The performance of various PSO algorithms, including our proposed algorithm, is compared in the context of adaptive channel equalization to that of the LMS algorithm through extensive simulations.
We assume that R R ≠ S R, since the high SNR expressions for I adm in the context of MMSE channel equalization in Appendix 1 indicate that I T = I for this application and according to Theorem 5 the optimal training corresponds to the optimal training for channel estimation in [8].
n T = 6, n R = 6, B = 8, a = 99. Figure 3 L-optimality criterion with arbitrary but positive semidefinite W 1, W 2 for the MMSE estimator with R R = S R. n T = 3, n R = 3, B = 4, a = 99. Figure 4 demonstrates the performance of optimal training designs for the MMSE estimator in the context of MMSE channel equalization.
In the context of HARQ protocols, joint equalization of multiple received copies of the same packet significantly enhances system performance, especially when there is channel diversity among subsequent HARQ transmissions.
Such a basis expansion has been successfully applied in the context of channel estimation and equalization in wireless communications, where the coefficients of the channel impulse response are low-pass processes with a bandwidth that is limited by the Doppler frequency [3 5].
It is shown, with the aid of a representative set of simulation results, that the proposed methodologies are capable of leading to significant performance improvements in the context of relevant information processing tasks – channel equalization and chaotic time series prediction – particularly when the input data suits well a cluster-based profile.
Equalization, decoding, and joint equalization and decoding will be discussed in the context of the MAP algorithm, but for completeness the MLSE algorithm will also be discussed.
Differential encoding is a widely used technique in the context of orthogonal frequency division multiplexing (OFDM) as an alternative to coherent channel estimation and equalization.
The proposed architecture is then analyzed in the context of a set of representative information extraction problems, more specifically supervised and unsupervised channel equalization, and blind separation of convolutive mixtures.
But the purpose of this paper is not to explore how an international equalization scheme for universal health coverage could be organized; the purpose is to explore one of the arguments for such a scheme – an argument that has received limited attention in the context of international aid.
