Generalized Gaussian Multiterminal Source Coding: The Symmetric Case

Consider a generalized multiterminal source coding system, where $\binom{\ell }{ m}$ encoders, each observing a distinct size- $m$ subset of $\ell $ ( $\ell \geq 2$ ) zero-mean unit-variance exchangeable Gaussian sources with correlation coefficient $\rho $ , compress their observations in such a way that a joint decoder can reconstruct the sources within a prescribed mean squared error distortion based on the compressed data. The optimal rate-distortion performance of this system was previously known only for the two extreme cases $m=\ell $ (the centralized case) and $m=1$ (the distributed case), and except when $\rho =0$ , the centralized system can achieve strictly lower compression rates than the distributed system under all non-trivial distortion constraints. Somewhat surprisingly, it is established in the present paper that the optimal rate-distortion performance of the afore-described generalized multiterminal source coding system with $m\geq 2$ coincides with that of the centralized system for all distortions when $\rho \leq 0$ and for distortions below an explicit positive threshold (depending on $m$ ) when $\rho > 0$ . Moreover, when $\rho > 0$ , the minimum achievable rate of generalized multiterminal source coding subject to an arbitrary positive distortion constraint $d$ is shown to be within a finite gap (depending on $m$ and $d$ ) from its centralized counterpart in the large $\ell $ limit except for possibly the critical distortion $d=1-\rho $ .