On Linear Precoding of Nonregenerative MIMO Relay Networks for Finite-alphabet Source

Author

Xiao Liang
Zhi Ding
Chengshan Xiao, Missouri University of Science and TechnologyFollow

Abstract

Multiple input and multiple output (MIMO) relay could provide broader wireless coverage, better diversity, and higher throughput. Most existing precoder designs for either source or relay node are based on the assumption of Gaussian input signals. However, recent works have revealed possible performance loss of MIMO systems originally optimized for Gaussian source signals when applied to practical finite-alphabet source signals. In this work, we investigate the design problem of joint MIMO precoding for wireless two-hop nonregenerative cooperative relay networks under finite-alphabet source signals. We identify several structural properties of optimal precoders. Specifically, we provided the optimal left singular vectors of the relay precoder and proved the convexity of mutual information with respect to the square of relay precoder singular value. These results generalize the two-hop relay networks in Gaussian input assumption to the cooperative relay networks in arbitrary finite-alphabet input signals. Furthermore, we propose gradient-based numerical iterative optimization algorithms not only for arbitrary finite-alphabet source signal precoding but also for cooperative relay networks which may or may not have a direct source to destination link. Our results demonstrate substantial performance improvement over existing precoder designed traditionally under Gaussian input assumption, which indicates that the water filling based precoding strategy is not suitable for finite-alphabet constellation source inputs.

Recommended Citation

X. Liang et al., "On Linear Precoding of Nonregenerative MIMO Relay Networks for Finite-alphabet Source," IEEE Transactions on Vehicular Technology, vol. 66, no. 11, pp. 9761 - 9775, article no. 7954686, Institute of Electrical and Electronics Engineers, Nov 2017.

The definitive version is available at https://doi.org/10.1109/TVT.2017.2717925

Department(s)

Electrical and Computer Engineering

Comments

National Science Foundation, Grant ECCS-1231848

Keywords and Phrases

Amplify-and-forward; convex; minimum mean-square error; mutual information

International Standard Serial Number (ISSN)

0018-9545

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Nov 2017