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 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 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.

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 Performance measurement of small-cells deployed under a heterogeneous network: an analysis of the co-existence of small-cells with the macro‑cell in 5G NR

2021 ◽  
Author(s):  
Mobasshir Mahbub ◽  
Bobby Barua
Keyword(s):  
Mobile Networks ◽  
Heterogeneous Network ◽  
Power Efficiency ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
Small Cells ◽  
Macro Cell ◽  
Received Power ◽  
Implementation Costs

Abstract Advancements of cellular networks such as 4G and 5G proposed the collaboration of small-cell technologies in mobile networks and constructed a heterogeneous network (HetNet) for collaborative connectivity. There are many benefits of small-cell-based collective communication such as the increase of device capability in indoor/outdoor locations, enhancement of wireless coverage, improved signal efficiency, lower implementation costs of gNB (Next-generation Base Station introduced in 5G), etc. The integration of small-cells by deploying low-power BSs (base stations) in conventional macro-gNBs was investigated as a convenient and economical way of raising the potentials of a cellular network with high demand from consumers. The fusion of small-cells with macro-cells offers increased coverage and capacity for heterogeneous networks. Therefore, the research aimed to realize the performance of a small-cell deployed under a macro-cell in a two-tier heterogeneous network. The research first modified the reference equation for measuring the received power by introducing the transmitter and receiver gain. The paper then measured the SINR, throughput, spectral efficiency, and power efficiency for both downlink and uplink by empirical simulation. The research further enlisted the notable outcomes after examining the simulation results and discussed some relevant research scopes in the concluding sections of the paper.

scholarly journals Autonomous Transmission Power Decision Strategy for Energy Efficient Operation of a Dense Small Cell Network

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Jaesung Park ◽  
Heejung Byun
Keyword(s):  
Energy Efficiency ◽  
Power Control ◽  
Programming Problem ◽  
Energy Efficient ◽  
Small Cell ◽  
Small Cells ◽  
Noncooperative Game ◽  
Efficient Operation ◽  
Cell Network ◽  
Small Cell Network

Smart interference management methods are required to enhance the throughput, coverage, and energy efficiency of a dense small cell network. In this paper, we propose a transmit power control for energy efficient operation of a dense small cell network. We cast the power control problem as a noncooperative game to satisfy the design requirement that small cells do not need any information exchange among them. We analyze the sufficient condition for the existence of a Nash equilibrium (NE) state of the proposed game. We also analyze that the NE state is unique by transforming the original nonlinear fractional programming problem into a nonlinear parametric programming problem. Through simulation studies, we verify our analysis results. In addition, we show that the proposed method achieves higher energy efficiency of a network and balances the energy efficiency among cells more evenly than the methods based on the AIMD (additive increase and multiplicative decrease) algorithm.

scholarly journals Maximizing Average Sum Rate of Small Cells in 5G Ultra-dense Networks with Deployment Optimization

2020 ◽  
Author(s):  
Yihao Luo ◽  
Yang Yang ◽  
Long Zhang ◽  
Dazhong He ◽  
Jie Yang
Keyword(s):  
Closed Form ◽  
Simulation Analysis ◽  
Transmission Rate ◽  
Optimization Theory ◽  
Small Cell ◽  
Base Stations ◽  
Small Cells ◽  
Dense Networks ◽  
Macro Cell ◽  
Sum Rate

Abstract As the evolution of trends of intelligent IoT in 5G era, ultra-dense networks (UDN) become a promising paradigm via densely deploying small cells in cellular networks, where the transmission rate of mobile users can be highly improved. In this paper, an investigative study was presented regarding optimizing deployment of small cell base stations (BS) to maximize the average sum rate (ASR) in 5G UDN. In particular on a stochastic geometrical perspective, a homogeneous-type Poisson point process (PPP) was used for depicting an arbitrary arrangement of both macro cell user equipment (UE) and small cell BSs. Moreover, the closed-form probabilities of successful transmission was derived regarding the uplink and downlink of small cells. Then, the ASR of small cells was obtained as well as the problem of maximizing ASR was analyzed with outage constraints. Further, the study also demonstrated that the maximum ASR located in a closed interval of small cell BS density, where the lower and higher bounds of the interval were obtained. Finally, for maximizing the ASR value, the optimal small cell BS density in a closed-form was derived out with convex optimization theory. Simulation analysis indicated that different constraints from the macro cell network led to different maximum ASRs, and interferences caused by small cells and macro cell UE had likewise influenced the performance of small cells.

scholarly journals Joint Antenna Selection and Precoding Optimization for Small-Cell Network with Minimum Power Consumption

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Qiang Sun ◽  
Xin Wang ◽  
Jue Wang ◽  
Chen Xu
Keyword(s):  
Computational Complexity ◽  
Power Consumption ◽  
Antenna Selection ◽  
Minimum Mean Square Error ◽  
Optimization Algorithms ◽  
Optimal Solution ◽  
Small Cell ◽  
Cell Network ◽  
Small Cell Network ◽  
Circuit Power

We focus on the power consumption problem for a downlink multiuser small-cell network (SCN) considering both the quality of service (QoS) and power constraints. First based on a practical power consumption model taking into account both the dynamic transmit power and static circuit power, we formulate and then transform the power consumption optimization problem into a convex problem by using semidefinite relaxation (SDR) technique and obtain the optimal solution by the CVX tool. We further note that the SDR-based solution becomes infeasible for realistic implementation due to its heavy backhaul burden and computational complexity. To this end, we propose an alternative suboptimal algorithm which has low implementation overhead and complexity, based on minimum mean square error (MMSE) precoding. Furthermore, we propose a distributed correlation-based antenna selection (DCAS) algorithm combining with our optimization algorithms to reduce the static circuit power consumption for the SCN. Finally, simulation results demonstrate that our proposed suboptimal algorithm is very effective on power consumption minimization, with significantly reduced backhaul burden and computational complexity. Moreover, we show that our optimization algorithms with DCAS have less power consumption than the other benchmark algorithms.

Sign in / Sign up

Export Citation Format

Share Document