This paper investigates over-the-air model aggregation for distributed reconfigurable intelligent surfaces (RISs)-assisted federated learning systems. Specifically, channel state information at the senors is assumed t...
详细信息
ISBN:
(数字)9781665455442
ISBN:
(纸本)9781665455442
This paper investigates over-the-air model aggregation for distributed reconfigurable intelligent surfaces (RISs)-assisted federated learning systems. Specifically, channel state information at the senors is assumed to be unavailable to avoid the overwhelming feedback overhead. With the objective of computation distortion minimization, we jointly optimize distributed RIS reflection matrices and the receiver beamforming, subject to the unit-modulus constraints imposed on the RIS reflection coefficients. In order to tackle this non-convex design problem, an alternating-based algorithm is proposed where, at every step, the RIS reflection matrices and the receiver beamforming are both obtained in closed forms. Numerical results validate the effectiveness of the proposed algorithm in reducing the aggregation error.
Massive MIMO systems have emerged as a promising technology for next-generation wireless communication networks. Beamforming, a key technique in Massive MIMO, significantly enhances the system's performance by exp...
详细信息
ISBN:
(纸本)9798350371000;9798350370997
Massive MIMO systems have emerged as a promising technology for next-generation wireless communication networks. Beamforming, a key technique in Massive MIMO, significantly enhances the system's performance by exploiting the spatial domain. This paper presents a collaborative beamforming approach that leverages vertical collaboration between base stations to improve adaptation and mitigate fading variations, while also applying the principle of free energy to optimize beamforming. The approach involves sharing estimated channel states and learned models among base stations, enabling them to collectively optimize beamforming based on the principle of free energy. Evaluations in single-user operation scenarios demonstrate that both with and without vertical collaboration, the expected free energy, representing beamforming performance, decreases over time. However, vertical collaboration reduces temporary decreases in signal-to-interference-plus-noise ratio (SINR) caused by independent adaptation to fading variations. Furthermore, in a multi-user switching scenario, the proposed approach ensures stable control by utilizing learned models and state estimation results, leading to improved beamforming performance during switching.
The rapid expansion of Wireless Sensor networks (WSNs) has made them a critical component in various applications, from environmental monitoring to military surveillance. However, their inherent vulnerabilities make t...
详细信息
作者：
Jia, ZiheXue, PengDai, ZhiqiangGao, QianZhang, Xiaomeng
Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250014 China
Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan250353 China Shandong Fundamental Research Center for Computer Science
Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China
The development of the Internet has made people more closely related and has put forward higher requirements for recommendation models. Most recommendation models are studied only for the long-term interests of users....
详细信息
distributed Denial Service of Service (DDoS) is very sophisticated attack which brute-force packet jamming to a network to render it useless, if done with large number of nodes. It can be easily countered by a number ...
详细信息
The population protocol model [3] offers a theoretical framework for designing and analyzing distributed algorithms among limited-resource mobile agents. While the original population protocol model considers the conc...
详细信息
In this paper, we explore the benefits of cooperative diversity for Wireless Sensor Network (WSN). Relays are uniformily distributed in L hops and N branches between the sensor nodes SN and the base station BS. Three ...
详细信息
We address the problem of Termination Detection (TD) in asynchronous networks. It is known that TD cannot be achieved in the context of self-stabilization, except in the specific case where the TD algorithm is snap-st...
详细信息
ISBN:
(纸本)9781665497534
We address the problem of Termination Detection (TD) in asynchronous networks. It is known that TD cannot be achieved in the context of self-stabilization, except in the specific case where the TD algorithm is snap-stabilizing, i.e., it always behaves according to its specification regardless of the initial configuration. In this paper, we propose a generic, deterministic, snap-stabilizing, silent algorithm that detects whether an observed terminating silent self-stabilizing algorithm, A, has converged to a configuration that satisfies an intended predicate. Our algorithm assumes that nodes know (an upper bound on) the network diameter D. However, it requires no underlying structure, nor specific topology (arbitrary network), and works in anonymous networks, i.e., our algorithm uses no kind of assumption allowing distinguishing one or more nodes. Furthermore, it works under the weakest scheduling assumptions a.k.a, the unfair daemon. Built over any asynchronous self-stabilizing underlying unison U, our solution adds only O(log D) bits per node. Since there exists no unison algorithm with better space complexity, the extra space of our solution is negligible w.r.t. the space complexity of the underlying unison algorithm. Our algorithm provides a positive answer in O(max(k, k', D)) time units, where k and k' are the stabilization time complexities of A and U, respectively.
Graph clustering is one of the key techniques to understand structures that are presented in networks. In addition to clusters, bridges and outliers detection is also a critical task as it plays an important role in t...
详细信息
Graph clustering is one of the key techniques to understand structures that are presented in networks. In addition to clusters, bridges and outliers detection is also a critical task as it plays an important role in the analysis of networks. Recently, several graph clustering methods are developed and used in multiple application domains such as biological network analysis, recommendation systems and community detection. Most of these algorithms are based on the structural clustering algorithm. Yet, this kind of algorithm is based on the structural similarity. This latter requires to parse all graph' edges in order to compute the structural similarity. However, the height needs of similarity computing make this algorithm more adequate for small graphs, without significant support to deal with large-scale networks. In this paper, we propose a novel distributed graph clustering algorithm based on structural graph clustering. The experimental results show the efficiency in terms of running time of the proposed algorithm in large networks compared to existing structural graph clustering methods. (c) 2022 Elsevier B.V. All rights reserved.
Cell clusters and networks that interconnect them are key components of emerging applications such as 6G wireless molecular communication systems, drug delivery and tissue regeneration. This paper discusses empirical,...
详细信息
暂无评论