Avoiding divergence in the constant modulus algorithm for blind equalization of MIMO systems

Pavan, Flávio R. M.; Silva, Magno T. M.; Miranda, María Dolores Martínez

doi:10.1109/sam.2016.7569728

Cited by 2 publications

(2 citation statements)

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“…To obtain the least square solution w s i to J (w i ), its gradient shown in (16), as shown at the bottom of the previous page, is set to zero, where sgn[•] is the signum function and f is the derivative of the second term in square bracket of (10) with regard to…”

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

confidence: 99%

“…To solve the random phase rotation and reduce the steady-state error of the above two algorithms, cross-correlation and multimodulus algorithm (CC-MMA) has been put forward [14], [15]. As the stability of these algorithms are easily affected by the initialization, step size and environment noise, and sometimes even divergent, recently, their robust versions have been further studied [16], [17]. Specifically, they work as the corresponding normalized version when the consistency rule is met, otherwise they disregard the cross-correlation term and estimate the dispersion error by a linear function.…”

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%