Linear Space-Time Interference Alignment for $K$ -User MIMO Interference Channels
Author(s) -
Xiaorong Jing,
Linlin Mo,
Hongqing Liu,
Cuicui Zhang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2787153
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Interference is believed to be the most significant bottleneck for the next-generation wireless networks to achieve high throughout. Interference alignment (IA), as a novel interference management scheme to break through the traditional interference cancelation, not only makes the complete mitigation of interference possible but also achieves a theoretical breakthrough in promoting the wireless network capacity region. In this paper, by combining the space and time, we proposed a linear space-time (LST) IA algorithm based on the extension of the channel in time dimension for K-user multi-input multi-output interference channel. The proposed LST-IA scheme effectively reduces the number of antennas required for eliminating interference completely in systems, and the closed-form solution of precoding matrices and detector matrices is obtained as well. Compared with the classical IA algorithms, the simulation results demonstrate that the proposed scheme shows distinguished advantages in terms of sum-rate and bit error rate in the strong interference communication scenarios.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom