The multiaccess coded caching (MACC) system, as formulated by Hachem {\it et al.}, consists of a central server with a library of $N$ files, connected to $K$ cache-less users via an error-free shared link, and $K$ cache nodes, each equipped with cache memory of size $M$ files. Each user can access $L$ neighboring cache nodes under a cyclic wrap-around topology. Most existing studies operate under the strong assumption that users can retrieve content from their connected cache nodes at no communication cost. In practice, each user retrieves content from its $L$ different connected cache nodes at varying costs. Additionally, the server also incurs certain costs to transmit the content to the users. In this paper, we focus on a cost-aware MACC system and aim to minimize the total system cost, which includes cache-access costs and broadcast costs. Firstly, we propose a novel coded caching framework based on superposition coding, where the MACC schemes of Cheng \textit{et al.} are layered. Then, a cost-aware optimization problem is derived that optimizes cache placement and minimizes system cost. By identifying a sparsity property of the optimal solution, we propose a structure-aware algorithm with reduced complexity. Simulation results demonstrate that our proposed scheme consistently outperforms the scheme of Cheng {\it et al.} in scenarios with heterogeneous retrieval costs.

翻译：由Hachem等人提出的多接入编码缓存系统包含一个拥有N个文件库的中心服务器，通过无差错共享链路连接至K个无缓存用户及K个缓存节点，每个缓存节点配备容量为M个文件的缓存存储器。在循环环绕拓扑下，每个用户可访问L个相邻缓存节点。现有研究大多基于用户从连接缓存节点检索内容无需通信成本的强假设。实际场景中，用户从其L个不同连接缓存节点检索内容存在差异化的成本开销。此外，服务器向用户传输内容也会产生特定成本。本文聚焦于成本感知的多接入编码缓存系统，旨在最小化包含缓存访问成本与广播传输成本在内的系统总成本。首先，我们提出基于叠加编码的新型编码缓存框架，将Cheng等人的多接入编码缓存方案进行分层处理。进而推导出优化缓存放置以最小化系统成本的成本感知优化问题。通过识别最优解的稀疏特性，我们提出了一种降低复杂度的结构感知算法。仿真结果表明，在异构检索成本场景下，我们提出的方案始终优于Cheng等人的方案。