Distributed Compression of Linear Functions: Partial Sum-Rate Tightness and Gap to Optimal Sum-Rate Conference Paper uri icon


  • We consider the problem of distributed compression of the difference Z = Y1 cY2 of two jointly Gaussian sources Y1 and Y2 (with positive correlation coefficient and positive c) under an MSE distortion constraint D on Z. The rate region for this problem is unknown. We provide a new lower bound on the minimum sum-rate by utilizing the connection of the above problem with the two-terminal source coding problem with matrix-distortion constraint. Our lower bound not only improves existing bounds in many cases, but also allows us to prove sum-rate tightness of the Berger-Tung scheme when c is either relatively small or large and D is larger than some threshold. Furthermore, our lower bound enables us to show that the improved lattice-based scheme recently introduced in [1] (with the smallest achievable sum-rate) performs within 1.18 b/s from the optimal sum-rate for all values of c, and D. 2011 IEEE.

name of conference

  • 2011 IEEE International Symposium on Information Theory Proceedings

published proceedings

  • 2011 IEEE International Symposium on Information Theory Proceedings

author list (cited authors)

  • Yang, Y., & Xiong, Z.

citation count

  • 4

complete list of authors

  • Yang, Yang||Xiong, Zixiang

publication date

  • January 2011