scholarly journals Performance Evaluation of Moving Small-Cell Network with Proactive Cache

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Young Min Kwon ◽  
Syed Tariq Shah ◽  
JaeSheung Shin ◽  
Ae-Soon Park ◽  
Min Young Chung
Keyword(s):  
Performance Evaluation ◽  
Mobile Network ◽  
Network Capacity ◽  
Small Cell ◽  
System Capacity ◽  
System Level ◽  
Small Cells ◽  
Data Traffic ◽  
Wireless Backhaul ◽  
Cell Network

Due to rapid growth in mobile traffic, mobile network operators (MNOs) are considering the deployment of moving small-cells (mSCs). mSC is a user-centric network which provides voice and data services during mobility. mSC can receive and forward data traffic via wireless backhaul and sidehaul links. In addition, due to the predictive nature of users demand, mSCs can proactively cache the predicted contents in off-peak-traffic periods. Due to these characteristics, MNOs consider mSCs as a cost-efficient solution to not only enhance the system capacity but also provide guaranteed quality of service (QoS) requirements to moving user equipment (UE) in peak-traffic periods. In this paper, we conduct extensive system level simulations to analyze the performance of mSCs with varying cache size and content popularity and their effect on wireless backhaul load. The performance evaluation confirms that the QoS of moving small-cell UE (mSUE) notably improves by using mSCs together with proactive caching. We also show that the effective use of proactive cache significantly reduces the wireless backhaul load and increases the overall network capacity.

scholarly journals Performance evaluation of wireless data traffic in Mm wave massive MIMO communication

2020 ◽  
Vol 20 (3) ◽  
pp. 1342
Author(s):  
Ahmed Thair Al-Heety ◽  
Mohammad Tariqul Islam ◽  
Ahmed Hashim Rashid ◽  
Hasanain N. Abd Ali ◽  
Ali Mohammed Fadil ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Network Capacity ◽  
System Capacity ◽  
Small Cells ◽  
Data Traffic ◽  
Wireless Data ◽  
Wireless Backhaul ◽  
Input Multiple Output

<span>Due to the evaluation of mobile devices and applications in the current decade, a new direction for wireless networks has emerged. The general consensus about the future 5G network is that the following should be taken into account; the purpose of thousand-fold system capacity, hundredfold energy efficiency, lower latency, and smooth connectivity. The massive multiple-input multiple-output (MIMO), as well as the Millimeter wave (mm Wave) have been considered in the ultra-dense cellular network (UDN), because they are viewed as the emergent solution for the next generations of communication. This article focuses on evaluating and discussing the performance of mm Wave massive MIMO for ultra-dense network, which is one of the major technologies for the 5G wireless network. More so, the energy efficiencies of two kinds of architectures for wireless backhaul networks were investigated and compared in this article. The results of the simulation revealed some points that should be considered during the deployment of small cells in the two architectures UDN with backhaul network capacity and backhaul energy efficiency, that the changing the frequency bands in Distribution approach gives the same energy efficiency reached to 600 Mb/s at 15 nodes while the Conventional approach results reached less than 100 Mb/s at the same number of nodes.</span>

scholarly journals Capacity Analysis and Optimization in Heterogeneous Network with Adaptive Cell Range Control

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xinyu Gu ◽  
Xin Deng ◽  
Qi Li ◽  
Lin Zhang ◽  
Wenyu Li
Keyword(s):  
Heterogeneous Network ◽  
Selection Procedure ◽  
Mobile Network ◽  
Network Capacity ◽  
Network Evolution ◽  
Range Extension ◽  
Traffic Load ◽  
System Level ◽  
Small Cells ◽  
Cell Range

