List sequence MAP decoding

Carl Fredrik Leanderson, Carl-Erik W. Sundberg

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingResearchpeer-review


A list sequence (LS) maximum a posteriori probability (MAP) decoding algorithm for convolutional codes, that takes into account bitwise a priori probabilities and produces a rank ordered list of [script L] sequence MAP estimates, can be obtained by modification of the metric increments of the serial list Viterbi algorithm. In this paper, we study the performance of LS-MAP decoding with genie-assisted error detection on the additive white Gaussian noise channel. Computer simulations and approximate analytical expressions, based on geometrical considerations are presented. We focus on the frame error rate and it is concluded that LS-MAP decoding with [script L] > 1 often exploits a priori information more efficiently than conventional single sequence MAP decoding ( [script L] = 1). This leads in many cases to larger relative gains with LS-MAP than LS-ML decoding as [script L] increases.
Original languageEnglish
Title of host publicationConference Record / IEEE Global Telecommunications Conference
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication statusPublished - 2002
EventGLOBECOM'02 - IEEE Global Telecommunications Conference, 2002 - Taipei, Taiwan, Province of China
Duration: 2002 Nov 172002 Nov 21

Publication series



ConferenceGLOBECOM'02 - IEEE Global Telecommunications Conference, 2002
Country/TerritoryTaiwan, Province of China

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering


  • List sequence maximum a posteriori probability (LS-MAP) decoding


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