Analysis and Optimization of Probabilistic Caching in Multi-Antenna Small-Cell Networks
Xianzhe Xu, Meixia Tao

TL;DR
This paper investigates probabilistic caching in multi-antenna small-cell networks, proposing user-centric clustering and beamforming schemes to optimize successful transmission probability using stochastic geometry.
Contribution
It introduces a user-centric clustering model with coordinated and uncoordinated beamforming, deriving tractable expressions and optimizing caching strategies for improved network performance.
Findings
ZF beamforming outperforms MF in interference nulling.
Optimal caching probabilities depend on beamforming scheme.
Closed-form expressions for successful transmission probability are derived.
Abstract
Previous works on cache-enabled small-cell networks (SCNs) with probabilistic caching often assume that each user is connected to the nearest small base station (SBS) among all that have cached its desired content. The user may, however, suffer strong interference from other SBSs which do not cache the desired content but are geographically closer. In this work, we investigate this issue by deploying multiple antennas at each SBS. We first propose a user-centric SBS clustering model where each user chooses its serving SBS only from a cluster of nearest SBSs with being a fixed cluster size. Two beamforming schemes are considered. One is coordinated beamforming, where each SBS uses zero-forcing (ZF) beamformer to null out the interference within the coordination cluster. The other is uncoordinated beamforming, where each SBS simply applies matched-filter (MF) beamformer. Using…
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