Optimal channel selection for simultaneous RF energy harvesting and data transmission in cognitive radio networks

Hooshiary, Akram; Azmi, Paeiz; Mokari, Nader; Maleki, Sina

doi:10.1002/ett.3291

Cited by 10 publications

(6 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…

E_{h, k m}^{t - 1}

is the amount of the harvested energy by the k ‐th user of the m ‐th RRH during slot t −1 which is obtained as follows:

\begin{align} E_{h, k m}^{t prefix- 1} = true \sum_{f = 1}^{M} false(1 prefix- α_{f} false) T {\overset{P}{true}}_{h, k m}^{f, t prefix- 1} φ_{k m}^{f}, \end{align}

where

φ_{k m}^{f}

is an assignment index,

φ_{k m}^{f}

is set to ‘1’ if the k ‐th user of the m ‐th RRH selects the f ‐th channel for energy harvesting. Also

{\hat{P}}_{k m}^{f, t - 1}

is the amount of harvesting power by the k ‐th user of the m ‐th RRH during slot t −1 from channel f , which is obtained as below:

\begin{align} {\overset{P}{true}}_{h, k m}^{f, t prefix- 1} = \frac{1}{4 R_{L}} ({}, {false(2 p_{k F}^{n} false| h_{k m}^{f} {false|}^{2} R_{a} false)}^{1 false/ 2} prefix- \frac{i V_{T}}{2} normalln ((), 2 π false(2 p_{k F}^{n} false| h_{k m}^{f} {false|}^{2} R_{a} false))) \end{align}

…”

Section: Problem Formulation For a Pdma‐based Systemmentioning

confidence: 99%

Energy efficient transmission in dynamic PDMA‐based systems with RF energy harvesting

Hooshiary

Azmi

Mokari

2020

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

Nonorthogonal multiple access (NOMA) and energy harvesting technologies are two promising approaches to increase spectral and energy efficiency, respectively. In this paper, a pattern division multiple access (PDMA) uplink transmission network in which users are able to harvest energy from the received radio frequency power is considered. In order to maximize the energy efficiency, we perform resource allocation in the power, subcarrier, and time domains. Also, for each time slot, the pattern matrix is determined dynamically. To enhance the detection reliability, successive interference cancellation and maximal ratio combining at each receiver are utilized. For resource allocation, the actual harvested and available energies of the users are considered. Moreover, in order to perform a comprehensive analysis, further to PDMA, the energy efficiency of the power domain NOMA (PD-NOMA) is also investigated and the results are compared. It is shown that the energy efficiency and the average total transferred data of PDMA are higher than that of PD-NOMA.

show abstract

“…

E_{h, k m}^{t - 1}

is the amount of the harvested energy by the k ‐th user of the m ‐th RRH during slot t −1 which is obtained as follows:

\begin{align} E_{h, k m}^{t prefix- 1} = true \sum_{f = 1}^{M} false(1 prefix- α_{f} false) T {\overset{P}{true}}_{h, k m}^{f, t prefix- 1} φ_{k m}^{f}, \end{align}

where

φ_{k m}^{f}

is an assignment index,

φ_{k m}^{f}

is set to ‘1’ if the k ‐th user of the m ‐th RRH selects the f ‐th channel for energy harvesting. Also

{\hat{P}}_{k m}^{f, t - 1}

is the amount of harvesting power by the k ‐th user of the m ‐th RRH during slot t −1 from channel f , which is obtained as below:

\begin{align} {\overset{P}{true}}_{h, k m}^{f, t prefix- 1} = \frac{1}{4 R_{L}} ({}, {false(2 p_{k F}^{n} false| h_{k m}^{f} {false|}^{2} R_{a} false)}^{1 false/ 2} prefix- \frac{i V_{T}}{2} normalln ((), 2 π false(2 p_{k F}^{n} false| h_{k m}^{f} {false|}^{2} R_{a} false))) \end{align}

…”

Section: Problem Formulation For a Pdma‐based Systemmentioning

confidence: 99%

Energy efficient transmission in dynamic PDMA‐based systems with RF energy harvesting

Hooshiary

Azmi

Mokari

2020

Trans Emerging Tel Tech

Self Cite

View full text Add to dashboard Cite

show abstract

“…This section surveys the existing techniques and algorithms related to Hooshiary et al suggested an optimal channel selection mechanism for managing the network traffic in CRN. The main intention of this paper was to select the best possible channels for allocation.…”

Section: Related Workmentioning

confidence: 99%

IDsMA: An integrated digital signature and mutual authentication mechanism for securing the cognitive radio networks

Balamurugan

Kumar

2019

Int J Communication

View full text Add to dashboard Cite

Summary Enabling a reliable and secure communication in cognitive radio networks (CRNs) is one of the interesting and demanding research areas and these days, it is used in wide range of applications. The traditional works mainly aimed to improve the spectrum efficiency and bandwidth utilization of the CRN. Moreover, it focused on attack detection in the network for improving the reliability. Thus, this work intended to secure the CRN by considering the objectives of both attack detection and quality of service (QoS) improvement. For this purpose, an integrated digital signature and mutual authentication (IDsMA) mechanism is proposed in this paper, which incorporates the benefits of both security and reliability. Also, the Rivest‐Sharmir‐Adlemann (RSA) algorithm is utilized to encrypt and decrypt the data at the transmitter and receiver side. Here, the unique user ID is generated by the service eNodeB based on the hash function, which is validated at the server side for validating the authenticity of the user. Furthermore, the particle swarm optimization (PSO) and relevant vector machine (RVM) techniques are utilized for optimal channel selection and attack classification. The simulation results evaluate the performance of the proposed technique by using various performance measures. Also, its superiority is proved by comparing the proposed technique with the existing techniques.

show abstract

“…The multichannel selection was modeled as a convex optimization problem in [6], which maximized average throughput by controlling the channel selection probability. In [7], considering a realistic rectenna characteristic function, channels for energy harvesting and data transmission were selected simultaneously to improve system throughput. Multiple users were allowed to transmit on the same channel at the same time in [8] which judged the success of a transmission by the number of users access the same channel.…”

Section: Introductionmentioning

confidence: 99%

Weighted-Directed-Hypergraph-Based Spectrum Access for Energy Harvesting Cognitive Radio Sensor Network

Ren

Zhang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

In this paper, we investigate the spectrum access for energy harvesting cognitive radio sensor network (EH-CRSN), where sensor nodes (SNs) connected to different sinks share several channels. To maximize the sum of system energy efficiency (EE) and spectrum efficiency (SE), different from traditional works modeling the interference relationship by binary graph and unweighted hypergraph, we apply a novel weighted directed hypergraph (WDH) to accurately characterize the degree of interference among neighbor SNs and formulate the channel access problem in multi-sink network as a WDH game. We analyze the existence of Nash equilibrium (NE) and design a spectrum access algorithm to achieve the optimal solution which is one of NE. Moreover, simulation results are presented to verify the effectiveness of the proposed algorithm. INDEX TERMS Weighted directed hypergraph game, spectrum access, energy harvesting, cognitive radio, sensor network.

show abstract

Optimal channel selection for simultaneous RF energy harvesting and data transmission in cognitive radio networks

Cited by 10 publications

References 30 publications

Energy efficient transmission in dynamic PDMA‐based systems with RF energy harvesting

Energy efficient transmission in dynamic PDMA‐based systems with RF energy harvesting

IDsMA: An integrated digital signature and mutual authentication mechanism for securing the cognitive radio networks

Weighted-Directed-Hypergraph-Based Spectrum Access for Energy Harvesting Cognitive Radio Sensor Network

Contact Info

Product

Resources

About