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Implementation and Performance Analysis of Trellis Coded Modulation in Additive White Gaussian Noise

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Abstract

Band-limited channels face a serious challenge in modern communication due to the need to increase transmission rate while bandwidth remains the same. Mobile communications including mobile satellite, wireless mobile and indoor wireless communication all need to transmit at a higher rate. Trellis-coded Modulation (TCM) is a modulation and error control scheme that allow band-limited and/or power limited channels to attain an efficient data rate without an increase in bandwidth. It is an advanced mode of convolutional coding that combines digital modulation and error correction coding in a single stage. This project sought to investigate the performance of TCM in Additive White Gaussian Noise, modelling a mobile wireless channel. To do this, trellis codes are digitally modulated with M-ary PSK and M-ary QAM using computer simulation (MATLAB) and the performance is evaluated when the modulated signals propagates through additive white Gaussian Noise. Experiments were also carried out on hardware equipment using Telecommunication Instructional Modeling System (TIMS). The plot of bit error rate against \( E_{b} /N_{0} \) showed that there is a significant coding gain at no extra cost of bandwidth expansion.

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References

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Correspondence to Olawale Olapetan .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Olapetan, O., Otung, I. (2018). Implementation and Performance Analysis of Trellis Coded Modulation in Additive White Gaussian Noise. In: Odumuyiwa, V., Adegboyega, O., Uwadia, C. (eds) e-Infrastructure and e-Services for Developing Countries. AFRICOMM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 250. Springer, Cham. https://doi.org/10.1007/978-3-319-98827-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-98827-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98826-9

  • Online ISBN: 978-3-319-98827-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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