Energy Efficiency with Adaptive Decoding Power and Wireless Backhaul Small Cell Selection

2016 ◽  
Author(s):  
Tri Minh Nguyen ◽  
Animesh Yadav ◽  
Wessam Ajib ◽  
Chadi Assi
Keyword(s):  
Energy Efficiency ◽  
Small Cell ◽  
Cell Selection ◽  
Wireless Backhaul ◽  
Adaptive Decoding

Energy Efficiency Optimization in LTE-U Based Small Cell Networks

2019 ◽  
Vol 68 (2) ◽  
pp. 1963-1967 ◽  
Author(s):  
Rui Yin ◽  
Yunfeng Zhang ◽  
Fang Dong ◽  
Anding Wang ◽  
Chau Yuen
Keyword(s):  
Energy Efficiency ◽  
Small Cell ◽  
Small Cell Networks ◽  
Efficiency Optimization ◽  
Cell Networks

scholarly journals Energy performance of 5G backhaul wireless network utilizing hybrid centric-distributed architecture

2019 ◽  
Vol 16 (3) ◽  
pp. 1343
Author(s):  
Hamza Mohammed Ridha Al-Khafaji ◽  
Hasan Shakir Majdi
Keyword(s):  
Energy Efficiency ◽  
Wireless Network ◽  
Network Architecture ◽  
Energy Performance ◽  
Small Cells ◽  
Network Architectures ◽  
Distributed Architecture ◽  
Wireless Backhaul ◽  
Fifth Generation ◽  
5G Network

<p>This paper scrutinizes the influence of deployment scenarios on the energy performance of fifth-generation (5G) network at various backhaul wireless frequency bands. An innovative network architecture, the hybrid centric-distributed, is employed and its energy efficiency (EE) model is analyzed. The obtained results confirm that the EE of the 5G network increases with an increasing number of small cells and degrades with an increasing frequency of wireless backhaul and radius of small cells regardless of the network architectures. Moreover, the hybrid centric-distributed architecture augments the EE when compared with the distributed architecture.</p>

scholarly journals Energy Efficiency Maximization of Dynamic CoMP-JT Algorithm in Dense Small Cell Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Xuefei Peng ◽  
Jiandong Li ◽  
Yifei Xu
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Optimal Solution ◽  
Small Cell ◽  
Base Stations ◽  
Maximization Problem ◽  
Second Phase ◽  
User Association ◽  
Coordinated Multipoint ◽  
Convex Problem

We firstly formulate the energy efficiency (EE) maximization problem of joint user association and power allocation considering minimum data rate requirement of small cell users (SUEs) and maximum transmit power constraint of small cell base stations (SBSs), which is NP-hard. Then, we propose a dynamic coordinated multipoint joint transmission (CoMP-JT) algorithm to improve EE. In the first phase, SUEs are associated with the SBSs close to them to reduce the loss of power by the proposed user association algorithm, where the associated SBSs of each small cell user (SUE) form a dynamic CoMP-JT set. In the second phase, through the methods of fractional programming and successive convex approximation, we transform the EE maximization subproblem of power allocation for SBSs into a convex problem that can be solved by proposed power allocation optimization algorithm. Moreover, we show that the proposed solution has a much lower computational complexity than that of the optimal solution obtained by exhaustive search. Simulation results demonstrate that the proposed solution has a better performance.

scholarly journals Coexistence of Cognitive Small Cell and WiFi System: A Traffic Balancing Dual-Access Resource Allocation Scheme

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Xiaoge Huang ◽  
Yangyang Li ◽  
She Tang ◽  
Qianbin Chen
Keyword(s):  
Power Allocation ◽  
Optimization Problems ◽  
Holistic Approach ◽  
Data Rate ◽  
Small Cell ◽  
Dual Band ◽  
Cell Selection ◽  
Allocation Scheme ◽  
Traffic Balancing ◽  
Unlicensed Bands

We consider a holistic approach for dual-access cognitive small cell (DACS) networks, which uses the LTE air interface in both licensed and unlicensed bands. In the licensed band, we consider a sensing-based power allocation scheme to maximize the sum data rate of DACSs by jointly optimizing the cell selection, the sensing operation, and the power allocation under the interference constraint to macrocell users. Due to intercell interference and the integer nature of the cell selection, the resulting optimization problems lead to a nonconvex integer programming. We reformulate the problem to a nonconvex power allocation game and find the relaxed equilibria, quasi-Nash equilibrium. Furthermore, in order to guarantee the fairness of the whole system, we propose a dynamic satisfaction-based dual-band traffic balancing (SDTB) algorithm over licensed and unlicensed bands for DACSs which aims at maximizing the overall satisfaction of the system. We obtain the optimal transmission time in the unlicensed band to ensure the proportional fair coexistence with WiFi while guaranteeing the traffic balancing of DACSs. Simulation results demonstrate that the SDTB algorithm could achieve a considerable performance improvement relative to the schemes in literature, while providing a tradeoff between maximizing the total data rate and achieving better fairness among networks.

scholarly journals User Association and Small-Cell Base Station On/Off Strategies for Energy Efficiency of Ultradense Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Jing Gao ◽  
Qing Ren ◽  
Pei Shang Gu ◽  
Xin Song
Keyword(s):  
Energy Efficiency ◽  
Optimization Method ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
User Association ◽  
User Mobility ◽  
Efficient Design ◽  
Widespread Application ◽  
Cell Base

The widespread application of wireless mobile services and requirements of ubiquitous access have resulted in drastic growth of the mobile traffic and huge energy consumption in ultradense networks (UDNs). Therefore, energy-efficient design is very important and is becoming an inevitable trend. To improve the energy efficiency (EE) of UDNs, we present a joint optimization method considering user association and small-cell base station (SBS) on/off strategies in UDNs. The problem is formulated as a nonconvex nonlinear programming problem and is then decomposed into two subproblems: user association and SBS on/off strategies. In the user association strategy, users associate with base stations (BSs) according to their movement speeds and utility function values, under the constraints of the signal-to-interference ratio (SINR) and load balancing. In particular, taking care of user mobility, users are associated if their speed exceeds a certain threshold. The macrocell base station (MBS) considers user mobility, which prevents frequent switching between users and SBSs. In the SBS on/off strategy, SBSs are turned off according to their loads and the amount of time required for mobile users to arrive at a given SBS to further improve network energy efficiency. By turning off SBSs, negative impacts on user associations can be reduced. The simulation results show that relative to conventional algorithms, the proposed scheme achieves energy efficiency performance enhancements.

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