Using UE-VBS for dynamic virtual small cells deployment and backhauling in 5G Ultra-Dense networks

2021 ◽  
Vol 189 ◽  
pp. 107926
Author(s):  
Kuna Venkateswararao ◽  
Pravati Swain ◽  
Christophoros Christophorou ◽  
Andreas Pitsillides
Keyword(s):  
Small Cells ◽  
Dense Networks

Energy-Efficient Mobility-Aware Caching Algorithms for Clustered Small Cells in Ultra-Dense Networks

2019 ◽  
Vol 68 (7) ◽  
pp. 6833-6846 ◽  
Author(s):  
Iman Keshavarzian ◽  
Zolfa Zeinalpour-Yazdi ◽  
Aliakbar Tadaion
Keyword(s):  
Energy Efficient ◽  
Small Cells ◽  
Dense Networks

Toward Scalable User-Deployed Ultra-Dense Networks: Blockchain-Enabled Small Cells as a Service

2020 ◽  
Vol 58 (8) ◽  
pp. 82-88 ◽  
Author(s):  
Emanuele Di Pascale ◽  
Hamed Ahmadi ◽  
Linda Doyle ◽  
Irene Macaluso
Keyword(s):  
Small Cells ◽  
Dense Networks

The Role of Massive MIMO and Small Cells in Ultra-dense Networks

2019 ◽  
pp. 113-133 ◽  
Author(s):  
Qi Zhang ◽  
Howard H. Yang ◽  
Tony Q. S. Quek
Keyword(s):  
Massive Mimo ◽  
Small Cells ◽  
Dense Networks

Adaptive Small Cells Clustering based on Many-to-Many Swap Matching for Ultra-Dense Networks

2019 ◽  
Author(s):  
Ning Chen ◽  
Siqiang Ke ◽  
Zhibin Gao ◽  
Hongyue Lin ◽  
Minghui Liwang ◽  
...  
Keyword(s):  
Small Cells ◽  
Dense Networks

scholarly journals Optimization of Unmanned Aerial Vehicle Augmented Ultra-Dense Networks

2020 ◽  
Author(s):  
Alireza Zamani ◽  
Robert Kämmer ◽  
Yulin Hu ◽  
Anke Schmeink
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Optimization Problem ◽  
Original Problem ◽  
Heuristic Method ◽  
Linear Structure ◽  
Small Cells ◽  
Simulation Studies ◽  
Dense Networks ◽  
Aerial Vehicle ◽  
Lower Complexity

Abstract In this paper, we study the integration of unmanned aerial vehicle small cells (UAV-SC) for the purpose of augmenting or temporarily restoring service to an ultra-dense cellular network. The aim is to minimize the overall power consumption of the network by jointly optimizing the number of UAV-SCs, their placement, associations and the power allocation, subject to user QoS, transmit power and fronthaul capacity constraints. As the resulting optimization problem is non-convex and computationally inefficient to solve, we investigate lower complexity alternatives. By reformulating the original problem, a linear structure can be obtained that is efficiently solved by off-the-shelf solvers. Furthermore, we also propose a meta-heuristic method that is based on particle swarm optimization. The performance of the proposed methods is evaluated via simulation studies and compared to state-of-the-art techniques. The results illustrate that the proposed methods consistently outperform conventional techniques by deploying fewer UAV-SCs and also lowering the transmit powers. Furthermore, considerable power savings were observed particularly for low QoS demands and dense scenarios.

scholarly journals The Impact of Heterogenous Ultra-dense Network Technologies on the Performance of 4G and 5GNetworks

2020 ◽  
Vol 10 (1) ◽  
pp. 35-44
Keyword(s):  
Cost Effective ◽  
Cellular System ◽  
Small Cells ◽  
High Expectations ◽  
Dense Networks ◽  
High Data ◽  
Data Rates ◽  
Network Technologies ◽  
The Impact

The flood of applications that demand massive data has imposed a challenge for 5G cellular network in order to deliver high data rates, a better quality of service, and low energy consumption. Heterogenous ultra- dense networks are one of the major technologies to address such challenges. HUDNs play a big role in a cellular system. They deliver cost-effective coverage with low transmit power and high capacty to face the risen data and the high expectations of the user's performance. In this paper, we introduce the impact of small cells on the cellular system and the technologies the small cells utilize to make the cellular system faces the subscriber's demands. First, we discuss the fundamentals of used technologies in small cells. Next, we studied the small cell management. Then, self-organizing networks are studied. After that, we have reviewed the small cell's power consumption, mobility, and handover. Finally, the real-world experience of mm-waves and MIMO in 5G small cells

scholarly journals Comparative Analysis of V-Band and E-Band mmWaves for Green Backhaul Solutions for 5G Ultra-Dense Networks

2021 ◽  
pp. 115-124
Author(s):  
Ayodeji A. Ajani ◽  
◽  
Vitalice K. Oduol ◽  
Zachaeus K. Adeyemo ◽  
Ebude C. Awasume
Keyword(s):  
Energy Efficiency ◽  
Comparative Analysis ◽  
Power Consumption ◽  
Energy Efficient ◽  
Small Cells ◽  
Network Simulator ◽  
Form Complex ◽  
Dense Networks ◽  
Wireless Backhaul ◽  
V Band

5G Ultra-Dense Networks (UDNs) will involve massive deployment of small cells which in turn form complex backhaul network. This backhaul network must be energy efficient for the 5G UDN network to be green. V-band and E-band mmWave technologies are among the wireless backhaul solutions tipped for 5G UDN. In this paper, we have compared the performance of the two backhaul solutions to determine which is more energy efficient for 5G UDN. We first formulated the problem to minimize power, then proposed an algorithm to solve the problem. This was then simulated using Network simulator 3.The first scenario made use of V-band mmWave while thesecond was E-band mmWave. The performance metricsused were power consumption and energy efficiency againstthe normalized hourly traffic profile. The performances ofthe two solutions were compared. The results revealed thatE-band mmWave outperformed V-band mmWave inbackhauling traffic in 5G UDN. It can be concluded that E-band green backhaul solution is recommended over V-bandmmWave for 5G UDN.

Dynamic Load Adjustments for Small Cells in Heterogeneous Ultra-dense Networks

2020 ◽  
Author(s):  
Qi Zhang ◽  
Xiaodong Xu ◽  
Jingxuan Zhang ◽  
Xiaofeng Tao ◽  
Cong Liu
Keyword(s):  
Dynamic Load ◽  
Small Cells ◽  
Dense Networks
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