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…a technique to reduce the total energy bill at the edge device by utilizing model compression and time-varying model split between the edge and remote nodes. The time-varying representation accounts…
…blends with polyhydroxybutyrate (PHB) and composites with pyrolyzed lignin (PL), and multiwalled carbon nanotubes (MWCNTs), in conjunction with processes typical in the fabrication of electronics components, including plasma treatment, dip…
…flock requires a huge inter-UAV communication which is impossible to implement in real-time applications. One method of control is to apply the mean field game (MFG) framework which substantially reduces…
This paper presents a synthesis flow for building lumped circuit models of arbitrary complexity for mm-wave IC passive components, based on S-parameters obtained by measurements or electromagnetic (EM) field simulations….
Industrial wireless networks are pushing towards distributed architectures moving beyond traditional server-client transactions. Paired with this trend, new synergies are emerging among sensing, communications and Machine Learning (ML) co-design, where…
…sickness (and thereby maximize comfort). An A* type method is used to create a Pareto-optimal collection of piecewise linear trajectories while taking into account criteria that improve comfort. We conducted…
Scheduling fast uplink grant transmissions for machine type communications (MTCs) is one of the main challenges of future wireless systems. In this paper, a novel fast uplink grant scheduling method…
In this article, a compact printed monopole dual-band antenna using artificial magnetic conductor (AMC)-plane with improved gain and broader bandwidth, applicable for off-body internet of things (IoT) devices is presented….
The Finnish Ministry of Transport and Communications has established a working group to advance 6G communication technologies. The group’s primary focus is to develop a national 6G roadmap for Finland…
Patch-based sparse representation modeling has shown great potential in image compressive sensing (CS) reconstruction. However, this model usually suffers from some limits, such as dictionary learning with great computational complexity,…