Robust resource allocation for orthogonal frequency division multiplexing‐based cooperative cognitive radio networks with imperfect channel state information

Yang, Weiwei; Zhao, Xiaohui

doi:10.1049/iet-com.2016.0742

Cited by 16 publications

(8 citation statements)

References 29 publications

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“…(4) Determine gbest of the swarm from the total pbest value. (5) Update the velocity and position of every particle using (13) and (14). (6) Update the generation number using t � t + 1.…”

Section: Optimal Location and Operating Channel Selection Of A Secondmentioning

confidence: 99%

“…In fact, how to improve resource allocation using a dynamic allocation policy in a CRN has always been a hot research area. Yang and Zhao [13] proposed a heuristic, robust, relay selection scheme and formulated robust power allocation as a semi-infinite program to maximize capacity while ensuring that interference with primary users is below a predefined interference threshold. Tiwari and Saha [14] presented a particle swarm optimization-(PSO-) based, cochannel interferenceconstrained, efficient, and low-complexity novel spectrum allocation scheme with simultaneous power and network capacity optimization.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Cognitive Radio Secondary Information Gathering Station Positioning and Operating Channel Selection for IoT Sensor Networks

Jinyi

Yang

Yoo

2018

Mobile Information Systems

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e Internet of ings (IoT) is the interconnection of different objects through the internet using different communication technologies. e objects are equipped with sensors and communications modules. e cognitive radio network is a key technique for the IoT and can effectively address spectrum-related issues for IoT applications. In our paper, a novel method for IoT sensor networks is proposed to obtain the optimal positions of secondary information gathering stations (SIGSs) and to select the optimal operating channel. Our objective is to maximize secondary system capacity while protecting the primary system. In addition, we propose an appearance probability matrix for secondary IoT devices (SIDs) to maximize the supportable number of SIDs that can be installed in a car, in wearable devices, or for other monitoring devices, based on optimal deployment and probability. We derive fitness functions based on the above objectives and also consider signal to interference-plus-noise ratio (SINR) and position constraints. e particle swarm optimization (PSO) technique is used to find the best position and operating channel for the SIGSs. In a simulation study, the performance of the proposed method is evaluated and compared with a random resources allocation algorithm (parts of this paper were presented at the ICTC2017 conference (Wen et al., 2017)).

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Section: Optimal Location and Operating Channel Selection Of A Secondmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Cognitive Radio Secondary Information Gathering Station Positioning and Operating Channel Selection for IoT Sensor Networks

Jinyi

Yang

Yoo

2018

Mobile Information Systems

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“…However, without comprehensive cognitive capability, IoT is just like an awkward stegosaurus, all brawn and no brains. To fulfill its potential and deal with growing Li et al [4] Low -Good ---High Hong et al [5] Low ---Low --Baloch et al [6] Low -Poor -High Better -Zhu et al [7] Low --High -Good -Yang et al [8] Low -Good ----Bhardwaj et al [9] Low -Good High -Good Low Chen et al [10] Low Better -High --High Naser et al [11] Low ---Low --Feng et al [12] ---Low -Better - • used in developing resource constrained devices • useful for embedded system developers challenges, we must take the cognitive capability into consideration and empower IoT with high-level intelligence, i.e., brain-empowered IoT or CIoT. In this paper, we have analyzed some measures like energy consumption, network life time, resource allocation, throughput, time duration, quality of service and delay researched by various authors (Table 1).…”

Section: Introductionmentioning

confidence: 99%

A Survey on Data Perception in Cognitive Internet of Things

Bhajantri¹,

Balugari

2019

JTIT

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A Cognitive Internet of Things (CIoT) is a brand of Internet of Things (IoT) with cognitive and agreeable mechanisms, which are incorporated to advance performance and accomplish insights into real world environments. CIoT can perceive present system’s conditions, analyze the apparent information, make smart choices, and increase the network performance. In this survey paper, we present classiﬁcations of data perception techniques used in CIoT. This paper also compares the data perception works against energy consumption, network life-time, resource allocation, and throughput, as well as quality of data and delay. In addition, simulation tools for IoT and their performance are discussed. Finally, we provide the model of cognitive agent-based data perception in CIoT for future research and development, which ensures the network performance in terms of reliability, energy eﬃcient, accuracy, scalable, fault tolerant, and quality of data.

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“…In CRT Based Scheme, key is established in an efficient way for node addition, node compromise and also at regular intervals. The communication cost incurred at each node for establishing key is one receive operation and computation cost incurred is one modulus operation and one EX-OR operation by each node [11][12]. A deployment conscious security framework supporting, a shift of complex operations to more capable nodes of heterogeneous environment and relieving resource constrained generic sensor nodes of major activities is introduced in [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Secured communications in cognitive radio networks

Perarasi¹,

Nagarajan²

2018

AMA_D

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Enabling end to end secure communications between source and sink is significant for many Cognitive Radio Networks (CRNs). While there have been many works devoted to hop by hop secure communications, the issue of end to end secure communications is largely ignored. In this paper, an end to end secure communication protocol in randomly deployed CRNs is designed. Specifically; this protocol is based on a methodology called differentiated key pre-distribution. The core idea is to distribute different number of keys to different nodes to enhance the resilience of certain links. This feature is leveraged during routing, where users route through those links with higher resilience. Using rigorous theoretical analysis, an expression for the quality of end to end secure communications is derived and uses it to determine optimum protocol parameters. Extensive performance evaluation illustrates that the proposed solution can provide highly secure communications between relays and sink in randomly deployed CRNs.

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Robust resource allocation for orthogonal frequency division multiplexing‐based cooperative cognitive radio networks with imperfect channel state information

Cited by 16 publications

References 29 publications

Optimization of Cognitive Radio Secondary Information Gathering Station Positioning and Operating Channel Selection for IoT Sensor Networks

Optimization of Cognitive Radio Secondary Information Gathering Station Positioning and Operating Channel Selection for IoT Sensor Networks

A Survey on Data Perception in Cognitive Internet of Things

Secured communications in cognitive radio networks

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