A method for determination of RF exposure compliance for pico cell base stations by SAR measurements in a flat phantom

2004 ◽  
Author(s):  
L. Hamberg ◽  
N. Lovehagen ◽  
M. Siegbahn ◽  
C. Tornevik
Keyword(s):  
Base Stations ◽  
Rf Exposure ◽  
Cell Base

A 2.14-GHz GaN MMIC Doherty Power Amplifier for Small-Cell Base Stations

2014 ◽  
Vol 24 (4) ◽  
pp. 263-265 ◽  
Author(s):  
Cheol Ho Kim ◽  
Seunghoon Jee ◽  
Gweon-Do Jo ◽  
Kwangchun Lee ◽  
Bumman Kim
Keyword(s):  
Power Amplifier ◽  
Small Cell ◽  
Base Stations ◽  
Doherty Power Amplifier ◽  
Cell Base

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.

Determination of the general public exposure around GSM and UMTS base stations

2007 ◽  
Vol 124 (1) ◽  
pp. 40-47 ◽  
Author(s):  
C. Bornkessel ◽  
M. Schubert ◽  
M. Wuschek ◽  
P. Schmidt
Keyword(s):  
General Public ◽  
Base Stations ◽  
Public Exposure

scholarly journals An Optimal Energy Efficiency of a Two-tier Network in Control-Data Separation Architecture

2020 ◽  
pp. 545-550
Author(s):  
Zaid Mujaiyid Putra Bin Ahmad Baidowi ◽  
◽  
Xiaoli Chu
Keyword(s):  
Energy Efficiency ◽  
Point Processes ◽  
Threshold Value ◽  
Base Station ◽  
Base Stations ◽  
Mobile Users ◽  
Maximization Problem ◽  
User Association ◽  
Data Separation ◽  
Cell Base

In this paper, we propose to maximize the Energy Efficiency (EE) of a two-tier network by jointly optimizing the number of active small cell base stations (SBSs) and the user-cell association. We apply the concept of signaling and data separation where a macro cell base station (MBS) provides full coverage while the SBSs provide high data transmission. First, we model the spatial distributions of the SBSs and mobile users following two independent Poisson Point Processes (PPP) and derive the expressions for the Signal-to-Interference Ratio (SIR), user cell associations, power consumption and energy efficiency of the Heterogeneous Network (HetNet). Then, we formulate the EE maximization problem and solve it by proposing the Switching off Decision and User Association (SODUA) algorithm. The algorithm associates a mobile user to an SBS that offers the highest SIR and calculates the load of each SBS. The algorithm, then, decides to switch off the SBSs that have fewer mobile users than a threshold value, where the mobile users will be offloaded to a nearby SBS that offers the highest SIR. Finally, we calculate the EE of the HetNet. We compare the EE achieved by the proposed algorithm (i.e. after offloading) and that "without offloading". The results show that the proposed algorithm improves the EE of the HetNet and that the EE cannot be further improved by switching off more SBSs than a certain number.

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