PhD Defense: Shuo Zheng

Shuo Zheng’s PhD defense will take place at 5th February, 10 am, Amphi Opale at TélécomParisTech (46 rue Barrault, 75013 Paris).

Committee:

  • Mr François-Xavier Coudoux, Université Polytechnique Hauts-de-France, Referee
  • Mrs Aline Roumy, INRIA Rennes, Referee
  • Mr Jean-Marie Gorce, INSA Lyon, Examiner
  • Mr Marc Leny, Ektacom, Examiner
  • Mrs Michèle Wigger, TélécomParitech, Examiner, Jury’s Chair
  • Mr Marco Cagnazzo, TélécomParisTech, Advisor
  • Mr Michel Kieffer, Université de Paris-sud, Advisor

Title: Accounting for Channel Constraints in Joint Source-Channel Video Coding Schemes

Abstract: SoftCast based Linear Video Coding (LVC) schemes have been emerged in the last decade as a quasi analog joint-source-channel alternative to classical video coding schemes. Theoretical analyses have shown that analog coding is better than digital coding in a multicast scenario when the channel signal-to-noise ratios (C-SNR) dier among receivers. LVC schemes provide in such context a decoded video quality at dierent receivers proportional to their C-SNR. This thesis considers rst the channel precoding and decoding matrix design problem for LVC schemes under a per-subchannel power constraint. Such constraint is found, e.g., on Power Line Telecommunication (PLT) channels and is similar to per-antenna power constraints in multi-antenna transmission system. An optimal design approach is proposed, involving a multi-level water lling algorithm and the solution of a structured Hermitian Inverse Eigenvalue problem. Three lower-complexity alternative suboptimal algorithms are also proposed. Extensive experiments show that the suboptimal algorithms perform closely to the optimal one and can reduce signicantly the complexity. The precoding matrix design in multicast situations also has been considered. A second main contribution consists in an impulse noise mitigation approach for LVC schemes. Impulse noise identication and correction can be formulated as a sparse vector recovery problem. A Fast Bayesian Matching Pursuit (FBMP) algorithm is adapted to LVC schemes. Subchannels provisioning for impulse noise mitigation is necessary, leading to a nominal video quality decrease in absence of impulse noise. A phenomenological model (PM) is proposed to describe the impulse noise correction residual. Using the PM model, an algorithm to evaluate the optimal number of subchannels to provision is proposed. Simulation results show that the proposed algorithms signicantly improve the video quality when transmitted over channels prone to impulse noise.

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