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Low-complexity near-optimal signal detection for uplink large-scale MIMO systems
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Low-complexity near-optimal signal detection for uplink large-scale MIMO systems
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Journal Article
Low-complexity near-optimal signal detection for uplink large-scale MIMO systems
2014
Overview
The minimum mean square error (MMSE) signal detection algorithm is near-optimal for uplink multi-user large-scale multiple-input–multiple-output (MIMO) systems, but involves matrix inversion with high complexity. It is firstly proved that the MMSE filtering matrix for large-scale MIMO is symmetric positive definite, based on which a low-complexity near-optimal signal detection algorithm by exploiting the Richardson method to avoid the matrix inversion is proposed. The complexity can be reduced from 𝒪(K3) to 𝒪(K2), where K is the number of users. The convergence proof of the proposed algorithm is also provided. Simulation results show that the proposed signal detection algorithm converges fast, and achieves the near-optimal performance of the classical MMSE algorithm.
Publisher
The Institution of Engineering and Technology,Institution of Engineering and Technology,John Wiley & Sons, Inc
Subject
/ Detection, estimation, filtering, equalization, prediction
/ Exact sciences and technology
/ Information, signal and communications theory
/ minimum mean square error signal detection
/ near‐optimal signal detection
/ Signal and communications theory
/ Telecommunications and information theory
/ uplink multiuser large‐scale multiple‐input‐multiple‐output systems
