Related papers: Stochastic Event-based Sensor Schedules for Remote…
Distributed consensus has been widely studied for sensor network applications. Whereas the asymptotic convergence rate has been extensively explored in prior work, other important and practical issues, including energy efficiency and link…
Network slicing is a proposing technology to support diverse services from mobile users (MUs) over a common physical network infrastructure. In this paper, we consider radio access network (RAN)-only slicing, where the physical RAN is…
In this paper, we study and analyze cognitive radio networks in which secondary users (SUs) are equipped with Energy Harvesting (EH) capability. We design a random spectrum sensing and access protocol for the SU that exploits the primary…
In this paper, we present a framework for distributively optimizing the transmission strategies of secondary users in an ad hoc cognitive radio network. In particular, the proposed approach allows secondary users to set their transmit…
The paper considers constrained linear systems with stochastic additive disturbances and noisy measurements transmitted over a lossy communication channel. We propose a model predictive control (MPC) law that minimizes a discounted cost…
The task of state estimation in active distribution systems faces a major challenge due to the integration of different measurements with multiple reporting rates. As a result, distribution systems are essentially unobservable in real time,…
In this work we study energy-efficient transmission for Cognitive Radio (CR) which opportunistically operates on Primary User's (PU's) channel through spectrum sensing. Spectrum sensing and compulsory idling (for incumbent protection)…
Unmanned aerial vehicles (UAVs) can provide wireless access services to terrestrial users without geographical limitations and will become an essential part of the future communication system. However, the openness of wireless channels and…
We propose a new framework for cooperative spectrum sensing in cognitive radio networks, that is based on a novel class of non-uniform samplers, called the event-triggered samplers, and sequential detection. In the proposed scheme, each…
This paper is concerned with developing a novel distributed Kalman filtering algorithm over wireless sensor networks based on randomized consensus strategy. Compared with the centralized algorithm, distributed filtering techniques require…
We study distributed estimation of a high-dimensional static parameter vector through a group of sensors whose communication network is modeled by a fixed directed graph. Different from existing time-triggered communication schemes, an…
For a wireless sensor network (WSN) with a large number of low-cost, battery-driven, multiple transmission power leveled sensor nodes of limited transmission bandwidth, then conservation of transmission resources (power and bandwidth) is of…
In this paper, a sequential probing method for interference constraint learning is proposed to allow a centralized Cognitive Radio Network (CRN) accessing the frequency band of a Primary User (PU) in an underlay cognitive scenario with a…
In this paper, we investigate the resource allocation design for integrated sensing and communication (ISAC) in distributed antenna networks (DANs). In particular, coordinated by a central processor (CP), a set of remote radio heads (RRHs)…
This paper considers a spectrum sharing based cognitive radio (CR) communication system, which consists of a secondary user (SU) having multiple transmit antennas and a single receive antenna and a primary user (PU) having a single receive…
This paper presents a complete design, analysis, and performance evaluation of a novel distributed event-triggered control and estimation strategy for DC microgrids. The primary objective of this work is to efficiently stabilize the grid…
We propose a provably stabilizing and tractable approach for control of constrained linear systems under intermittent observations and unreliable transmissions of control commands. A smart sensor equipped with a Kalman filter is employed…
This paper introduces a stochastic hybrid system (SHS) framework in state space model to capture sensor, communication, and system contingencies in modern power systems (MPS). Within this new framework, the paper concentrates on the…
We study a remote estimation setup with an autoregressive (AR) Markov process, a sensor, and a remote estimator. The sensor observes the process and sends encoded observations to the estimator as packets over an unreliable communication…
The robust distributed state estimation for a class of continuous-time linear time-invariant systems is achieved by a novel kernel-based distributed observer, which, for the first time, ensures fixed-time convergence properties. The…