This paper introduces Sign-Prioritized Federated Learning (SP-FL), a novel framework that improves wireless federated learning by prioritizing the transmission of critical gradient information, specifically gradient signs. It addresses unreliable communication in resource-constrained wireless networks by implementing an importance-aware hierarchical resource allocation strategy, demonstrating significant accuracy improvements.