As an attractive means of expanding mobile network capacity, heterogeneous network is regarded as an important direction of mobile network evolution. To increase the capacity of, for example, hot spots, a typical scenario in heterogeneous network is that the coverage areas of low power nodes (LPNs) are overlapped with macrocell. To increase the utilization of small cells generated by LPNs, cell range extension (CRE) is used to extend the coverage of the small cells by adding cell specific offset (CSO) to small cells during cell selection procedure. The value of CSO, however, needs to be set carefully. In this paper, the capacity of users in macrocells, users in small cells, and users in range extension areas is analyzed thoroughly in conditions with and without CRE. Based on the analysis, an adaptive CSO updating algorithm is proposed. The proposed algorithm updates the CSO value periodically by predicting the overall capacity and a new CSO value is selected which can give the optimal overall capacity. The proposed algorithm is evaluated by system-level simulations. Simulation results indicate that the proposed algorithm can ensure a nearly optimal performance in all tested traffic load situations.

scholarly journals Dual Connectivity in Heterogeneous Small Cell Networks with mmWave Backhauls

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Wooseong Kim
Keyword(s):  
Optimal Solution ◽  
Small Cell ◽  
Throughput Maximization ◽  
Small Cells ◽  
Network Access ◽  
Wireless Backhaul ◽  
Cell Network ◽  
Dual Connectivity ◽  
Macro Cell ◽  
User Data

Ultradense Network (UDN) with small cells is a key feature to begin a new era of 5G communication, which provides higher data rate, and accommodate explosive mobile traffic. Recently, mmWave-based wireless backhauls accelerate deployment of the UDN by reducing cost of fiber-optic cabling to small cells. The small cells can deliver user data to macro enhanced NodeBs (eNBs) using multihop relay in wireless backhaul mesh that consists of small and macro cell eNBs connected by the mmWave links. For such a heterogeneous small cell network (HetNet), 3GPP introduced dual connectivity (i.e., dual connections to macro and small cell eNBs), which is an attractive standard feature to manage user mobility and network access in the small cells. In this paper, we exploit dual connectivity scheme in a HetNet with the mmWave-based backhaul mesh which introduces two main challenges for throughput maximization, multihop routing from small to macro cell, and selection of a small cell eNB for user equipment (UE). We establish an optimization model and find an optimal solution in terms of throughput and fairness using an IBM CPLEX solver. Additionally, we propose a heuristic algorithm for complexity reduction and compare it with the optimal results in evaluation.

scholarly journals A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1493
Author(s):  
Ayesha Ayub ◽  
Sobia Jangsher ◽  
M. Majid Butt ◽  
Abdur Rahman Maud ◽  
Farrukh A. Bhatti
Keyword(s):  
Small Cell ◽  
Base Stations ◽  
Small Cells ◽  
Effective Capacity ◽  
Rate Enhancement ◽  
Cell Network ◽  
Small Cell Network ◽  
User Throughput ◽  
Average User ◽  
Cell Cooperation

Small cells deliver cost-effective capacity and coverage enhancement in a cellular network. In this work, we present the interplay of two technologies, namely Wi-Fi offloading and small-cell cooperation that help in achieving this goal. Both these technologies are also being considered for 5G and B5G (Beyond 5G). We simultaneously consider Wi-Fi offloading and small-cell cooperation to maximize average user throughput in the small-cell network. We propose two heuristic methods, namely Sequential Cooperative Rate Enhancement (SCRE) and Sequential Offloading Rate Enhancement (SORE) to demonstrate cooperation and Wi-Fi offloading, respectively. SCRE is based on cooperative communication in which a user data rate requirement is satisfied through association with multiple small-cell base stations (SBSs). However, SORE is based on Wi-Fi offloading, in which users are offloaded to the nearest Wi-Fi Access Point and use its leftover capacity when they are unable to satisfy their rate constraint from a single SBS. Moreover, we propose an algorithm to switch between the two schemes (cooperation and Wi-Fi offloading) to ensure maximum average user throughput in the network. This is called the Switching between Cooperation and Offloading (SCO) algorithm and it switches depending upon the network conditions. We analyze these algorithms under varying requirements of rate threshold, number of resource blocks and user density in the network. The results indicate that SCRE is more beneficial for a sparse network where it also delivers relatively higher average data rates to cell-edge users. On the other hand, SORE is more advantageous in a dense network provided sufficient leftover Wi-Fi capacity is available and more users are present in the Wi-Fi coverage area.

