Coded caching (CC) can substantially enhance network performance by leveraging memory as an additional communication resource. However, the use of CC is challenging in various practical applications due to dynamic user behavior. The existing solutions, based on shared caching, cannot directly handle all scenarios where users freely enter and depart the network at any time as they are constrained by specific conditions on network parameters. This paper proposes a universally applicable shared-caching scheme for dynamic setups without any restriction on network parameters. The closed-form expressions for the achievable degrees of freedom (DoF) are computed for the resulting generalized scheme, and are shown to achieve the existing optimal bounds of the shared-cache model. Furthermore, a successive-interference-cancellation-free extension based on a fast iterative optimized beamformer design is devised to optimize the use of excess spatial dimensions freed by cache-aided interference cancellation. Extensive numerical experiments are carried out to assess the performance of the proposed scheme. In particular, the results demonstrate that while a dynamic setup may achieve a DoF substantially lower than the optimal DoF of shared caching, our proposed scheme significantly improves the performance at the finite signal-to-noise ratio compared to unicasting, which only benefits from the local caching gain.

翻译：编码缓存（CC）可通过将内存作为额外通信资源显著增强网络性能。然而，由于动态用户行为，CC在实际应用中面临诸多挑战。现有基于共享缓存的解决方案受限于网络参数的特定条件约束，无法直接处理用户随时自由进出网络的所有场景。本文针对动态网络场景提出一种通用共享缓存方案，该方案对网络参数无任何限制。针对所提出的通用方案，推导了可达自由度（DoF）的闭式表达式，证明其能达到共享缓存模型的最优性能界。进一步地，基于快速迭代优化波束成形器设计，开发了无需串行干扰消除的扩展方案，以优化利用缓存辅助干扰消除所释放的多余空间维度。通过大量数值实验评估所提方案性能。结果表明，尽管动态网络场景的DoF可能显著低于共享缓存的最优DoF，但相较于仅受益于本地缓存增益的单播传输，我们的方案在有限信噪比条件下具有显著的性能提升。