This paper introduces a generalized stochastic geometry framework to analyze the coverage and ergodic rate performance of Integrated Sensing and Communication (ISAC) networks. The framework captures the spatial randomness in multi-cell networks, where both sensing and communication functions coexist. Key contributions include: 1. **Generalized Stochastic Geometry Framework**: A unified paradigm is established to model ISAC networks, considering the spatial randomness inherent in multi-cell networks. 2. **Coverage and Ergodic Rate Analysis**: Theoretical results are derived for the coverage and ergodic rate of sensing and communication performance under resource constraints. The coverage rate of unified ISAC performance is also presented, taking into account the coupling effects of dual functions. 3. **Analytical Formulations**: Expressions for evaluating the ergodic sensing rate constrained by the maximum communication rate and the ergodic communication rate constrained by the maximum sensing rate are obtained. 4. **Numerical Results**: Extensive simulations validate the accuracy of the derived formulations and show that denser networks significantly enhance ISAC coverage. Increasing the base station density from 1 km⁻² to 10 km⁻² boosts the ISAC coverage rate from 1.4% to 39.8%. Additionally, increasing the constrained sensing rate significantly improves the communication rate, while the reverse is less obvious. The paper provides insights into network deployment strategies and highlights the trade-offs between positioning accuracy and communication throughput in ISAC networks.This paper introduces a generalized stochastic geometry framework to analyze the coverage and ergodic rate performance of Integrated Sensing and Communication (ISAC) networks. The framework captures the spatial randomness in multi-cell networks, where both sensing and communication functions coexist. Key contributions include: 1. **Generalized Stochastic Geometry Framework**: A unified paradigm is established to model ISAC networks, considering the spatial randomness inherent in multi-cell networks. 2. **Coverage and Ergodic Rate Analysis**: Theoretical results are derived for the coverage and ergodic rate of sensing and communication performance under resource constraints. The coverage rate of unified ISAC performance is also presented, taking into account the coupling effects of dual functions. 3. **Analytical Formulations**: Expressions for evaluating the ergodic sensing rate constrained by the maximum communication rate and the ergodic communication rate constrained by the maximum sensing rate are obtained. 4. **Numerical Results**: Extensive simulations validate the accuracy of the derived formulations and show that denser networks significantly enhance ISAC coverage. Increasing the base station density from 1 km⁻² to 10 km⁻² boosts the ISAC coverage rate from 1.4% to 39.8%. Additionally, increasing the constrained sensing rate significantly improves the communication rate, while the reverse is less obvious. The paper provides insights into network deployment strategies and highlights the trade-offs between positioning accuracy and communication throughput in ISAC networks.