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Efficient codebook design for digital communication through compressed voice channels

Boloursaz Mashhadi, M ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1049/iet-com.2015.0827
  3. Publisher: Institution of Engineering and Technology , 2016
  4. Abstract:
  5. The common voice channels existing in cellular communication networks provide reliable, ubiquitously available and top priority communication mediums. These properties make voice dedicated channels an ideal choice for high priority, real time communication. However, such channels include voice codecs that hamper the data flow by compressing the waveforms prior to transmission. This study designs codebooks of speech-like symbols for reliable data transfer through the voice channel of cellular networks. An efficient algorithm is proposed to select proper codebook symbols from a database of natural speech to optimise a desired objective. Two variants of this codebook optimisation algorithm are presented: One variant minimises the symbol error rate and the other maximises the capacity achievable by the codebook. It is shown both analytically and by the simulation results that under certain circumstances, these two objective functions reach the same performance. Simulation results also show that the proposed codebook optimisation algorithm achieves higher data rates and lower symbol error rates compared with previously reported results while requiring lower computational complexity for codebook optimisation. The Gilbert-Elliot channel model is utilised to study the effects of adaptive compression rate adjustment of the vocoder on overall voice channel capacity. Finally, practical implementation issues are addressed
  6. Keywords:
  7. Complex networks ; Data transfer ; Digital communication systems ; Fading channels ; Mobile telecommunication systems ; Signal encoding ; Adaptive compression ; Communication medium ; Digital communications ; Gilbert-Elliot channel model ; Objective functions ; Real-time communication ; Reliable data transfers ; Symbol error rate (SER) ; Optimization
  8. Source: IET Communications ; Volume 10, Issue 18 , 2016 , Pages 2613-2620 ; 17518628 (ISSN)
  9. URL: http://ieeexplore.ieee.org/document/7782134