In this paper, we present a consensus-based framework for decentralized estimation of deterministic parameters in wireless sensor networks (WSNs). In particular, we propose an optimization algorithm to design (possibly complex) sensor gains in order to achieve an estimate of the parameter of interest that is as accurate as possible. The proposed design algorithm employs a cyclic approach capable of handling various sensor gain constraints. In addition, each iteration of the proposed design framework is comprised of the Gram-Schmidt process and power-method like iterations, and as a result, enjoys a low-computational cost.