Open AccessEnergy efficiency optimisation in MIMO‐OFDMA systems with block diagonalisation
Author(s) -
Mao Jing,
Chen Chen,
Cheng Xiang,
Xiang Haige
Publication year - 2017
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2017.0635
Subject(s) - subcarrier , mimo , computer science , mathematical optimization , signal subspace , subspace topology , selection (genetic algorithm) , resource allocation , orthogonal frequency division multiple access , telecommunications link , block (permutation group theory) , algorithm , orthogonal frequency division multiplexing , mathematics , telecommunications , beamforming , computer network , artificial intelligence , channel (broadcasting) , geometry , noise (video) , image (mathematics)
In this study, the authors investigate the energy‐efficient resource allocation in a multiuser downlink multiple‐input multiple‐output (MIMO) orthogonal frequency‐division multiple access system with block diagonalisation. Unlike the existing works in which one subcarrier is exclusively used, they consider the multiple user MIMO case on each subcarrier. An optimisation problem involving user selection, receive‐signal subspace selection and power allocation is formulated to maximise the system energy efficiency (EE). As optimising the orientation of the receive‐signal subspace is difficult, they considered two simpler resource allocation schemes, subspace selection scheme and user selection scheme. The two optimisation problems for the subspace and user selection schemes can be rewritten as a unified problem involving set selection and power allocation. By relaxing the combinatorial variables, they obtain an optimal joint set selection and power allocation solution, which can be directly applied to the original problem in most cases. To further reduce the complexity of the algorithm, they also develop a preselection technique for the user and received‐signal subspace on each subcarrier. Through simulations, they discuss the impact of different parameters on the EE for the two schemes and show that the proposed suboptimal algorithm can achieve a close performance to the optimal algorithm.