# D2D-Aware Device Caching in MmWave-Cellular Networks

**Authors:** Nikolaos Giatsoglou, Konstantinos Ntontin, Elli Kartsakli, Angelos, Antonopoulos, Christos Verikoukis

arXiv: 1703.04935 · 2017-05-17

## TL;DR

This paper introduces a D2D-aware caching policy for mmWave cellular networks that improves content offloading and reduces retrieval delays by leveraging high-bandwidth mmWave D2D links and stochastic modeling.

## Contribution

It proposes a novel caching policy that splits content into groups for D2D sharing, with analytical modeling and validation showing superior performance over existing methods.

## Key findings

- Higher offloading gains compared to state-of-the-art
- Lower content retrieval delays across various content popularities
- Effective mitigation of interference in mmWave D2D communications

## Abstract

In this paper, we propose a novel policy for device caching that facilitates popular content exchange through high-rate device-to-device (D2D) millimeter-wave (mmWave) communication. The D2D-aware caching (DAC) policy splits the cacheable content into two content groups and distributes it randomly to the user equipment devices (UEs), with the goal to enable D2D connections. By exploiting the high bandwidth availability and the directionality of mmWaves, we ensure high rates for the D2D transmissions, while mitigating the co-channel interference that limits the throughput gains of D2D communication in the sub-6 GHz bands. Furthermore, based on a stochastic-geometry modeling of the network topology, we analytically derive the offloading gain that is achieved by the proposed policy and the distribution of the content retrieval delay considering both half- and full-duplex mode for the D2D communication. The accuracy of the proposed analytical framework is validated through Monte-Carlo simulations. In addition, for a wide range of a content popularity indicator the results show that the proposed policy achieves higher offloading and lower content-retrieval delays than existing state-of-the-art approaches.

## Full text

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## Figures

18 figures with captions in the complete paper: https://tomesphere.com/paper/1703.04935/full.md

## References

45 references — full list in the complete paper: https://tomesphere.com/paper/1703.04935/full.md

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Source: https://tomesphere.com/paper/1703.04935