Flexible forward error correction codes with application to partial media data recovery
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摘要
Conventionally, linear block codes designed for packet erasure correction are targeted to recover all the lost source packets per block, when the fraction of lost data is smaller than the redundancy overhead. However, these codes fail to recover any lost packets, if the number of erasures just exceeds the limit for full recovery capability, while it can still be beneficial to recover part of the symbols. In addition, common linear block codes are not well suited for unequal error protection, since different block codes with different rates must be allocated for each priority class separately. These two problems motivate the design of more flexible forward error correction (FEC) codes for media streaming applications. We first review the performance of short and long linear block codes. Long block codes generally offer better error correction capabilities, but at the price of higher complexity and larger coding delay. Short block codes can be more appropriate in media streaming applications that require smooth performance degradation when the channel loss rate increases. We study a new class of linear block codes using sparse generator matrices that permit to optimize the performance of short block codes for partial recovery of the lost packets. In addition, the proposed codes are extended to the design of unequal erasure protection solutions. Simulations of practical video streaming scenarios demonstrate that the flexible sparse codes offer a promising solution with interesting error correction capabilities and small variance in the residual loss rate. They typically represent an effective trade-off between short block codes with limited flexibility, and long block codes with delay penalties.
论文关键词:Forward error correction,Multimedia communications,Video streaming
论文评审过程:Received 21 April 2008, Revised 18 November 2008, Accepted 30 December 2008, Available online 20 January 2009.
论文官网地址:https://doi.org/10.1016/j.image.2008.12.005