학술논문

Small cell placement and interference management in heterogeneous networks using multi-objective genetic algorithm
Document Type
Conference
Source
2017 International Conference on Applied System Innovation (ICASI) Applied System Innovation (ICASI), 2017 International Conference on. :1755-1758 May, 2017
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
Interference
Throughput
Computer architecture
Macrocell networks
Microprocessors
Biological cells
Genetic algorithms
Interference management
Heterogeneous network
Multi-objective GA
Language
Abstract
Small cells are being deployed at increasing rates to meet the multimedia communication demand in mobile network, but inter cell interference is a challenge in the heterogeneous network. In this study, we proposed a novel method to solve the small cell placement and the interference management problem. In order to achieve a tradeoff between the quality of service of cell edges user and the whole system performance, a multi-objective genetic algorithm is used to determine the number of small cells and their positions, and the transmission power in the macro base station. The simulation is conducted using a MATLAB, and the experimental results show that the proposed algorithm can find suitable resource allocation targeting on throughput or fairness requirement.