Novel spectrum sensing and access in cognitive radio networks

Zhang, Shibing; Hu, Yingdong; Zhang, Li; Bao, Zhihua

doi:10.1007/s11432-017-9282-2

Cited by 12 publications

(7 citation statements)

References 6 publications

(7 reference statements)

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“…Fan et al considered radio frequency energy harvesting FD CRNs, which uses CSS to increase the sensing results. Zhang et al proposed novel SS and access approach to resolve the negation between the sensing time and throughput, which works simultaneously.…”

Section: Literature Reviewmentioning

confidence: 99%

BLSBA‐ED‐SSO: Bivariate Lévy‐stable bat algorithm‐based energy detection for spectrum sensing optimization in cognitive radio networks (CRNs)

Babu¹,

Venkataramanan²

2020

Int J Communication

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The vacant licensed spectrum can be employed by the secondary users in cognitive radio networks. Nevertheless, this process of identification is frequently agreed with shadowing, multipath fading and receiver uncertainty problems. The primary contributions of the spectrum sensing techniques adopted in this work mainly concentrate on energy detection for spectrum sensing as well as to recognize the optimal spectral estimation according to the multitaper spectral estimation. The algorithm proposed in this work is based on bivariate Lévy-stable bat algorithm (BLSBA), energy detector (ED), and with the help of K out of M fusion rule; it is analysed for the single user as well as cooperative multiple users. In the BLSBA algorithm, a modified search equation with more helpful information from the search experiences is brought-in to create an optimal energy solution and bivariate Lévy-stable random walk is associated with BLSBA to remove the trapping process into local optima. The energy detection is defined numerically from this optimal detection. At last, a multi-taper spectral estimator (MSE) is proposed to cognitive radio detection for a huge network. The simulation results in both cases are computed and checked with the help of a BLSBA optimizer. For an individual secondary user scenario, the advancement of MSE to the ED is broadly described. Experimental result indicates that the objective false alarm likelihood is minimized and the demanded signal-to-noise ratio is accomplished to the extent. INDEX TERMSbivariate Lévy-stable bat algorithm (BLSBA)cognitive radio networks (CRNs); energy detector (ED)multitaper spectral estimator (MSE)optimizationspectrum sensing

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Section: Literature Reviewmentioning

confidence: 99%

BLSBA‐ED‐SSO: Bivariate Lévy‐stable bat algorithm‐based energy detection for spectrum sensing optimization in cognitive radio networks (CRNs)

Babu¹,

Venkataramanan²

2020

Int J Communication

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“…In the coming 5G or even 6G era, the satellite communication network is regarded as the most important part of the integrated network [2][3][4][5]. The practice has shown that widely deployed integrated terrestrial-satellite networks, along with emerging techniques, such as MIMO (Multiple-input Multiple-Output) [6], OFDM (orthogonal frequency division multiplexing) [7], and cognitive radio (CR) [8], can promote the performance of communication and provide satisfactory services for the growing number of terminals within limited resources.…”

Section: Introductionmentioning

confidence: 99%

A CLSTM and transfer learning based CFDAMA strategy in satellite communication networks

Xiang

Ren

2021

PLoS ONE

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With the development of the economy and technology, people’s requirement for communication is also increasing. Satellite communication networks have been paid more and more attention because of their broadband service capability and wide coverage. In this paper, we investigate the scheme of convolutional long short term memory (CLSTM) network and transfer learning (TL) based combined free/demand assignment multiple access (CFDAMA) scheme (CFDAMA-CLSTMTL), which is a new multiple access scheme in the satellite communication networks. Generally, there is a delay time T between sending a request from the user to the satellite and receiving a reply from the satellite. So far, the traditional multiple access schemes have not processed the data generated in this period. So, in order to transmit the data in time, we propose a new prediction method CLSTMTL, which can be used to predict the data generated in this period. We introduce the prediction method into the CFDAMA scheme so that it can reduce data accumulation by the way of sending the slots request which is the sum of slots requested by the user and the predicted slots generated in the delay time. A comparison with CFDAMA-PA and CFDAMA-PB is provided through simulation results, which gives the effect of the CFDAMA-CLSTMTL in a satellite communication network.

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“…Cognitive radio (CR) is yet another key technology that addresses the spectrum scarcity problem by squeezing secondary users (SUs) into licensed bands [30]. A novel joint spectrum sensing and access technique with interference cancellation for a CR network is proposed in [31]. Here, the cognitive user achieves greater throughput by a full duplex spectrum sensing technique, that is, one that simultaneously transmits its signal while sensing the spectrum.…”

Section: Introductionmentioning

confidence: 99%

Throughput maximization for underlay CR multicarrier NOMA network with cooperative communication

2020

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The non‐orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi‐carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.

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Novel spectrum sensing and access in cognitive radio networks

Cited by 12 publications

References 6 publications

BLSBA‐ED‐SSO: Bivariate Lévy‐stable bat algorithm‐based energy detection for spectrum sensing optimization in cognitive radio networks (CRNs)

BLSBA‐ED‐SSO: Bivariate Lévy‐stable bat algorithm‐based energy detection for spectrum sensing optimization in cognitive radio networks (CRNs)

A CLSTM and transfer learning based CFDAMA strategy in satellite communication networks

Throughput maximization for underlay CR multicarrier NOMA network with cooperative communication

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