Cooperation in 5G HetNets: Advanced Spectrum Access and D2D Assisted Communications

Tsiropoulos, Georgios I.; Yadav, Animesh; Zeng, Ming; Dobre, Octavia A.

doi:10.1109/mwc.2017.1700082

Cited by 71 publications

(32 citation statements)

References 13 publications

(14 reference statements)

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“…HetNets incorporates a bulk quantity of compactly deployed small cells such as femtocells, picocells, Relay Nodes (RNs), LTE, and WiFi APs . These small cells can serve both as indoor and outdoor UEs.…”

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

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“…The previously discussed technologies yield increased SE; however, they do not solve the problem of spectrum underutilization. The DSA technology provides a promising way that enables the use of underutilized frequency bands [8]. The DSA techniques broadly fall into two categories: i) cognitiveinspired radio access, which allows the secondary networks to use temporarily or spatially unoccupied bands without harmful interference to the primary networks; ii) cooperative-inspired radio access, where the primary networks allow spectrum sharing, trading, and leasing to the secondary networks with some economic favor.…”

Section: F Dynamic Spectrum Accessmentioning

confidence: 99%

All Technologies Work Together for Good: A Glance at Future Mobile Networks

Yadav

Dobre

2018

IEEE Wireless Commun.

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The astounding capacity requirements of 5G have motivated researchers to investigate the feasibility of many potential technologies, such as massive multiple-input multipleoutput, millimeter wave, full-duplex, non-orthogonal multiple access, carrier aggregation, cognitive radio, and network ultradensification. The benefits and challenges of these technologies have been thoroughly studied either individually or in a combination of two or three. It is not clear, however, whether all potential technologies operating together lead to fulfilling the requirements posed by 5G. This paper explores the potential benefits and challenges when all technologies coexist in an ultra-dense cellular environment. The sum rate of the network is investigated with respect to the increase in the number of small-cells and results show the capacity gains achieved by the coexistence.

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“…Future fifth-generation (5G) wireless networks are expected to be extremely heterogeneous in their architectures, allowing the coexistence of femtocell, microcell, and device-to-device (D2D) communications [ 1 , 2 , 3 , 4 ]. The development of conventional wireless networks into 5G wireless networks is driven by an incredible growth in wireless mobile devices, high data rates, high energy efficiency (EE), low latency, and improved quality of service [ 5 ]. To address these challenges, 5G wireless networks rely on some key technologies, such as full-duplex operation by users, network diversification, and D2D communications.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Power Allocation and Relay Selection Schemes for Relay-Assisted D2D Communications in 5G Wireless Networks

Rahman

Lee

Koo

2018

Sensors

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Device-to-device (D2D) communications allows user equipment (UE) that are in close proximity to communicate with each other directly without using a base station. Relay-assisted D2D (RA-D2D) communications in 5G networks can be applied to support long-distance users and to improve energy efficiency (EE) of the networks. In this paper, we first establish a multi-relay system model where the D2D UEs can communicate with each other by reusing only one cellular uplink resource. Then, we apply an adaptive neuro-fuzzy inference system (ANFIS) architecture to select the best D2D relay to forward D2D source information to the expected D2D destination. Efficient power allocation (PA) in the D2D source and the D2D relay are critical problems for operating such networks, since the data rate of the cellular uplink and the maximum transmission power of the system need to be satisfied. As is known, 5G wireless networks also aim for low energy consumption to better implement the Internet of Things (IoT). Consequently, in this paper, we also formulate a problem to find the optimal solutions for PA of the D2D source and the D2D relay in terms of maximizing the EE of RA-D2D communications to support applications in the emerging IoT. To solve the PA problems of RA-D2D communications, a particle swarm optimization algorithm is employed to maximize the EE of the RA-D2D communications while satisfying the transmission power constraints of the D2D users, minimum data rate of cellular uplink, and minimum signal-to-interference-plus-noise-ratio requirements of the D2D users. Simulation results reveal that the proposed relay selection and PA methods significantly improve EE more than existing schemes.

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Cooperation in 5G HetNets: Advanced Spectrum Access and D2D Assisted Communications

Cited by 71 publications

References 13 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

All Technologies Work Together for Good: A Glance at Future Mobile Networks

Energy-Efficient Power Allocation and Relay Selection Schemes for Relay-Assisted D2D Communications in 5G Wireless Networks

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