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Linear video coding (LVC) has recently emerged as a very promising paradigm for robust video delivery over unreliable channels. The pioneering LVC paper, introducing SoftCast, showed that, a cross-layer approach, based on linear-only processing followed by analog modulation, was able to improve the quality of received video with respect to traditional, layered approaches, when unreliable links to several users are considered. This paper considers the power allocation problem when the transmission channel consists of several sub-channels, each with its own power constraint. This framework models, e.g., multi-antenna, DSL, or powerline transmission systems. Minimizing the mean-square error at a receiver leads to an precoding and decoding matrix design problem. Our contributions consist in (1) formulating the matrix design problem in such a way that a multi-level water-filling solution proposed for MIMO channels can be adapted to LVC; (2) the proposal of three suboptimal power allocations techniques, with different trade-offs between complexity and efficiency; (3) a precoding matrix design for the multiple receivers scenario; (4) extensive simulations of the power allocation methods. The proposed optimal power allocation largely outperforms a simple adaptation of the allocation considered in SoftCast for the per-subchannel power constrained problem; moreover two of the suboptimal solutions perform very close to the optimal one, with a sensibly reduced complexity.

This paper considers the problem of impulse noise mitigation when video is encoded using a SoftCast-based Linear Video Coding (LVC) scheme and transmitted using an Orthogonal Frequency-Division Multiplexing (OFDM) scheme for multi-carrier modulation over a wideband channel prone to impulse noise. In the time domain, the impulse noise is modeled as realization of a sequence of independent and identically distributed Bernoulli-Gaussian variables. A Fast Bayesian Matching Pursuit algorithm is employed for impulse noise mitigation. This approach requires the provisioning of some OFDM subchannels to estimate the impulse noise locations and amplitudes. Provisioned subchannels cannot be used to transmit data and lead to a decrease of the video quality at receivers in absence of impulse noise. Using a phenomenological model (PM) of the residual noise variance after impulse mitigation in the subchannels, we have proposed an algorithms that is able to get the amount of subchannel to provision which minimizes the mean-square error of the decoded video at receivers. Simulation results show that the PM can accurately predict the number of subchannels to provision and that impulse noise mitigation can significantly improve the decoded video quality compared to a situation where all subchannels are used for data transmission.