July 2013 | Mohammad Ali Maddah-Ali and Urs Niesen
This paper introduces a novel coded caching approach that exploits both local and global caching gains to reduce peak traffic rates in communication systems. The local caching gain depends on the size of individual user caches, while the global caching gain depends on the total cache size across all users. The proposed scheme optimizes both the placement and delivery phases to achieve a multiplicative improvement in the peak rate compared to conventional uncoded caching schemes. The improvement can be significant, especially when the number of users is large. The paper formally analyzes the performance of the coded caching scheme using an information-theoretic formulation and shows that it achieves a rate that is within a constant factor of the information-theoretic optimum for all values of the problem parameters. The analysis is supported by numerical simulations and examples, demonstrating the effectiveness of the proposed scheme in reducing peak traffic rates.This paper introduces a novel coded caching approach that exploits both local and global caching gains to reduce peak traffic rates in communication systems. The local caching gain depends on the size of individual user caches, while the global caching gain depends on the total cache size across all users. The proposed scheme optimizes both the placement and delivery phases to achieve a multiplicative improvement in the peak rate compared to conventional uncoded caching schemes. The improvement can be significant, especially when the number of users is large. The paper formally analyzes the performance of the coded caching scheme using an information-theoretic formulation and shows that it achieves a rate that is within a constant factor of the information-theoretic optimum for all values of the problem parameters. The analysis is supported by numerical simulations and examples, demonstrating the effectiveness of the proposed scheme in reducing peak traffic rates.