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Deep Reinforcement Learning (DRL) has emerged as a powerful solution for meeting the growing demands for connectivity, reliability, low latency and operational efficiency in advanced networks. However, most research has focused on…
Achievable degrees-of-freedom (DoF) of the large-scale interfering two-way relay network is investigated. The network consists of $K$ pairs of communication nodes (CNs) and $N$ relay nodes (RNs). It is assumed that $K\ll N$ and each pair of…
The objective of this analysis was to simulate the performance of three different ad-hoc protocols for disruption-tolerant networking (DTN) - i.e. the transfer of information through a network of nodes in contexts prone to signal…
We present a novel multi-agent RL approach, Selective Multi-Agent Prioritized Experience Relay, in which agents share with other agents a limited number of transitions they observe during training. The intuition behind this is that even a…
In this work, a delay-tolerant unmanned aerial vehicle (UAV) relayed covert and secure communication framework is investigated. In this framework, a legitimate UAV serves as an aerial relay to realize communication when the direct link…
In the first part of this paper we have derived achievable transmission rates for the (single-band) interference relay channel (IRC) when the relay implements either the amplify-and-forward, decode-and-forward or estimate-and-forward…
In this paper, we consider a general distributed estimation problem in relay-assisted sensor networks by taking into account time-varying asymmetric communications, fading channels and intermittent measurements. Motivated by centralized…
We argue that Time-Sensitive Networking (TSN) will become the de facto standard for real-time communications in robotics. We present a review and classification of the different communication standards which are relevant for the field and…
Distributed resource allocation (DRA) is fundamental to modern networked systems, spanning applications from economic dispatch in smart grids to CPU scheduling in data centers. Conventional DRA approaches require reliable communication, yet…
Massive Machine-Type Communications (MTC) over cellular networks is expected to be an integral part of wireless "Smart City" applications. The Long Term Evolution (LTE)/LTE-Advanced (LTE-A) technology is a major candidate for provisioning…
Wireless technologies can support a broad range of smart grid applications including advanced metering infrastructure (AMI) and demand response (DR). However, there are many formidable challenges when wireless technologies are applied to…
Network Virtualization is one of the key technologies for developing the future mobile networks. However, the performance of virtual mobile entities may not be sufficient for delivering the service required for future networks in terms of…
Interference evaluation is crucial when deciding whether and how wireless technologies should operate. In this paper we demonstrate the benefit of risk-informed interference assessment to aid spectrum regulators in making decisions, and to…
In this paper, we study a multi-user multi-relay interference-channel network, where energy-constrained relays harvest energy from sources' radio frequency (RF) signals and use the harvested energy to forward the information to…
A wide range of multi-agent coordination problems including reference tracking and disturbance rejection requirements can be formulated as a cooperative output regulation problem. The general framework captures typical problems such as…
A key feature of the packet scheduler in LTE system is that it can allocate resources both in the time and frequency domain. Furthermore, the scheduler is acquainted with channel state information periodically reported by user equipments…
IoT devices have become an integral part of our lives and the industry. Many of these devices run real-time systems or are used as part of them. As these devices receive network packets over IP networks, the network interface informs the…
A two-phase beamforming solution for secure communication using untrusted relay nodes is presented. To thwart eavesdropping attempts of relay nodes, we deliberately introduce artificial noise in the source message. After pointing out the…
Recurrent neural networks (RNNs) are commonly applied to clinical time-series data with the goal of learning patient risk stratification models. Their effectiveness is due, in part, to their use of parameter sharing over time (i.e., cells…
Deploying sensor nodes randomly most of the time generates initial communication hole even in highly dense networks. These communication holes cannot be totally eliminated even when the deployment is done in a structured manner. In either…