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Cited by 448

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Base-Station Assisted Device-to-Device Communications for High-Throughput Wireless Video Networks

Golrezaei, Negin, Mansourifard, Parisa, Molisch, Andreas F., Dimakis, Alexandros G.·2014·IEEE Transactions on Wireless Communications

Abstract

We propose a new scheme for increasing the throughput of video files in cellular communications systems. This scheme exploits (1) the redundancy of user requests as well as (2) the considerable storage capacity of smartphones and tablets. Users cache popular video files and-after receiving requests from other users-serve these requests via device-to-device localized transmissions. The file placement is optimal when a central control knows a priori the locations of wireless devices when file requests occur. However, even a purely random caching scheme shows only a minor performance loss compared to such a “genie-aided” scheme. We then analyze the optimal collaboration distance, trading off frequency reuse with the probability of finding a requested file within the collaboration distance. We show that an improvement of spectral efficiency of one to two orders of magnitude is possible, even if there is not very high redundancy in video requests.

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Metadata

Authors
Golrezaei, N., Mansourifard, P., Molisch, A. F., & Dimakis, A. G.
Venue
IEEE Transactions on Wireless Communications
Published
2014-07
Volume
13
Issue
7
Pages
3665-3676
ISSN
1536-1276 (ISSN-L)
OpenAlex
W2039124714
Cited by
448
References
17
FWCI
73.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Base-Station Assisted Device-to-Device Communications for High-Throughput Wireless Video Networks. https://app.cochat.ai/papers/10.1109/twc.2014.2316817
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Golrezaei, N., Mansourifard, P., Molisch, A. F., & Dimakis, A. G. (2014). Base-Station Assisted Device-to-Device Communications for High-Throughput Wireless Video Networks. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/twc.2014.2316817

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.