block are used to weight the different soft decisions using the proposed approach helps reduce the growth in the number of bits required to store the combined soft decisions when multiple transmissions of the same information are required the proposed approach also makes it possible to reduce the implementation complexity of the constellation demapping process when ir is used with multiple different modulation schemes the quality metric values used to perform the weighted combinations of soft decisions across multiple transmissions can be modified to reflect any difference in scaling of the soft decisions by the constellation demapping process the proposed approach can also be extended to efficiently operate when the selected implementation of the signal conditioning unit is adapted to the propagation channel conditions it is possible to apply different correction factors to the quality metrics depending on the implementation of the signal conditioning unit doing so guarantees that soft decisions generated by different signal conditioning units are combined with the correct weighting before being passed to the channel decoder in two embodiments of the proposed architecture it is shown that the quality metrics can be derived directly from the computations performed in the signal conditioning process fig2 presents a typical implementation of the demodulation unit 108 the received signal r n is first passed to the signal conditioning unit 201 to generate the signal s n the signal processing performed in the signal conditioning unit 201 depends on the transmission format as well as on the propagation environment for example in cdma systems it is typical to use a rake receiver in order to combine the contributions coming from the different propagation paths cdma u2014 principles of spread spectrum communication andrew j viterbi addison wesley wireless communications series it should however be noted.