Related papers: Distributed Spectrum-Aware Clustering in Cognitive…

This paper focuses on scalability and robustness of spectral clustering for extremely large-scale datasets with limited resources. Two novel algorithms are proposed, namely, ultra-scalable spectral clustering (U-SPEC) and ultra-scalable…

Due to the rapid demand for wireless services and the increase in the wireless device count, there is a lack of available spectrum bands which constrain the further development of wireless communication .Therefore, Cognitive Radio (CR) has…

A wireless sensor network has a wide application domain which is expanding everyday and they have been deployed pertaining to their application area. An application independent approach is yet to come to terms with the ongoing exploitation…

Balanced energy consumption is a major research concern in sensor networks. If some sensor nodes spent energy rapidly compared to other sensor groups, then the energy consumption is not evenly distributed and the lifetime of the network is…

With rapid developments of information and technology, large scale network data are ubiquitous. In this work we develop a distributed spectral clustering algorithm for community detection in large scale networks. To handle the problem, we…

In cognitive radio networks, spectrum sensing is a crucial technique to discover spectrum opportunities for the Secondary Users (SUs). The quality of spectrum sensing is evaluated by both sensing accuracy and sensing efficiency. Here,…

Distributed integrated sensing and communication (D-ISAC) enables multiple spatially distributed nodes to cooperatively perform sensing and communication. However, achieving coherent cooperation across distributed nodes is challenging due…

Spectral Clustering is a popular technique to split data points into groups, especially for complex datasets. The algorithms in the Spectral Clustering family typically consist of multiple separate stages (such as similarity matrix…

Developing an efficient spectrum access policy enables cognitive radios to dramatically increase spectrum utilization while ensuring predetermined quality of service levels for primary users. In this paper, modeling, performance analysis,…

Subspace clustering refers to the problem of clustering high-dimensional data into a union of low-dimensional subspaces. Current subspace clustering approaches are usually based on a two-stage framework. In the first stage, an affinity…

Spectral clustering is a leading clustering method. Two of its major shortcomings are the disjoint optimization process and the limited representation capacity. To address these issues, we propose a deep spectral clustering model (named…

An integrated sensing and backscatter communication (ISABC) system is introduced herein. This system features a full-duplex (FD) base station (BS) that seamlessly merges sensing with backscatter communication and supports multiple users.…

This paper studies a factor modeling-based approach for clustering high-dimensional data generated from a mixture of strongly correlated variables. Statistical modeling with correlated structures pervades modern applications in economics,…

To optimally cover users in millimeter-Wave (mmWave) networks, clustering is needed to identify the number and direction of beams. The mobility of users motivates the need for an online clustering scheme to maintain up-to-date beams towards…

In connected vehicular networks, it is vital to have vehicular nodes that are capable of sensing about surrounding environments and exchanging messages with each other for automating and coordinating purpose. Towards this end, integrated…

Extreme crowding of electromagnetic spectrum in recent years has led to the challenges in designing sensing and communications systems. Both systems require a broad range of bandwidth, thus resulting in competing interests in exploiting the…

Distributed consensus protocols provide a mechanism for spreading information within clustered networks, allowing agents and clusters to make decisions without requiring direct access to the state of the ensemble. In this work, we propose a…

Owing to the ever-increasing demand in wireless spectrum, Cognitive Radio (CR) was introduced as a technique to attain high spectral efficiency. As the number of secondary users (SUs) connecting to the cognitive radio network is on the…

This paper presents a new integrated sensing and communication (ISAC) framework, leveraging the recent advancements of reconfigurable distributed antenna and reflecting surface (RDARS). RDARS is a programmable surface structure comprising…

Shared spectrum systems facilitate spectrum allocation to unlicensed users without harming the licensed users; they offer great promise in optimizing spectrum utility, but their management (in particular, efficient spectrum allocation to…