Nonasymptotic Noisy Lossy Source Coding

作者：Kostina Victoria^*; Verdu Sergio

来源：IEEE Transactions on Information Theory, 2016, 62(11): 6111-6123.

DOI：10.1109/TIT.2016.2562008

• Achievability
• converse
• finite blocklength regime
• lossy data compression
• noisy data compression
• noisy source coding
• noisy sources
• strong converse
• dispersion
• memoryless sources
• Shannon theory

This paper shows new general nonasymptotic achievability and converse bounds and performs their dispersion analysis for the lossy compression problem in which the compressor observes the source through a noisy channel. While this problem is asymptotically equivalent to a noiseless lossy source coding problem with a modified distortion function, nonasymptotically there is a noticeable gap in how fast their minimum achievable coding rates approach the common rate-distortion function, as evidenced both by the refined asymptotic analysis (dispersion) and the numerical results. The size of the gap between the dispersions of the noisy problem and the asymptotically equivalent noiseless problem depends on the stochastic variability of the channel through which the compressor observes the source.

• 出版日期2016-11