Cognitive and Energy Harvesting-Based D2D Communication in Cellular Networks: Stochastic Geometry Modeling and Analysis Article Swipe
YOU?
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· 2015
· Open Access
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· DOI: https://doi.org/10.1109/tcomm.2015.2411266
While cognitive radio enables spectrum-efficient wireless communication, radio frequency (RF) energy harvesting from ambient interference is an enabler for energy-efficient wireless communication. In this paper, we model and analyze cognitive and energy harvesting-based device-to-device (D2D) communication in cellular networks. The cognitive D2D transmitters harvest energy from ambient interference and use one of the channels allocated to cellular users (in uplink or downlink), which is referred to as the D2D channel, to communicate with the corresponding receivers. We investigate two spectrum access policies for cellular communication in the uplink or downlink, namely, random spectrum access (RSA) policy and prioritized spectrum access (PSA) policy. In RSA, any of the available channels including the channel used by the D2D transmitters can be selected randomly for cellular communication, while in PSA the D2D channel is used only when all of the other channels are occupied. A D2D transmitter can communicate successfully with its receiver only when it harvests enough energy to perform channel inversion toward the receiver, the D2D channel is free, and the signal-to-interference-plus-noise ratio (SINR) at the receiver is above the required threshold; otherwise, an outage occurs for the D2D communication. We use tools from stochastic geometry to evaluate the performance of the proposed communication system model with general path-loss exponent in terms of outage probability for D2D and cellular users. We show that energy harvesting can be a reliable alternative to power cognitive D2D transmitters while achieving acceptable performance. Under the same SINR outage requirements as for the non-cognitive case, cognitive channel access improves the outage probability for D2D users for both the spectrum access policies. When compared with the RSA policy, the PSA policy provides a better performance to the D2D users. Also, using an uplink channel provides improved performance to the D2D users in dense networks when compared to a downlink channel. For cellular users, the PSA policy provides almost the same outage performance as the RSA policy.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tcomm.2015.2411266
- https://ieeexplore.ieee.org/ielx7/26/7108080/07056528.pdf
- OA Status
- bronze
- Cited By
- 342
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2076579100
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2076579100Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/tcomm.2015.2411266Digital Object Identifier
- Title
-
Cognitive and Energy Harvesting-Based D2D Communication in Cellular Networks: Stochastic Geometry Modeling and AnalysisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-03-09Full publication date if available
- Authors
-
Ahmed Hamdi Sakr, Ekram HossainList of authors in order
- Landing page
-
https://doi.org/10.1109/tcomm.2015.2411266Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/26/7108080/07056528.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/26/7108080/07056528.pdfDirect OA link when available
- Concepts
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Telecommunications link, Stochastic geometry, Cognitive radio, Computer science, Energy harvesting, Computer network, Interference (communication), Transmitter, Cellular network, Channel (broadcasting), Stochastic geometry models of wireless networks, Wireless, Signal-to-interference-plus-noise ratio, Electronic engineering, Energy (signal processing), Radio resource management, Telecommunications, Wireless network, Engineering, Power (physics), Mathematics, Physics, Statistics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
342Total citation count in OpenAlex
- Citations by year (recent)
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2025: 5, 2024: 7, 2023: 11, 2022: 20, 2021: 28Per-year citation counts (last 5 years)
- References (count)
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31Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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