Analysis of Efficient Spectrum Handoff in a Multi-Class Hybrid Spectrum Access Cognitive Radio Network Using Markov Modelling

Shakeel, Atif; Hussain, Riaz; Iqbal, Adeel; Khan, Irfan Latif; Hasan, Qadeer Ul; Malik, Shahzad A.

doi:10.3390/s19194120

Cited by 19 publications

(12 citation statements)

References 37 publications

(47 reference statements)

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“…For performance detection, the average power of each node in a given cluster is under consideration. To connect with the base station, CRSN's size is critical [36]. The SNR estimation for detecting a received signal and determining the response from detection results using spectrum sensing methods.…”

Section: Sus Node Powermentioning

confidence: 99%

Assessment of Dynamic Swarm Heterogeneous Clustering in Cognitive Radio Sensor Networks

Bhatt

Onyema

Almuzaini

et al. 2022

Wireless Communications and Mobile Computing

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Many optimization algorithms have been created to determine the most energy-efficient transmission mode, allowing for lower power consumption during transmission over shorter distances while minimising interference from primary users (PUs). The improved cooperative clustering algorithm (ICCA) performs superior spectrum sensing across groups of multiusers compared to any other method currently available in terms of sensing inaccuracy, power savings, and convergence time than any other method currently available. The proposed ICCA algorithm is employed in this research study to find the optimal numbers of clusters based on its connectivity and the most energy-efficient distributed cluster-based sensing technique available. In this research, many randomly chosen secondary users (SUs) and primary users (PUs) are investigated for potential implementation opportunities. Therefore, as compared to the current optimization strategies, the proposed ICCA algorithm enhanced the convergence speed by integrating the multiuser clustered communication into a single communication channel. Experimental results revealed that the new ICCA algorithm reduced node power by 9.646 percent compared to traditional ways when comparing the novel algorithm to conventional approaches. In a similar vein, as compared to the prior methodologies, the ICCA algorithm reduced the average node power of SUs by 24.23 percent on average. When the SNR is decreased to values below 2 dB, the likelihood of detection improves dramatically, as seen in the figure. ICCA has a low false alarm rate when matched to other optimization algorithms for direct detection, and the proposed method outperforms them all. Following the findings of the simulations, the proposed ICCA technique effectively addresses multimodal optimization difficulties and optimizes network capacity performance in wireless networks. A detailed discussion of SS applications for the IoT and wireless sensor networks, both based on CR, is provided. There is also a thorough discussion of the most recent advancements in spectrum sensing as a facility. IoT or WSN may be essential in feeding the CR networks with spectrum sensing data and the future of spectrum sensing. The use of CR for fifth generation and afar its potential application in frequency allocation are discussed. To stay up with the advancement of communication technology, SS should give additional features to remain competitive, like the capacity to investigate various available channels and accessible places for transmission. Based on present and prospective methods in wireless communications, we highlight the crucial upcoming study paths and difficulty spots in signal processing for cognitive radio and potential solutions (SS-CR).

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Section: Sus Node Powermentioning

confidence: 99%

Assessment of Dynamic Swarm Heterogeneous Clustering in Cognitive Radio Sensor Networks

Bhatt

Onyema

Almuzaini

et al. 2022

Wireless Communications and Mobile Computing

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“…For switching spectrum handoff, cDUs will vacate their currently utilized channel and handoff to the next channel according to their already prepared target channel list. In non-switching spectrum handoff, on the arrival of CU, cDU will either reduce their transmit power which will reduce the data rate, or pause transmission and go into a waiting state until CU departs and the channel is free again [15]. The cDR-(5G-NR gNodeB) link will use a networkassisted D2D scheme to form a link between cellular and cD2D networks.…”