scholarly journals Macrocells-User Protected Interference-Aware Transmit Power Control for LTE-A Heterogeneous Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Arbab Waheed Ahmad ◽  
Heekwon Yang ◽  
Gul Shahzad ◽  
Chankil Lee
Keyword(s):  
Power Control ◽  
Heterogeneous Networks ◽  
Small Cell ◽  
System Level ◽  
Small Cells ◽  
Control Technique ◽  
Coverage Area ◽  
Current Channel ◽  
Transmit Power ◽  
Transmit Power Control

In Long Term Evolution-Advanced (LTE-A) heterogeneous networks (HetNets), small cells are deployed within the coverage area of macrocells having 1 : 1 frequency reuse. The coexistence of small cells and a macrocell in the same frequency band poses cross-tier interference which causes outage for macrocells users and/or small cell users. To address this problem, in this paper, we propose two algorithms that consider the received interference level at the evolved NodeB (eNB) while allocating transmit power to the users. In the proposed algorithm, the transmit power of all users is updated according to the target and instantaneous signal-to-noise-plus-interference ratio (SINR) condition as long as the effective received interference at the serving eNB is below the given threshold. Otherwise, if the effective received interference at the eNB is greater than the threshold, the transmit power of small cell users is gradually reduced in order to guarantee the target SINR for all macrocells users, aiming for zero-outage for macrocells users at the cost of an increased outage ratio for small cell users. Further, in the second algorithm, the transmit power of all users is additionally controlled by the power headroom report that considers the current channel condition while updating the transmit power which results in the outage ratio decreasing for small cell users. The extensive system-level simulations show significant improvements in the average throughput and outage ratio when compared with the conventional transmit power control technique.

Distributed Dynamic Resource Allocation for OFDMA-Based Cognitive Small Cell Networks Using a Regret-Matching Game Approach

2015 ◽  
pp. 230-253 ◽  
Author(s):  
Wei-Sheng Lai ◽  
Tsung-Hui Chang ◽  
Ta-Sung Lee
Keyword(s):  
Resource Allocation ◽  
Small Cell ◽  
Small Cells ◽  
Allocation Strategy ◽  
Small Cell Networks ◽  
Distributed Resource Allocation ◽  
Cell Network ◽  
Resource Allocation Strategy ◽  
Matching Game ◽  
Cell Networks

Game theoretical approaches have been used to develop distributed resource allocation technologies for cognitive heterogeneous networks. In this chapter, we present a novel distributed resource allocation strategy for cognitive small cell networks based on orthogonal frequency-division multiple access. In particular, we consider a heterogeneous network consisting of macrocell networks overlaid with cognitive small cells that opportunistically access the available spectrum. We focus on a regret-matching game approach, aiming at maximizing the total throughput of the small cell network subject to cross-tier interference and quality of service (QoS) constraints. The regret-matching game approach exploits a regret procedure to learn the optimal resource allocation strategy from the regrets of the actions of cognitive users. Furthermore, the regret-matching game approach is extended to the joint resource allocation and user admission control problem. Numerical results are presented to demonstrate the effectiveness of the proposed regre-matching approaches.

scholarly journals Countrywide Mobile Spectrum Sharing with Small Indoor Cells for Massive Spectral and Energy Efficiencies in 5G and Beyond Mobile Networks

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3825 ◽  
Author(s):  
Rony Kumer Saha
Keyword(s):  
Energy Efficiency ◽  
Mobile Networks ◽  
Spectral Efficiency ◽  
Spectrum Sharing ◽  
Performance Metrics ◽  
Interference Management ◽  
Mobile Network ◽  
System Level ◽  
Small Cells ◽  
Generic Model

