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On Optimal TCM Encoders

Alex Alvarado ; Alexandre Graell i Amat (Institutionen för signaler och system, Kommunikationssystem) ; Fredrik Brännström (Institutionen för signaler och system, Kommunikationssystem) ; Erik Agrell (Institutionen för signaler och system, Kommunikationssystem)
IEEE Transactions on Communications (0090-6778). Vol. 61 (2013), 6, p. 2178 - 2189 .
[Artikel, refereegranskad vetenskaplig]

An asymptotically optimal trellis-coded modulation (TCM) encoder requires the joint design of the encoder and the binary labeling of the constellation. Since analytical approaches are unknown, the only available solution is to perform an exhaustive search over the encoder and the labeling. For large constellation sizes and/or many encoder states, however, an exhaustive search is unfeasible. Traditional TCM designs overcome this problem by using a labeling that follows the set-partitioning principle and by performing an exhaustive search over the encoders. In this paper we study binary labelings for TCM and show how they can be grouped into classes, which considerably reduces the search space in a joint design. For $8$-ary constellations, the number of different binary labelings that must be tested is reduced from $8!=40320$ to $240$. For the particular case of an $8$-ary pulse amplitude modulation constellation, this number is further reduced to $120$ and for $8$-ary phase shift keying to only $30$. An algorithm to generate one labeling in each class is also introduced. Asymptotically optimal TCM encoders are tabulated which are up to $0.3$~dB better than the previously best known encoders.

Nyckelord: Binary reflected Gray code; bit-interleaved coded modulation; coded modulation; convolutional encoder; performance bounds; set-partitioning; trellis-coded modulation; Viterbi decoding

Denna post skapades 2013-06-13. Senast ändrad 2016-04-28.
CPL Pubid: 178335


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Institutioner (Chalmers)

Institutionen för signaler och system, Kommunikationssystem (1900-2017)



Chalmers infrastruktur



Denna publikation är ett resultat av följande projekt:

MIMO-BICM: Fundamentals, Analysis, and Design (VR//2011-5950)

Signal Recovery: Compressed Sensing meets Coding Theory (VR//2011-5961)