To address the performance distortion caused by a priori information loss in signal transmission processes of communication systems, an information fidelity-based performance bounds evaluation method is proposed for information recovery. In practical communication environments, due to channel noise and system non-ideality, the receiver often can not obtain a complete priori information from the transmitter, which limits the applicability of traditional Fisher-information-based Cramer-Rao bounds under such conditions. By introducing the concept of information fidelity and its moment generating function, an inequality relating the noise-to-signal ratio, the Fisher information, and the fidelity information is established, and a new lower-bound estimation model for NSR(Noise-to-Signal Ratio) is derived, providing more robust theoretical bounds for information recovery performance in communication systems. Theoretical analysis and two numerical examples ( including a binary communication system and a multimode signal transmission channel) demonstrate that, compared with classical Fisher-information-based bounds, the information-fidelity-based bounds, while more relaxed, exhibit stronger robustness and practicality in realistic scenarios with incomplete a priori information, and small sample sizes,offering a new theoretical tool for communication system performance evaluation.

communication systems, information fidelity, information recovery, performance bounds, Fisher information, Cramer-Rao inequality