A Semi-Adaptive MMSE Weights Generation Approach for Ordered Successive Detection in MIMO Systems


IEICE TRANSACTIONS on Communications   Vol.E87-B   No.2   pp.276-285
Publication Date: 2004/02/01
Online ISSN: 
Print ISSN: 0916-8516
Type of Manuscript: PAPER
Category: Wireless Communication Technology
wireless,  MIMO,  ordered successive detection,  minimum mean square error,  adaptive,  

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To increase the spectral utilization efficiency of a wireless link, multiple-input multiple-output (MIMO) systems can be employed to transmit several data streams in parallel at the same time and on the same frequency but from different transmit antennas. However, at the receiver side multi-stream detection is needed. In this paper, ordered successive MMSE detection (OSD) is considered as a low-complexity detection scheme. OSD's main computational cost lies in computing the nulling weights that correspond to each stage of successive detection. In this paper, we develop an efficient semi-adaptive approach to generate MMSE weights. This semi-adaptive approach efficiently combines two approaches: channel estimates-based direct matrix inversion weights generation (direct approach) and Recursive Least Squares (RLS) algorithm-based weights generation (adaptive approach). Although the direct approach alone performs better than the adaptive approach, it is more complex for updating weights within the tracking mode. On the other hand, the adaptive approach alone is less complex in updating weights within the tracking mode, but converges slowly within the training mode. Our combined semi-adaptive approach effectively offsets these disadvantages. We demonstrate, through computer simulations, that the semi-adaptive approach can achieve the BER of the direct approach in slow time-varying MIMO channels, while its computational complexity is less than or comparable to that of the adaptive approach.