DocumentCode :
717550
Title :
A SVD-Based Optimum Algorithm Research for Macro-Femto Cell Interference Coordination
Author :
Kaiyue Yan ; Yan Yang ; Shuping Dang
Author_Institution :
State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
fYear :
2015
fDate :
11-14 May 2015
Firstpage :
1
Lastpage :
6
Abstract :
The intra-tier interference in heterogeneous networks becomes more serious when the number of macro-femto cells dramatically increases. Based on the singular value decomposition (SVD) algorithm, this paper proposes an optimized interference alignment (IA) algorithm to improve the macro-femto cell downlink rate. To achieve the largest degrees of freedom (DOF), we adopt the precoding matrix as a powerful tool to mitigate the effect of inter-channel interference (ICI). In comparison with the conventional interference coordination methods, the SVD algorithm is capable of adjusting the coefficients of the precoding matrix with lower complexity. Furthermore, zero-forcing algorithm is also used to combat ICI in this proposed IA algorithm. The numerical results show that ICI can be suppressed effectively and the system performance in terms of throughput and signal-to-interference- plus-noise ratio (SINR) can be improved considerably.
Keywords :
adjacent channel interference; femtocellular radio; precoding; singular value decomposition; SVD; heterogeneous networks; interchannel interference; intratier interference; macro-femto cell downlink rate; macro-femto cell interference coordination; optimized interference alignment algorithm; optimum algorithm research; precoding matrix; singular value decomposition; zero-forcing algorithm; Algorithm design and analysis; Interference; Macrocell networks; Receivers; Signal to noise ratio; Simulation; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st
Conference_Location :
Glasgow
Type :
conf
DOI :
10.1109/VTCSpring.2015.7145651
Filename :
7145651
Link To Document :
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