Section: Introductionmentioning

confidence: 99%

cDERSA: Cognitive D2D Enabled Relay Selection Algorithm to Mitigate Blind-Spots in 5G Cellular Networks

et al. 2021

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Blind-spots, where wireless signals do not reach within the coverage range, often emerge in a dynamic environment due to obstacles, geographical location or mobility of cellular users (CUs). Thus greatly reducing the overall system performance in terms of coverage and throughput. Relay-aided cognitive Device to Device (cD2D) communication system underlying the 5G cellular network can help mitigate blind-spots. Cognitive capability helps D2D users to acquire the spectrum opportunistically for proximity communication and establish a semi-independent network underlying the 5G network, which not only offloads 5G-New Radio (NR) base station but also enhances the overall system performance. In this work, we have developed a relay-aided cognitive D2D network that helps CUs falling into the blind-spots to retain access to the 5G network and increase wireless coverage. Relay selection requires mutual consent between the relay and the device in the blind-spot. The in-coverage devices are tempted to act as relays through incentive-based mechanism. For enhanced system performance a suitable match among the devices in blind-spots and the relays is required. cD2D enabled relay selection algorithm (cDERSA) is proposed in this work, in which a cognitive D2D user (cDU), which is a CU falling in the blind-spot, establishes a relayed cD2D link to access 5G-NR gNodeB. All cDUs as well as the tempted relays, i.e. cognitive D2D relays (cDRs), first scan their surroundings for devices capable of D2D communication and based on multicriteria objective functions, build a priority table . A stable marriage problem is formulated and solved using a unique, stable, distributed, and efficient matching algorithm based on the Gale-Shapley algorithm. A new incentive mechanism is also developed to keep relays motivated to share their resources. Simulation is performed and their results show improvement in throughput and average user satisfaction, which validates our proposed cDERSA.

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“…This requires additional functionality of spectrum handover or spectrum mobility as the primary user appears on the channel being opportunistically used by the CRN user. A wide range of techniques have been deployed for spectrum handover such as bioinspired techniques [6], Markov modeling [7], and supervised machine learning techniques [8].…”

Section: Introductionmentioning

confidence: 99%

Self‐Organized Efficient Spectrum Management through Parallel Sensing in Cognitive Radio Network

Rahim

Hussain

Khan

et al. 2021

Wireless Communications and Mobile Computing

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In this paper, we propose an innovative self-organizing medium access control mechanism for a distributed cognitive radio network (CRN) in which utilization is maximized by minimizing the collisions and missed opportunities. This is achieved by organizing the users of the CRN in a queue through a timer and user ID and providing channel access in an orderly fashion. To efficiently organize the users in a distributed, ad hoc network with less overhead, we reduce the sensing period through parallel sensing wherein the users are divided into different groups and each group is assigned a different portion of the primary spectrum band. This consequently augments the number of discovered spectrum holes which then are maximally utilized through the self-organizing access scheme. The combination of two schemes augments the effective utilization of primary holes to above 95%, even in impasse situations due to heavy primary network loading, thereby achieving higher network throughput than that achieved when each of the two approaches are used in isolation. By efficiently combining parallel sensing with the self-organizing MAC (PSO-MAC), a synergy has been achieved that affords the gains which are more than the sum of the gains achieved through each one of these techniques individually. In an experimental scenario with 50% primary load, the network throughput achieved with combined parallel sensing and self-organizing MAC is 50% higher compared to that of parallel sensing and 37% better than that of self-organizing MAC. These results clearly demonstrate the efficacy of the combined approach in achieving optimum performance in a CRN.

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Analysis of Efficient Spectrum Handoff in a Multi-Class Hybrid Spectrum Access Cognitive Radio Network Using Markov Modelling

Cited by 19 publications

References 37 publications

Assessment of Dynamic Swarm Heterogeneous Clustering in Cognitive Radio Sensor Networks

Assessment of Dynamic Swarm Heterogeneous Clustering in Cognitive Radio Sensor Networks

cDERSA: Cognitive D2D Enabled Relay Selection Algorithm to Mitigate Blind-Spots in 5G Cellular Networks

Self‐Organized Efficient Spectrum Management through Parallel Sensing in Cognitive Radio Network

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