In this paper, we propose a technique to share the licensed spectrums of all mobile network operators (MNOs) of a country with in-building small cells per MNO by exploiting the external wall penetration loss of a building and introducing the time-domain eICIC technique. The proposed technique considers allocating the dedicated spectrum Bop per MNO only its to outdoor macro UEs, whereas the total spectrum of all MNOs of the country Bco to its small cells indoor per building such that technically any small indoor cell of an MNO can have access to Bco instead of merely Bop assigned only to the MNO itself. We develop an interference management strategy as well as an algorithm for the proposed technique. System-level capacity, spectral efficiency, and energy efficiency performance metrics are derived, and a generic model for energy efficiency is presented. An optimal amount of small indoor cell density in terms of the number of buildings L carrying these small cells per MNO to trade-off the spectral efficiency and the energy efficiency is derived. With the system-level numerical and simulation results, we define an optimal value of L for a dense deployment of small indoor cells of an MNO and show that the proposed spectrum sharing technique can achieve massive indoor capacity, spectral efficiency, and energy efficiency for the MNO. Finally, we demonstrate that the proposed spectrum sharing technique could meet both the spectral efficiency and the energy efficiency requirements for 5G mobile networks for numerous traffic arrival rates to small indoor cells per building of an MNO.

scholarly journals Enhancing 5G Small Cell Selection: A Neural Network and IoV-Based Approach

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6361
Author(s):  
Ibtihal Ahmed Alablani ◽  
Mohammed Amer Arafah
Keyword(s):  
Neural Network ◽  
Los Angeles ◽  
Dwell Time ◽  
Selection Process ◽  
Small Cell ◽  
System Capacity ◽  
Small Cells ◽  
Cell Selection ◽  
Selection Scheme ◽  
Feed Forward Back Propagation

The ultra-dense network (UDN) is one of the key technologies in fifth generation (5G) networks. It is used to enhance the system capacity issue by deploying small cells at high density. In 5G UDNs, the cell selection process requires high computational complexity, so it is considered to be an open NP-hard problem. Internet of Vehicles (IoV) technology has become a new trend that aims to connect vehicles, people, infrastructure and networks to improve a transportation system. In this paper, we propose a machine-learning and IoV-based cell selection scheme called Artificial Neural Network Cell Selection (ANN-CS). It aims to select the small cell that has the longest dwell time. A feed-forward back-propagation ANN (FFBP-ANN) was trained to perform the selection task, based on moving vehicle information. Real datasets of vehicles and base stations (BSs), collected in Los Angeles, were used for training and evaluation purposes. Simulation results show that the trained ANN model has high accuracy, with a very low percentage of errors. In addition, the proposed ANN-CS decreases the handover rate by up to 33.33% and increases the dwell time by up to 15.47%, thereby minimizing the number of unsuccessful and unnecessary handovers (HOs). Furthermore, it led to an enhancement in terms of the downlink throughput achieved by vehicles.

Mobile Data Offloading for Streaming-Class Traffic with QoS Guarantee

2015 ◽  
Vol 7 (4) ◽  
pp. 26-42
Author(s):  
Anusree Ajith ◽  
T. G. Venkatesh
Keyword(s):  
Mobile Network ◽  
Network Capacity ◽  
Live Streaming ◽  
Data Traffic ◽  
Mobile Data ◽  
Qos Guarantee ◽  
Real Time Traffic ◽  
Video And Audio ◽  
Mobile Network Operators ◽  
Mobile Data Offloading

Faced with the tremendous increase in the amount of data traffic and associated congestion, mobile network operators are moving towards Heterogeneous networks (HetNets), in the process of expanding network capacity. Offloading data traffic onto Wi-Fi in order to avoid congestion in the backbone is an important step in the evolution of HetNets. On-the-spot and delayed offloading have been widely studied in the literature. This paper proposes an offloading algorithm which has low computational complexity. The proposed algorithm offloads data based on a balking function which is dependent on present network condition. Using extensive simulations, the authors demonstrate that the proposed algorithm achieves reduction in mean transmission delay without sacrificing much on the offloading efficiency. This technique is more efficient and applicable to real-time traffic, like live streaming video and audio, which has short and stringent delay requirements or deadlines.

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