Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems

In this paper, we address the issue of multiaccess communication through multi-hop linear non-regenerative relays, where all users, all relay nodes, and the destination node may have multiple antennas. Using a linear minimal mean-squared error (MMSE) receiver at the destination node, we demonstrate...

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Main Author: Rong, Yue
Format: Journal Article
Published: Institute of Electical and Electronic Engineers 2011
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/8919
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author Rong, Yue
author_facet Rong, Yue
author_sort Rong, Yue
building Curtin Institutional Repository
collection Online Access
description In this paper, we address the issue of multiaccess communication through multi-hop linear non-regenerative relays, where all users, all relay nodes, and the destination node may have multiple antennas. Using a linear minimal mean-squared error (MMSE) receiver at the destination node, we demonstrate that the optimal amplifying matrix at each relay node can be viewed as a linear MMSE filter concatenated with another linear filter. As a consequence, the MSE matrix of the signal waveform estimation at the destination node is decomposed into the sum of the MSE matrices at all relay nodes. We show that at a high signal-to-noise ratio (SNR) environment, this MSE matrix decomposition significantly simplifies the solution to the problem of optimizing the source precoding matrices and relay amplifying matrices. Simulation results show that even at the low to medium SNR range, the simplified optimization algorithms have only a marginal performance degradation but a greatly reduced computational complexity and signalling overhead compared with the existing optimal iterative algorithm, and thus are of great interest for practical relay systems.
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spelling curtin-20.500.11937-89192018-03-29T09:05:40Z Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems Rong, Yue Multiuser MIMO relay MMSE Multi-hop relay In this paper, we address the issue of multiaccess communication through multi-hop linear non-regenerative relays, where all users, all relay nodes, and the destination node may have multiple antennas. Using a linear minimal mean-squared error (MMSE) receiver at the destination node, we demonstrate that the optimal amplifying matrix at each relay node can be viewed as a linear MMSE filter concatenated with another linear filter. As a consequence, the MSE matrix of the signal waveform estimation at the destination node is decomposed into the sum of the MSE matrices at all relay nodes. We show that at a high signal-to-noise ratio (SNR) environment, this MSE matrix decomposition significantly simplifies the solution to the problem of optimizing the source precoding matrices and relay amplifying matrices. Simulation results show that even at the low to medium SNR range, the simplified optimization algorithms have only a marginal performance degradation but a greatly reduced computational complexity and signalling overhead compared with the existing optimal iterative algorithm, and thus are of great interest for practical relay systems. 2011 Journal Article http://hdl.handle.net/20.500.11937/8919 10.1109/TCOMM.2011.081111.100756 Institute of Electical and Electronic Engineers restricted
spellingShingle Multiuser
MIMO relay
MMSE
Multi-hop relay
Rong, Yue
Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems
title Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems
title_full Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems
title_fullStr Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems
title_full_unstemmed Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems
title_short Simplified Algorithms for Optimizing Multiuser Multi-Hop MIMO Relay Systems
title_sort simplified algorithms for optimizing multiuser multi-hop mimo relay systems
topic Multiuser
MIMO relay
MMSE
Multi-hop relay
url http://hdl.handle.net/20.500.11937/8919