Impacts of Sensing Energy and Data Availability on Throughput of Energy Harvesting Cognitive Radio Networks

Liu, Xiaoying; Xu, Bin; Wang, Xiong; Zheng, Kechen; Chi, Kaikai; Tian, Xianzhong

doi:10.1109/tvt.2022.3204310

Cited by 42 publications

(39 citation statements)

References 33 publications

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“…Performance has been carried out through MATLAB simulation in a PC with specification: Intel(R) Core (TM); i5‐5200U; CPU @ 2.20 GHz; 8 GB RAM. In Table 2, values of the parameters for simulation are considered 22 …”

Section: Resultsmentioning

confidence: 99%

Throughput analysis in censoring‐based cooperative cognitive radio network with energy harvesting

Das

Saha

Bhowmick

et al. 2023

Int J Communication

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Summary An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.

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Section: Resultsmentioning

confidence: 99%

Throughput analysis in censoring‐based cooperative cognitive radio network with energy harvesting

Das

Saha

Bhowmick

et al. 2023

Int J Communication

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“…With the rapid development of intelligent transportation systems, the explosive growth of vehicular communication services has led to the shortage of radio spectrum resources for vehicular network communications [ 1 , 2 ]. Cognitive radio-enabled vehicular networks can provide additional spectrum resources for vehicular communications; thus, they have the potential to be widely adopted in many scenarios, such as road transportation, railway transportation, aerospace, as well as military fields [ 3 , 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

A High-Precision Vehicle Detection and Tracking Method Based on the Attention Mechanism

Wang

Dong

Zhao

et al. 2023

Sensors

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Vehicle detection and tracking technology plays an important role in intelligent transportation management and control systems. This paper proposes a novel vehicle detection and tracking method for small target vehicles to achieve high detection and tracking accuracy based on the attention mechanism. We first develop a new vehicle detection model (YOLOv5-NAM) by adding the normalization-based attention module (NAM) to the classical YOLOv5s model. By exploiting the YOLOv5-NAM model as the vehicle detector, we then propose a real-time small target vehicle tracking method (JDE-YN), where the feature extraction process is embedded in the prediction head for joint training. Finally, we present extensive experimental results to verify our method on the UA-DETRAC dataset and to demonstrate that the method can effectively detect small target vehicles in real time. It is shown that compared with the original YOLOv5s model, the mAP value of the YOLOv5-NAM vehicle detection model is improved by 1.6%, while the MOTA value of the JDE-YN method improved by 0.9% compared with the original JDE method.

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“…In order to alleviate the contradiction between the increasing demand of wireless services and the shortage of spectrum resources, cognitive radio (CR) technology has been proposed [2]. In CR network, secondary users (SUs) are allowed to use the licensed spectrum of primary network, which can accommodate more users over scarce spectrum resources [3][4][5][6][7][8]. Secondary network can assess the authorized spectrum of PU in three modes of the overlay, the underlay and the interweave [9].…”

Section: Introductionmentioning

confidence: 99%

On the outage probability of energy harvested cooperative multiuser cognitive NOMA network

et al. 2023

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This paper investigates a multiple users cooperative cognitive non‐orthogonal multiple access (NOMA) network with energy harvesting. Primary transmitter and secondary sources serving as energy‐constrained nodes harvest energy from the power beacon PBS. In primary network, primary transmitter sends signals towards primary receiver. In order to make full use of spectrum resources, the secondary network access the licensed spectrum of primary network with overlay mode, where the best secondary source with maximum transmission signal‐to‐noise ratio between primary transmitter and secondary sources act as relays to forward signal via NOMA principle. In this context, two cooperative transmission protocols, namely, traditional NOMA cooperative transmission and adaptive NOMA cooperative transmission are proposed. For NOMA cooperative transmission, relays use NOMA to forward the superimposed signal of primary signal and secondary signal without any constrain. However, for adaptive NOMA cooperative transmission, relays use NOMA by judging whether the transmission between primary transmitter and primary receiver is successful or not. Primary receiver merges signals received from two transmission slots by selection combining. Finally, exact and asymptotic outage probability of primary network and secondary network with two cooperative transmissions are derived and simulated. It is shown that outage performance is improved for the proposed adaptive NOMA cooperative transmission.

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Impacts of Sensing Energy and Data Availability on Throughput of Energy Harvesting Cognitive Radio Networks

Cited by 42 publications

References 33 publications

Throughput analysis in censoring‐based cooperative cognitive radio network with energy harvesting

Throughput analysis in censoring‐based cooperative cognitive radio network with energy harvesting

A High-Precision Vehicle Detection and Tracking Method Based on the Attention Mechanism

On the outage probability of energy harvested cooperative multiuser cognitive NOMA network

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