Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2013(Vol.5, Issue:04)
Article Information:

Improved QR Decomposition-Based SIC Detection Algorithm for MIMO System

Li Liu, Jinkuan Wang, Fulai Liu, Xin Song and Yuhuan Wang
Corresponding Author:  Li Liu 
Submitted: June 28, 2012
Accepted: August 17, 2012
Published: February 01, 2013
Abstract:
Multiple-Input Multiple-Output (MIMO) systems can increase wireless communication system capacity enormously. Maximum Likelihood (ML) detection algorithm is the optimum detection algorithm which computational complexity growing exponentially with the number of transmit-antennas, which makes it difficult to use it in practice system. Ordered Successive Interference Cancellation (SIC) algorithm with lower computing complexity will suffer from error propagation when an incorrect symbol is selected in the early layers. An MIMO signal detection algorithm based on Improved Sorted-QR decomposition (ISQR) is presented in this study. According to the rule of SNR, ISQR can obtain the optimum detection order with less calculation. Based on ISQR an improved detection algorithm is proposed which providing 2 adjustable parameters. Trade-off between performance and complexity can be selected properly by setting the 2 parameters at different values. Simulation experiments are given under the multiple scattering wireless communication environments and the simulation experiment results show the validity of proposed algorithm.

Key words:  Maximum likelihood detection, MIMO, QR-decomposition, successive interference cancellation, , ,
Abstract PDF HTML
Cite this Reference:
Li Liu, Jinkuan Wang, Fulai Liu, Xin Song and Yuhuan Wang, . Improved QR Decomposition-Based SIC Detection Algorithm for MIMO System. Research Journal of Applied Sciences, Engineering and Technology, (04): 1251-1256.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved