Performance of multilevel turbo codes with group partitioning over satellite channels

Osman O., Uçan O. N. , Odabasioglu N.

IEE PROCEEDINGS-COMMUNICATIONS, vol.152, no.6, pp.1055-1059, 2005 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 152 Issue: 6
  • Publication Date: 2005
  • Doi Number: 10.1049/ip-com:20059063
  • Page Numbers: pp.1055-1059


A new type of turbo codes called multilevel turbo codes (ML-TC) which employ a new partitioning technique (group partitioning) in order to improve channel error performance. The underlying basis for multilevel coding is partitioning a signal set into several levels and encoding each level separately through the respective layer of the encoder. Initial partitioning levels are very important for the performance of ML-TC schemes. Group partitioning maximises the Euclidean distance of these levels, and it provides additional bit error performance augmentation of 0.6 dB for the range of signal-to-noise ratio (SNR) under study. The ML-TC system contains multiple turbo encoder/decoder blocks in its architecture. The parallel input data sequences are encoded by the multilevel scheme and mapped to any modulation type, such as MPSK. MQAM. etc. Then, for the purpose of performance analysis, these modulated signals are passed through narrowband fading channels. At the receiver side, the input sequence of the first level is estimated by the first turbo decoder block. Subsequently, the other input sequences of other levels are computed using the estimated input bit streams of the respective previous levels. Following that process, the performance of the proposed system is investigated in various fading channels. As an example, 4-PSK two-level turbo codes are simulated over AWGN, Rician and Rayleigh channels for 100 and 256 frame sizes. ML-TC simulation results display coding gains of up to 4.5 dB, when compared to those of 8-PSK turbo trellis-coded modulation. Therefore, it is concluded that satisfactory performance is achieved in ML-TC systems for all SNR values in various fading environments.