Related papers: New Architecture for Dynamic Spectrum Allocation i…
An important issue in heterogeneous wireless networks is how to optimally utilize various radio resources. While many methods have been proposed for managing radio resources in each network, these methods are not suitable for heterogeneous…
Interference coupling in heterogeneous networks introduces the inherent non-convexity to the network resource optimization problem, hindering the development of effective solutions. A new framework based on multi-pattern formulation has…
Modern artificial intelligence relies on networks of agents that collect data, process information, and exchange it with neighbors to collaboratively solve optimization and learning problems. This article introduces a novel distributed…
Based on the theory of the Federal Communications Commission, the spectrum available on cognitive radio networks is limit and the non-optimal use of the spectrum necessitates the need for a telecommunications model, so that this pattern can…
Dynamic spectrum sharing approach is a paradigm shift from the conventional static and exclusive approach to spectrum allocation. The existing methodologies to define use of the spectrum and quantify its efficiency are based on the static…
Dynamic spectrum access allows the unlicensed wireless users (secondary users) to dynamically access the licensed bands from legacy spectrum holders (primary users) either on an opportunistic or a cooperative basis. In this paper, we focus…
We consider a downlink multiuser massive MIMO system comprising multiple heterogeneous base stations with hybrid precoding architectures. To enhance the energy efficiency of the network, we propose a novel coordinated hybrid precoding…
This work presents joint iterative power allocation and interference suppression algorithms for spread spectrum networks which employ multiple hops and the amplify-and-forward cooperation strategy for both the uplink and the downlink. We…
In this paper, we employ deep reinforcement learning to develop a novel radio resource allocation and packet scheduling scheme for different Quality of Service (QoS) requirements applicable to LTEadvanced and 5G networks. In addition,…
In order to meet the constantly increasing demand by mobile terminals for higher data rates with limited wireless spectrum resource, cognitive radio and spectrum aggregation technologies have attracted much attention due to its capacity in…
We introduce hierarchical neighbor graphs, a new architecture for connecting ad hoc wireless nodes distributed in a plane. The structure has the flavor of hierarchical clustering and requires only local knowledge and minimal computation at…
This research introduces a revolutionary paradigm for HetNet management, presenting an innovative algorithmic framework that transcends traditional notions of network capacity enhancement. Our exploration delves into the intricate interplay…
Faced with increasing network traffic demands, cell dense deployment is one of significant means to utilize spectrum resources efficiently to improve network capacity. Multi-hop integrated access and backhaul (IAB) architectures have…
In this paper, a novel cluster-based approach for optimizing the energy efficiency of wireless small cell networks is proposed. A dynamic mechanism based on the spectral clustering technique is proposed to dynamically form clusters of small…
In this paper, a new cooperation structure for spectrum sensing in cognitive radio networks is proposed which outperforms the existing commonly-used ones in terms of energy efficiency. The efficiency is achieved in the proposed design by…
When implementing hierarchical federated learning over wireless networks, scalability assurance and the ability to handle both interference and device data heterogeneity are crucial. This work introduces a learning method designed to…
This article explores the design and experimentation of a neural network architecture capable of dynamically adjusting its internal structure based on the input data. The proposed model introduces a routing mechanism that allows each layer…
This study focusses on self-balancing microgrids to smartly utilize and prevent overdrawing of available power capacity of the grid. A distributed framework for automated distribution of optimal power demand is proposed, where all building…
In this paper, we present a hierarchical framework that integrates upper-level routing with low-level optimal trajectory planning for connected and automated vehicles (CAVs) traveling in an urban network. The upper-level controller…
In the past few years, DRL has become a valuable solution to automatically learn efficient resource management strategies in complex networks with time-varying statistics. However, the increased complexity of 5G and Beyond networks requires…