obtained by considering an auxiliary channel where the output lengths cor
Externí odkaz:
http://arxiv.org/abs/2410.02342
The sixth generation and beyond communication systems are expected to enable communications of a massive number of machine-type devices. The traffic generated by some of these devices will significantly deviate from those in conventional communicatio
Externí odkaz:
http://arxiv.org/abs/2409.14911
This paper considers an unsourced random access (URA) set-up equipped with a passive reconfigurable intelligent surface (RIS), where a massive number of unidentified users (only a small fraction of them being active at any given time) are connected t
Externí odkaz:
http://arxiv.org/abs/2408.13329
We investigate the unsourced random access scheme assuming that the base station is equipped with multiple antennas, and propose a high-performing solution utilizing on-off-division multiple access. We assume that each user spreads its pilot sequence
Externí odkaz:
http://arxiv.org/abs/2406.06284
We study the problem of unsourced random access (URA) over Rayleigh block-fading channels with a receiver equipped with multiple antennas. We propose a slotted structure with multiple stages of orthogonal pilots, each of which is randomly picked from
Externí odkaz:
http://arxiv.org/abs/2307.07310
Publikováno v:
In Expert Systems With Applications 1 January 2025 259
Autor:
Fazli, Ali, Kazemi, Mohammad Hosein
Publikováno v:
Industrial Robot: the international journal of robotics research and application, 2024, Vol. 51, Issue 2, pp. 246-257.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IR-07-2023-0142
We examine federated learning (FL) with over-the-air (OTA) aggregation, where mobile users (MUs) aim to reach a consensus on a global model with the help of a parameter server (PS) that aggregates the local gradients. In OTA FL, MUs train their model
Externí odkaz:
http://arxiv.org/abs/2207.09232
With the increase of digital data and social network platforms the impact of social media science in driving company decision related to product/service features and customer care operations is becoming more crucial. In particular, platform such as T
Externí odkaz:
http://arxiv.org/abs/2207.00816
We consider federated edge learning (FEEL) among mobile devices that harvest the required energy from their surroundings, and share their updates with the parameter server (PS) through a shared wireless channel. In particular, we consider energy harv
Externí odkaz:
http://arxiv.org/abs/2205.12869