… conventional loss weighting strategies, including constant weighting, SNR weighting, and
SNR with an lower bound. Figure 4 shows that our MinSNR-γ weighting strategy produces …

… Differentiating (18) with respect tok , we can derive that the minimum of the variance is …
ones when the two sub-arrays having similar SNR. Otherwise, the joint estimator with improper …

… Within the framework of this case study this SNR-based weighting model has been implemented
in the BS5. The data preprocessing, for example, search for the minimum and maximum …

… strategy is given, the precoder proposed in this section can be directly applied. The design
of the scheduling strategy … “It-MSE-Min non-PNC” and “It-MSE-Min PNC,” decreases as SNR …

… The proposed strategy combines a robust near-optimal data-… bias, convergence to a local
minimum, or a catastrophe. … In particular, weighting (10) emphasizes high SNR components …

… This work presents a method for designing the weighting parameter … The proposed strategy
was specially derived for the … As a result, the minimum J T is affected by both g and SNR in …

… foundation for re-weighted minimum norm algorithms, which … algorithm as a computational
strategy partway between classical … on signal-to-noise ratio (SNR). In this case, the columns of …

… adaptive rate-based weighting strategy which further … achieved versus SNR for the “maximum
SINR” [6] and “minimum INL” [7… actual equalizer types for the ratebased weighting strategy. …

… wide range of SNR levels, we design a power function based weighting scheme for energy
… Because our system adopts CDR strategy, the interference induced by missed detection is …

… bias, our strategy relies on the introduction of a correction term in the a priori SNR estimate
… level and minimum spectral distortions. As a result, let us consider that the a posteriori …