scholarly journals Cross-Entropy Method for Content Placement and User Association in Cache-Enabled Coordinated Ultra-Dense Networks

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 576 ◽  
Author(s):  
Jia Yu ◽  
Ye Wang ◽  
Shushi Gu ◽  
Qinyu Zhang ◽  
Siyun Chen ◽  
...  
Keyword(s):  
Mobile Communications ◽  
Network Throughput ◽  
Cross Entropy ◽  
Traffic Load ◽  
Small Cells ◽  
User Association ◽  
Cell Edge ◽  
Dense Networks ◽  
Cross Entropy Method ◽  
Content Placement

Due to the high splitting-gain of dense small cells, Ultra-Dense Network (UDN) is regarded as a promising networking technology to achieve high data rate and low latency in 5G mobile communications. In UDNs, each User Equipment (UE) may receive signals from multiple Base Stations (BSs), which impose severe interference in the networks and in turn motivates the possibility of using Coordinated Multi-Point (CoMP) transmissions to further enhance network capacity. In CoMP-based Ultra-Dense Networks, a great challenge is to tradeoff between the gain of network throughput and the worsening backhaul latency. Caching popular files on BSs has been identified as a promising method to reduce the backhaul traffic load. In this paper, we investigated content placement strategies and user association algorithms for the proactive caching ultra dense networks. The problem has been formulated to maximize network throughput of cell edge UEs under the consideration of backhaul load, which is a constrained non-convex combinatorial optimization problem. To decrease the complexity, the problem is decomposed into two suboptimal problems. We first solved the content placement algorithm based on the cross-entropy (CE) method to minimize the backhaul load of the network. Then, a user association algorithm based on the CE method was employed to pursue larger network throughput of cell edge UEs. Simulation were conducted to validate the performance of the proposed cross-entropy based schemes in terms of network throughput and backhaul load. The simulation results show that the proposed cross-entropy based content placement scheme significantly outperform the conventional random and Most Popular Content placement schemes, with with 50% and 20% backhaul load decrease respectively. Furthermore, the proposed cross-entropy based user association scheme can achieve 30% and 23% throughput gain, compared with the conventional N-best, No-CoMP, and Threshold based user association schemes.

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

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

Network Throughput and Outage Analysis in a Poisson and Matérn Cluster based LTE-Advanced Small Cell Networks

2021 ◽  
Author(s):  
Joydev Ghosh
Keyword(s):  
Outage Probability ◽  
Cell Formation ◽  
Access Network ◽  
Small Cell ◽  
Network Throughput ◽  
Base Stations ◽  
Small Cells ◽  
Network Cell ◽  
Lte Advanced ◽  
The Impact

<div>In LTE-A (LTE-Advanced), the access network cell formation is an integrated form of outdoor unit and indoor unit. With the indoor unit extension the access network becomes heterogeneous (HetNet). HetNet is a straightforward way to provide quality of service (QoS) in terms better network coverage and high data rate. Although, due to uncoordinated, densely deployed small cells large interference may occur, particularly in case of operating small cells within the spectrum of macro base stations (MBS). This paper probes the impact of small cell on the outage probability and the average network throughput enhancement. The positions of the small cells are retained random and modelled with homogeneous Poisson Point Process (PPP) and Matérn Cluster process (MCP). The paper provides an analytic form which permits to compute the outage probability, including the mostly applied fast fading channel types. Furthermore, simulations are evaluated in order to calculate the average network throughput for both random processes. Simulation results highlights that the network throughput remarkably grows due to small cell deployment.</div>

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 Resource Allocation for Energy Efficient User Association in User-Centric Ultra-Dense Networks Integrating NOMA and Beamforming

2020 ◽  
Author(s):  
Long Zhang ◽  
Guobin Zhang ◽  
Xiaofang Zhao ◽  
Yali Li ◽  
Chuntian Huang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Large Scale ◽  
Mixed Integer ◽  
Joint Optimization ◽  
User Association ◽  
Dual Decomposition ◽  
Dense Networks ◽  
Wireless Backhaul ◽  
User Centric

A coupling of wireless access via non-orthogonal multiple access and wireless backhaul via beamforming is a promising way for downlink user-centric ultra-dense networks (UDNs) to improve system performance. However, ultra-dense deployment of radio access points in macrocell and user-centric view of network design in UDNs raise important concerns about resource allocation and user association, among which notably is energy efficiency (EE) balance. To overcome this challenge, we develop a framework to investigate the resource allocation problem for energy efficient user association in such a scenario. The joint optimization framework aiming at the system EE maximization is formulated as a large-scale non-convex mixed-integer nonlinear programming problem, which is NP-hard to solve directly with lower complexity. Alternatively, taking advantages of sum-of-ratios decoupling and successive convex approximation methods, we transform the original problem into a series of convex optimization subproblems. Then we solve each subproblem through Lagrangian dual decomposition, and design an iterative algorithm in a distributed way that realizes the joint optimization of power allocation, sub-channel assignment, and user association simultaneously. Simulation results demonstrate the effectiveness and practicality of our proposed framework, which achieves the rapid convergence speed and ensures a beneficial improvement of system-wide EE.<br>

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