Joint beam design and user selection over non-binary coded MIMO interference channel

Haitao Li; Haiying Yuan

doi:10.1117/12.2014020

13 March 2013 Joint beam design and user selection over non-binary coded MIMO interference channel

Haitao Li, Haiying Yuan

Proceedings Volume 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies; 878418 (2013) https://doi.org/10.1117/12.2014020
Event: Fifth International Conference on Machine Vision (ICMV 12), 2012, Wuhan, China

Abstract

In this paper, we discuss the problem of sum rate improvement for coded MIMO interference system, and propose joint beam design and user selection over interference channel. Firstly, we have formulated non-binary LDPC coded MIMO interference networks model. Then, the least square beam design for MIMO interference system is derived, and the low complexity user selection is presented. Simulation results confirm that the sum rate can be improved by the joint user selection and beam design comparing with single interference aligning beamformer.

Citation Download Citation

Haitao Li and Haiying Yuan "Joint beam design and user selection over non-binary coded MIMO interference channel", Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 878418 (13 March 2013); https://doi.org/10.1117/12.2014020

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available