Multiaccess Coded Caching with Heterogeneous Retrieval Costs

2026-01-15

AI Summary

This work addresses the suboptimal total cost in multi-access coded caching systems, where existing approaches neglect the heterogeneous communication costs incurred when users retrieve content from different cache nodes. To tackle this limitation, we introduce, for the first time, a heterogeneous cache retrieval cost model and propose a layered caching framework based on superposition coding that explicitly accounts for the trade-off between broadcast and retrieval costs during the joint optimization of cache placement and delivery strategies. Theoretical analysis reveals that the optimal solution exhibits a sparse structure, which inspires the design of a low-complexity, structure-aware optimization algorithm. Simulation results demonstrate that the proposed scheme significantly outperforms the method by Cheng et al. under heterogeneous cost scenarios, achieving substantial reductions in overall system cost.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

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.

Problem

• Multiaccess Coded Caching
• Heterogeneous Retrieval Costs
• Cache-Access Cost
• Broadcast Cost
• Cost Minimization

Innovation

• multiaccess coded caching
• heterogeneous retrieval costs
• superposition coding
• cost-aware optimization
• sparsity structure