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（MACC）系统由一个中央服务器、K个无缓存用户和K个缓存节点组成。服务器拥有一个包含N个文件的库，并通过一条无差错共享链路连接到用户。每个缓存节点配备大小为M个文件的缓存容量。在循环环绕拓扑下，每个用户可以访问L个相邻缓存节点。现有研究大多基于一个强假设，即用户从连接的缓存节点检索内容时无需通信成本。实际上，每个用户从其L个不同连接的缓存节点检索内容时会产生不同的成本。此外，服务器向用户传输内容也会产生一定的成本。本文聚焦于成本感知的MACC系统，旨在最小化系统总成本，包括缓存访问成本和广播成本。首先，我们提出了一种基于叠加编码的新型编码缓存框架，其中对Cheng等人的MACC方案进行了分层处理。随后，推导出一个成本感知优化问题，以优化缓存放置并最小化系统成本。通过识别最优解的稀疏特性，我们提出了一种复杂度降低的结构感知算法。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。