
This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-channel code rate, and demonstrates that joint source-channel code design brings considerable performance advantage over a separate one in the non-asymptotic regime. A joint source-channel code maps a block of $k$ source symbols onto a length$-n$ channel codeword, and the fidelity of reproduction at the receiver end is measured by the probability $��$ that the distortion exceeds a given threshold $d$. For memoryless sources and channels, it is demonstrated that the parameters of the best joint source-channel code must satisfy $nC - kR(d) \approx \sqrt{nV + k \mathcal V(d)} Q(��)$, where $C$ and $V$ are the channel capacity and channel dispersion, respectively; $R(d)$ and $\mathcal V(d)$ are the source rate-distortion and rate-dispersion functions; and $Q$ is the standard Gaussian complementary cdf. Symbol-by-symbol (uncoded) transmission is known to achieve the Shannon limit when the source and channel satisfy a certain probabilistic matching condition. In this paper we show that even when this condition is not satisfied, symbol-by-symbol transmission is, in some cases, the best known strategy in the non-asymptotic regime.
converse, FOS: Computer and information sciences, rate-distortion theory, Computer Science - Information Theory, Information Theory (cs.IT), Shannon theory, memoryless sources, finite blocklength regime, lossy source coding, 620, 004, Achievability, joint source-channel coding (JSCC)
converse, FOS: Computer and information sciences, rate-distortion theory, Computer Science - Information Theory, Information Theory (cs.IT), Shannon theory, memoryless sources, finite blocklength regime, lossy source coding, 620, 004, Achievability, joint source-channel coding (JSCC)
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