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.

AN ENERGY EFFICIENT SPECTRUM AWARE ROUTING FOR COGNITIVE RADIO NETWORKS

2019 ◽  
Vol 13 ◽  
Author(s):  
Dileep Reddy Bolla ◽  
Shivashankar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Multipath Fading ◽  
Spectrum Management ◽  
Radio Networks ◽  
Traffic Load ◽  
End To End Delay ◽  
End To End

Background: Now a days Due to rapid increase in the internet the Spectrum available is been overcrowded and thus the spectrum Sensing can be achieved by using the predominant technology i.e., Cognitive Radio as the spectrum is been under-utilized by the wireless communication technologies. Objective: The prime objective of the research work carried out is to achieve the energy efficiency and to use the spectrum effectively by using the spectrum management concept and achieve better throughput, end to end delay etc., Methods: The detection of the spectrum hole plays a vital role in the routing of the cognitive radio networks. As the hidden node problems and the multipath fading and the shadowing are considered to be impacting the sensing of the spectrum to overcome these issues Cooperative spectrum Sensing Mechanism is been adopted to sense the spectrum in an optimal manner and over cum the issues. Along with these issues the spectrum resources changes time to time in the routing. Result: An Energy Efficient Spectrum aware Routing (ESR) is been proposed which involves the timeslot and the routing schemes were been discussed. The simulation parameters have been proposed and the improvement in the performance of network through and a decrease in the end-to end delay have been observed and analyzed. Conclusion: An Energy Efficient spectrum management and the routing is successfully established to communication in the network and further traffic load is observed to be balanced in the protocol based on the residual energy in a node and further it prologs the Network Lifetime of the Overall Network and the Individual CR user. Further the end-to-end Delay has been observed to be lower which ensure higher throughput in the network and improves the network life time.

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.

An Energy Efficient Spectrum Aware Routing for Cognitive Radio Networks (CRNs)

2020 ◽  
Vol 10 ◽  
Author(s):  
Dileep Reddy Bolla ◽  
Jijesh J J ◽  
Mahaveer Penna ◽  
Shiva Shankar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Research Work ◽  
Spectrum Management ◽  
Residual Energy ◽  
Radio Networks ◽  
Traffic Load ◽  
The Impact

Back Ground/ Aims:: Now-a-days in the Wireless Communications some of the spectrum bands are underutilized or unutilized; the spectrum can be utilized properly by using the Cognitive Radio Techniques using the Spectrum Sensing mechanisms. Objectives:: The prime objective of the research work carried out is to achieve the energy efficiency and to use the spectrum effectively by using the spectrum management concept and achieve better throughput, end to end delay etc., Methods:: The detection of the spectrum hole plays a vital role in the routing of Cognitive Radio Networks (CRNs). While detecting the spectrum holes and the routing, sensing is impacted by the hidden node issues and exposed node issues. The impact of sensing is improved by incorporating the Cooperative Spectrum Sensing (CSS) techniques. Along with these issues the spectrum resources changes time to time in the routing. Results:: All the issues are addressed with An Energy Efficient Spectrum aware Routing (EESR) protocol which improves the timeslot and the routing schemes. The overall network life time is improved with the aid of residual energy concepts and the overall network performance is improved. Conclusion:: The proposed protocol (EESR) is an integrated system with spectrum management and the routing is successfully established to communication in the network and further traffic load is observed to be balanced in the protocol based on the residual energy in a node and further it improves the Network Lifetime of the Overall Network and the Individual CR user, along with this the performance of the proposed protocol outperforms the conventional state of art routing protocols.

scholarly journals Verifiably safe exploration for end-to-end reinforcement learning

2021 ◽  
Author(s):  
Nathan Hunt ◽  
Nathan Fulton ◽  
Sara Magliacane ◽  
Trong Nghia Hoang ◽  
Subhro Das ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
End To End
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