…and healthcare services in a contact-less manner. The edge computing paradigms offer a de-centralized and versatile networking infrastructure capable of adhering to the novel demands of 5G. In this article,…
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…
In this article, we propose a communication-efficient decentralized machine learning (ML) algorithm, coined quantized group ADMM (Q-GADMM) . To reduce the number of communication links, every worker in Q-GADMM communicates…
The 3GPP standardization body is actively investigating the requirements and specifying the radio access interface of 5G new radio (NR) systems to support satellite communications. However, the 5G NR was…
…propose a network slice communication service distribution technique for local 5G micro-operator deployment scenarios. This is achieved by expanding/leveraging the communication service management function (CSMF) defined by 3GPP into a…
Cellular networks are expected to be the main communication infrastructure to support the expanding applications of Unmanned Aerial Vehicles (UAVs). As these networks are deployed to serve ground User Equipment…
Ceramic (Ba0.55 Sr0.45 Ti1.01 O3 ) – polypropylene polymer ER182 composites‐based materials were applied for sub‐THz range antenna lens application in telecommunications. Typical plano‐convex ‐shaped lenses were simulated and measured…
…a set of IoT devices by only relying on the first-order statistics of the channels. In addition to low complexity, the proposed scheme performs favorably as compared to benchmarking schemes…
…the information signals are often continuous-valued, digital communication of compressive measurements requires quantization. In such a quantized compressed sensing (QCS) context, we address remote acquisition of a sparse source through…
This paper introduces a simple approach combining deep learning and histogram contour processing for automatic detection of various types of artifact contaminating the raw electroencephalogram (EEG). The proposed method considers…