scholarly journals Trading off Network Density with Frequency Spectrum for Resource Optimization in 5G Ultra-Dense Networks

Technologies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 114
Author(s):  
Georgios P. Koudouridis ◽  
Pablo Soldati
Keyword(s):  
Resource Management ◽  
Frequency Spectrum ◽  
Radio Resource Management ◽  
Spectrum Management ◽  
Traffic Load ◽  
Network Density ◽  
Management Problem ◽  
Dense Networks ◽  
New Radio ◽  
Duality Techniques

To effectively increase the capacity in 5G wireless networks requires more spectrum and denser network deployments. However, due to the increasing network density, the coordination of network and spectrum management becomes a challenging task both within a single operator’s network and among multiple operators’ networks. In this article, we develop new radio resource management (RRM) algorithms for adapting the frequency spectrum and the density of active access nodes in 5G ultra-dense networks (UDNs) to the traffic load and the user density in different geographical areas of the network. To this end, we formulate a network optimization problem where the allocation of spectrum bandwidth and the density of active access nodes are optimized to minimize a joint cost function, and we exploit Lagrange duality techniques to develop provably optimal network-scheduling algorithms. In particular, we develop density algorithms for two application scenarios. The first scenario solves the resource management problem for an operator of an ultra-dense network with exclusive access to a pool of frequency resources, while the second scenario applies to the management of the network density of collocated UDNs that belong to multiple operators sharing the same frequency spectrum. Simulation results demonstrate how effectively the algorithms can adapt the allocation of the spectrum allocation and the density of active access nodes over space and time.

Reinforcement Learning for Routing and Spectrum Management in Cognitive Wireless Mesh Network

2016 ◽  
Vol 5 (1) ◽  
pp. 59-72
Author(s):  
Ayoub Alsarhan
Keyword(s):  
Reinforcement Learning ◽  
Resource Management ◽  
Spectrum Management ◽  
Mesh Network ◽  
Traffic Load ◽  
Connection Admission Control ◽  
Main Concern ◽  
Load Spectrum ◽  
Management Scheme ◽  
End To End

Cognitive radio networks (CRNs) can provide a means for offering end-to-end Quality of Service (QoS) required by unlicensed users (secondary users. SUs). The authors consider the approach where licensed users (primary users, PUs) play the role of routers and lease spectrum with QoS guarantees for the SUs. Available spectrum is managed by the PU admission and routing policy. The main concern of the proposed policy is to provide end-to-end QoS connections to the SUs. Maximizing gain is the key objective for the PU. In this paper, the authors propose a novel resource management scheme where reinforcement learning (RL) is used to drive resource management scheme. The derived scheme helps PUs to adapt to the changes in the network conditions such as traffic load, spectrum cost, service reward, etc, so that PU's gain can continuously be optimized. The approach integrates spectrum adaptations with connection admission control and routing policies. Numerical analysis results show the ability of the proposed approach to attain the optimal gain under different conditions and constraints.

Management of 3.5-GHz Spectrum in 5G Dense Networks: A Hierarchical Radio Resource Management Scheme

2018 ◽  
Vol 13 (2) ◽  
pp. 57-64 ◽  
Author(s):  
Ioannis-Prodromos Belikaidis ◽  
Andreas Georgakopoulos ◽  
Evangelos Kosmatos ◽  
Valerio Frascolla ◽  
Panagiotis Demestichas
Keyword(s):  
Resource Management ◽  
Radio Resource Management ◽  
Radio Resource ◽  
Dense Networks ◽  
Management Scheme

Distributed Resources Management in Wireless LANs

2011 ◽  
pp. 293-304
Author(s):  
Ghassan Kbar ◽  
Wathiq Mansoor
Keyword(s):  
Resource Management ◽  
Large Scale ◽  
Radio Resource Management ◽  
Management Technique ◽  
Radio Resource ◽  
Distributed Resources ◽  
Dynamic Channel Assignment ◽  
Resources Management ◽  
New Radio ◽  
Dynamic Channel

This paper introduces a new radio resource management technique based on distributed dynamic channel assignment, and sharing load among Access Points (AP). Deploying wireless LANs (WLAN) on a large scale is mainly affected by reliability, availability and performance. These parameters will be a concern for most managers who want to deploy WLANs. In order to address these concerns, a new radio resource management technique can be used in a new generation of wireless LAN equipment. This technique would include distributed dynamic channel assignment, and load sharing among Access Points (AP), which improves the network availability and reliability compared to centralized management techniques. In addition, it will help to increase network capacities and improve performance, especially in large-scale WLANs. Analysis results using normal and binomial distribution have been included which indicate an improvement of performance resulting from network balancing when implementing distributed resources management at WLANs.

scholarly journals 5G New Radio: Dynamic Time Division Duplex Radio Resource Management Approaches

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
F. S. Samidi ◽  
N. A. M. Radzi ◽  
W. S. H. M. W. Ahmad ◽  
F. Abdullah ◽  
M. Z. Jamaludin ◽  
...  
Keyword(s):  
Resource Management ◽  
Radio Resource Management ◽  
Radio Resource ◽  
Time Division Duplex ◽  
New Radio ◽  
Management Approaches ◽  
Dynamic Time ◽  
Time Division

scholarly journals Dynamic resource management algorithms for interference prediction in 5G new radio scenarios

2021 ◽  
Author(s):  
Ismail ANGRI ◽  
Mohammed Mahfoudi ◽  
Abdellah Najid
Keyword(s):  
Resource Management ◽  
High Speed ◽  
Radio Resource Management ◽  
Interference Management ◽  
Scheduling Algorithms ◽  
New Radio ◽  
Radio Resources ◽  
Resource Management Algorithms ◽  
The Stability

Abstract Efficient Radio Resource Management is a key mechanism in interference management in 5G New Radio (NR) networks, specifically in the case of the presence of mobile users moving at high speed. To this end, the prediction and the evaluation of the propagation channel sensitivity requires that the radio resources allocation in NR must be efficient and powerful. Therefore, several scheduling algorithms have been developed and tested using the mmWave model of NS-3 simulator, with the aim of enhancing their contribution to improving the quality of the signal received by users. The performances have been evaluated in terms of Signal-to-Interference-and-Noise-Ratio (SINR) and signal Block Error Rate (BLER). The simulations were run for different types of data flows, and achieved satisfactory results for most schemes. The achievements clearly show the importance of scheduling algorithms in lowering received interference, but they have also demonstrated the stability and reliability of some of those strategies.

Agile Radio Resource Management Techniques for 5G New Radio

2017 ◽  
Vol 55 (6) ◽  
pp. 62-63 ◽  
Author(s):  
Athul Prasad ◽  
Anass Benjebbour ◽  
Omer Bulakci ◽  
Klaus I. Pedersen ◽  
Nuno K. Pratas ◽  
...  
Keyword(s):  
Resource Management ◽  
Radio Resource Management ◽  
Radio Resource ◽  
New Radio ◽  
Management Techniques
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