Probabilistic Caching in Wireless D2D Networks: Cache Hit Optimal vs. Throughput Optimal

TL;DR

This paper explores probabilistic caching strategies in wireless D2D networks, optimizing for throughput rather than cache hit rate, and demonstrates significant gains in dense environments using stochastic geometry tools.

Contribution

It introduces a throughput-based caching optimization approach considering transmission reliability, providing a closed-form approximation and numerical solutions for optimal caching probabilities.

Findings

Throughput optimization yields higher request success density than cache-hit optimization.

Optimal caching probabilities vary with network density, favoring different strategies in dense environments.

Significant performance gains are achieved in dense user scenarios.

Abstract

Departing from the conventional cache hit optimization in cache-enabled wireless networks, we consider an alternative optimization approach for the probabilistic caching placement in stochastic wireless D2D caching networks taking into account the reliability of D2D transmissions. Using tools from stochastic geometry, we provide a closed-form approximation of cache-aided throughput, which measures the density of successfully served requests by local device caches, and we obtain the optimal caching probabilities with numerical optimization. Compared to the cache-hit-optimal case, the optimal caching probabilities obtained by cache-aided throughput optimization show notable gain in terms of the density of successfully served user requests, particularly in dense user environments.