Hybrid Coded Caching in Cellular Networks with D2D-Enabled Mobile Users

Hassanpour, Seyedeh Bahereh; Khonsari, Ahmad; Shariatpanahi, Seyed Pooya; Dadlani, Aresh

doi:10.1109/pimrc.2019.8904142

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…The global caching gain is proportional to the aggregate memory of all the caches, where every user benefits from its cache contents to decode the desired content and to remove the interference in the coded message due to other caches requests. This idea has been further generalized to hierarchical coded caching [7], multi-server coded caching [8], decentralized coded caching [9]- [11], online coded caching [12], device to device (D2D) coded caching [13], hybrid server-D2D coded caching [14], coded caching with asynchronous user requests [15], and coded caching with multiple file requests [16]- [18].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Content Caching for Shared Medium Networks Under Heterogeneous Users' Behaviours

Sheshjavani,

Khonsari,

Shariatpanahi

et al. 2021

Preprint

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Content caching is a widely studied technique aimed to reduce the network load imposed by data transmission during peak time while ensuring users' quality of experience. It has been shown that when there is a common link between caches and the server, delivering contents via the coded caching scheme can significantly improve performance over conventional caching. However, finding the optimal content placement is a challenge in the case of heterogeneous users' behaviours. In this paper we consider heterogeneous number of demands and non-uniform content popularity distribution in the case of homogeneous and heterogeneous user-preferences. We propose a hybrid coded-uncoded caching scheme to trade-off between popularity and diversity. We derive explicit closed-form expressions of the server load for the proposed hybrid scheme and formulate the corresponding optimization problem. Results show that the proposed hybrid caching scheme can reduce the server load significantly and outperforms the baseline pure coded and pure uncoded and previous works in the literature for both homogeneous and heterogeneous user preferences.

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Section: Introduction 1backgroundmentioning

confidence: 99%

Content Caching for Shared Medium Networks Under Heterogeneous Users' Behaviours

Sheshjavani,

Khonsari,

Shariatpanahi

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

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“…In [40], the throughput scaling of the network was improved by exploiting the global caching gain and the spatial reuse gain simultaneously. The authors in [41] proposed a hybrid coded caching approach to enhance cellular network performance by applying decentralized coded caching. This approach provided spatial reuse gain in the first sub-phase, and centralized coded caching enabling multicasting transmissions in the second sub-phase.…”

Section: Introductionmentioning

confidence: 99%

Smart Technique for Cache-Assisted Device to Device Communications

2020

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The emergence of smart terminals with the consequence of higher network traffic growth rates, has increased the demand for new techniques that are needed to meet user requirements for high-quality communication and social media services. One of these techniques is Device-to-Device (D2D) communication, allowing direct data transmission of popular files between users. This is an advantage during rush hours where there is no access to the traffic via a base station (BS), thereby reducing network loads. In this paper, we propose a new caching paradigm for D2D communication to achieve the goal of rising network offloading. A Smart Adaptive Algorithm (SAA) is proposed that smartly selects users with higher probabilities of sharing more data, then places popular files in their cache. This is done to optimize network offloading at minimal consumed energy by the user (user cost), taking into account the user speed, location, predicted zones, interests, and the size of the requested file. The data offloading ratio is taken as a performance metric in evaluating network offloading. It is defined as the proportion of requested data that can be delivered via D2D links. The offloading ratio is calculated in different scenarios in order to assess the influence of proactive caching on core network load. To minimize the complexity of the algorithm, and to respond in a shorter time period to the number of requests, user demand shall be handled with both the base station and the user's device application. For the simulation and implementation of the proposed algorithm, a human mobility model that predicts different human mobility behaviors is used. The simulation results reveal that the offloading ratio is significantly affected by the size of the file transmitted via D2D connection as well as the user speed. The amount of increase in the offloading ratio due to the increase in the user speed is based on the size of the files transmitted through D2D connection. The smaller files transmitted via D2D connection would result in a significant increase in the offloading ratio, whereas the larger file size would result in a less change in the offloading ratio for higher speed users. The simulation results also reveal that higher speed users share more data at a high bit rates compared to users with lower speeds. Simulation results also show that the proposed SAA has superior performance as compared to other algorithms available in literature.

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