Home Random Page


CATEGORIES:

BiologyChemistryConstructionCultureEcologyEconomyElectronicsFinanceGeographyHistoryInformaticsLawMathematicsMechanicsMedicineOtherPedagogyPhilosophyPhysicsPolicyPsychologySociologySportTourism






Soft output Viterbi algorithm

 

A decoder with a soft decision makes decision not only about binary value “1” or “0”, but also trust value related to this bit. If demodulator decides, then trust value is 1, the degree of trust to it is high. If it is less certain, then it has less trust value. A decoder with a soft input can produce data with a hard decision or data with a soft decision. For example, Viterbi decoder accepts soft information from a demodulator and produces data with a hard decision. A decoder can use soft information for determination of hard equality of the bit to “0” or “1”, and in the output we will get such hard decision.

The primary difference between hard-decision and soft-decision Viterbi decoding is that the soft-decision algorithm cannot use a Hamming distance metric because of its limited resolution. A distance metric with the required resolution is Euclidean distance, and to facilitate its use, the binary numbers “1” and “0” are transformed to the octal numbers “7” and “0”, respectively. Soft-decision Viterbi decoding, for the most part, proceeds in the same way as hard-decision. Consider how soft-decision decoding is performed with using Euclidean distances, i.e. BMt = . Suppose that a pair of soft-decision code symbols with values (5, 4) enters decoder during the first transition interval. The metric BM (0, 0) = and the metric BM (7, 7) = . The rest of the task, finding path in the trellis, proceeds in the same way as hard-decision decoding.

 


Date: 2015-02-16; view: 1110


<== previous page | next page ==>
Decoding of the nonsystematic convolutional codes | Concatenated codes
doclecture.net - lectures - 2014-2024 year. Copyright infringement or personal data (0.007 sec.)