English

Exact Minimax Estimation for Phase Synchronization

Statistics Theory 2021-01-08 v2 Optimization and Control Statistics Theory

Abstract

We study the phase synchronization problem with measurements Y=zzH+σWCn×nY=z^*z^{*H}+\sigma W\in\mathbb{C}^{n\times n}, where zz^* is an nn-dimensional complex unit-modulus vector and WW is a complex-valued Gaussian random matrix. It is assumed that each entry YjkY_{jk} is observed with probability pp. We prove that the minimax lower bound of estimating zz^* under the squared 2\ell_2 loss is (1o(1))σ22p(1-o(1))\frac{\sigma^2}{2p}. We also show that both generalized power method and maximum likelihood estimator achieve the error bound (1+o(1))σ22p(1+o(1))\frac{\sigma^2}{2p}. Thus, σ22p\frac{\sigma^2}{2p} is the exact asymptotic minimax error of the problem. Our upper bound analysis involves a precise characterization of the statistical property of the power iteration. The lower bound is derived through an application of van Trees' inequality.

Cite

@article{arxiv.2010.04345,
  title  = {Exact Minimax Estimation for Phase Synchronization},
  author = {Chao Gao and Anderson Y. Zhang},
  journal= {arXiv preprint arXiv:2010.04345},
  year   = {2021}
}
R2 v1 2026-06-23T19:11:44.561Z