SPC01-2: A New Blind Signal Separation Algorithm for Instantaneous MIMO System

Gu, Nong; Guan, Zhenying; Nahavandi, Saeid; Xiang, Yong

doi:10.1109/glocom.2006.533

Cited by 5 publications

(2 citation statements)

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“…To realize blind equalization and source separation simultaneously, function (7) and (10) are added, constructing the final cost function as (12) where β is the adjustment factor between source separation and equalization.…”

Section: A Svr-cc-mma(p 2)mentioning

confidence: 99%

“…modified observation is fed into the subsequent equalizer to retrieve another source. However, performance degradation is observed in these methods owing to inter-stage propagation of estimation errors [7]. Avoiding this defect, numbers of methods that can recover all sources simultaneously have been presented [1], [8]- [17], which are constructed via adding a separation term on the cost function of equalization.…”

Section: Introductionmentioning

confidence: 99%

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SVR Based Blind Signal Recovery for Convolutive MIMO Systems With High-Order QAM Signals

2019

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This paper addresses the blind signal recovery for convolutive multiple-input multiple-output systems with high-order quadrature amplitude modulation (QAM) signals. First, a family of batch blind recovery algorithms is proposed. Concretely, they introduce the error function of multimodulus algorithm and the cross-correlation among different equalizer output vectors into the penalty term of the support vector regression (SVR) framework to recover all sources simultaneously. Then, the corresponding dual-mode blind recovery schemes are constructed to further decrease the interference. The new blind formulation through iterative re-weighted least square achieves low complexity optimization. The SVR framework, in essence, determines that the proposals perform better than the conventional methods in terms of data block size, total interference, and symbol error rate. Moreover, the excellent initialization provided by the first mode and the accurate error expression in the second mode ensure that the SVR-based dual-mode schemes work well with the high-order QAM signals. Finally, the efficiency of the proposals over the classical approaches is evaluated by simulations. INDEX TERMS Convolutive MIMO systems, high-order QAM signals, blind equalization, blind source separation, support vector regression, multimodulus algorithm.

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Section: A Svr-cc-mma(p 2)mentioning

confidence: 99%