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Traffic analysis presents a serious threat to wireless network privacy due to the open nature of wireless medium. Traditional solutions are mainly based on the mix mechanism proposed by David Chaum, but the main drawback is its low network performance due to mixing and cryptographic operations. We propose a novel privacy preserving scheme based on network coding called Priv-Code to counter against traffic analysis attacks for wireless communications. Priv-Code is able to provide strong privacy protection for wireless networks as the mix system because of its intrinsic mixing feature, and moreover, it can achieve better network performance owing to the advantage of network coding. We first construct a hypergraph-based network coding model for wireless networks, under which we formalize an optimization problem whose objective function is to make each node have identical transmission rate. Then we provide a decentralized algorithm for this optimization problem. After that we develop an information theoretic metric for privacy measurement using entropy, and based on this metric we demonstrate that Priv-Code achieves stronger privacy protection than the mix system while achieving better network performance.