A Compatibility Vector Technique for Cooperative Scheduling and Channel Assignment Algorithm in Broadband Wireless Networks

Jayaraman, Ramkumar; Raja, Gunasekaran; Ghosal, Dipak; Arul, Rajakumar; A, Sabareesh Kumar

doi:10.1007/s11036-017-0841-x

Cited by 8 publications

(7 citation statements)

References 31 publications

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“…A nonstandalone mode is a way to add 5G new radio into an LTE network . The LTE RAN is used as a master eNB and provides control in signalling to establish and manage the connection with the devices.…”

Section: Deployment Of Ran In Hetnetsmentioning

confidence: 99%

An optimal multitier resource allocation of cloud RAN in 5G using machine learning

Bashir

Arul

Basheer

et al. 2019

Trans Emerging Tel Tech

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The networks are evolving drastically since last few years in order to meet user requirements. For example, the 5G is offering most of the available spectrum under one umbrella. In this work, we will address the resource allocation problem in fifth-generation (5G) networks, to be exact in the Cloud Radio Access Networks (C-RANs). The radio access network mechanisms involve multiple network topologies that are isolated based on the spectrum bands and it should be enhanced with numerous access technology in the deployment of 5G network. The C-RAN is one of the optimal technique to combine all the available spectral bands. However, existing C-RAN mechanisms lacks the intelligence perspective on choosing the spectral bands. Thus, C-RAN mechanism requires an advanced tool to identify network topology to allocate the network resources for substantial traffic volumes. Therefore, there is a need to propose a framework that handles spectral resources based on user requirements and network behavior. In this work, we introduced a new C-RAN architecture modified as multitier Heterogeneous Cloud Radio Access Networks in a 5G environment. This architecture handles spectral resources efficiently. Based on the simulation analysis, the proposed multitier H-CRAN architecture with improved control unit in network management perspective enables augmented granularity, end-to-end optimization, and guaranteed quality of service by 15 percentages over the existing system.Trans Emerging Tel Tech. 2019;30:e3627.wileyonlinelibrary.com/journal/ett spectrum like WiFi. 2 The advanced antennas with multiple input and multiple output technologies can be adopted in the evolving 5G to provide higher data rate. 3,4 The colossal requirements of future 5G networks cannot be accomplished by the existing radio access networks (RANs), wherein the base band units (BBUs) and radio units are consolidated. 2 Meanwhile, the cloud-enabled services in 5G ecosystem cater heterogeneous communication framework utilizing advanced virtualization techniques. The network virtualization stimulates multiservice and multitenancy for efficient network operations and service provisions, which, in turn, offers new-fangled service-oriented and edge-cloud 5G architectures with enhanced Quality of Experience (QoE). 5 Thus, the current RAN architectures need to be further extended with various virtualization techniques to develop Cloud RAN (C-RAN). Cloud RANs abutments the correlation of Access Points (APs) to the pool of BBU via a troop of transport links in the Control Unit (CU), 6 which conquers the limitations in the traditional RAN. 7 However, C-RAN requires an intelligent technique to recognize the topology of the network in the mobility stage and to locate the resources, as the vast traffic volume created by the sampled radio signals are directly transported to the CU. 8 The next-generation networks are expected to learn consistently based on the varied user behavior and spectral stability that depends on both the user's environment and network behavior. 9 Thereby, sea...

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Section: Deployment Of Ran In Hetnetsmentioning

confidence: 99%

An optimal multitier resource allocation of cloud RAN in 5G using machine learning

Bashir

Arul

Basheer

et al. 2019

Trans Emerging Tel Tech

Self Cite

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“…Social interactions are sorted based on behavioural activity to obtain frequent pattern based on semantic knowledge. In other aspects related to data mining, the data pattern is created, which helps for validation of the users [13] in networks [14].…”

Section: Related Workmentioning

confidence: 99%

Boolean Based Mining Algorithm for Pattern Discovery Based on Human Interaction

Ramanayagam¹,

Raja²,

Kannan³

2019

IJITEE

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Mining is a process that provides useful information on surfing and access pattern information based on capturing the behaviour of the user. Semantic knowledge helps to understand how the users will interact with the system. In this paper, we propose a Boolean based APriori Pattern (APP) algorithm to discover pattern based on human interaction using behavioural analysis. In the process of data mining, we have used a Boolean expression that helps to determine the pattern discovery based on the use of frequent pattern by applying association rules. The behavioural analysis is proposed based on the classification of ideas based on comments concerning positive opinion /contrary opinion during human interaction in the practical scenarios. The behavioural analysis is represented as a tree hierarchy where tree based mining is performed by the tree construction and interaction of flow patterns i.e., frequent patterns. The study shows that the successful pattern can be extracted based on the behavioural analysis of human interaction such as frequent pattern, flow interaction and relationships between the interactions.

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“…Interference node level (mi) [27,10] is defined here as the number of connected conflicting nodes to get interfering links and is represented in equation (1).…”

Section: Interference Node Level (Mi)mentioning

confidence: 99%

“…The underlying interference problems also lead to network disruption during establishment of multiple connections and degrade QoS. Various Channel Assignment (CA) schemes [9] [10] have contributed for identifying and mitigating the interferences in WMN. The conflict graph concept is commonly employed to address interference issues in WMN.…”

Section: Introductionmentioning

confidence: 99%

Interference Mitigation Based on Radio Aware Channel Assignment for Wireless Mesh Networks

Jayaraman

Raja

Chauhdary

et al. 2018

Wireless Pers Commun

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An intricate network deployment for high demand users leads to simultaneous transmission in wireless mesh networks. Multiple radios are adapted to individual nodes for improving network performance and Quality of Service (QoS). However, whenever multiple radios are assigned to the same channel, co-located radio interference occurs, which poses a major drawback. This paper proposes a Radio aware Channel Assignment (Ra-CA) mechanism based on a direct graphical model for mitigation of interference in multi-radio multi-channel networks. Initially, the co-located radio interference is identified by classifying non-interfering links for simultaneous transmission in the network. Proposed channel assignment mechanism helps in allocating the minimal number of channels to the network that mitigate co-located radio interference. Performance analysis of the proposed Ra-CA strategy is carried out compared with other existing techniques, like BFS-CA and MaIS-CA, in multi-radio networks. Simulation results demonstrate that the proposed channel assignment scheme is more efficient compared to the existing ones, in terms of QoS parameters like, packet drop rate, packet delivery ratio, transmission delay and throughput.

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A Compatibility Vector Technique for Cooperative Scheduling and Channel Assignment Algorithm in Broadband Wireless Networks

Cited by 8 publications

References 31 publications

An optimal multitier resource allocation of cloud RAN in 5G using machine learning

An optimal multitier resource allocation of cloud RAN in 5G using machine learning

Boolean Based Mining Algorithm for Pattern Discovery Based on Human Interaction

Interference Mitigation Based on Radio Aware Channel Assignment for Wireless Mesh Networks

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