Approach of Robust Resource Allocation in Cognitive Radio Network With Spectrum Leasing

Liu, Zhixin; Zhao, Mingye; Chan, Kit Yan; Yuan, Yazhou; Guan, Xinping

doi:10.1109/tgcn.2020.2988975

Cited by 10 publications

(6 citation statements)

References 35 publications

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“…A neural network based solution was proposed to determine the optimal transmission policy that would result in minimal spectrum leasing cost while considering the QoS of the CRN. The works in [20] and [21] considered the problem of resource allocation and spectrum leasing in CRNs where the PUs lease part of their spectrum to the SUs in exchange for data transmission assistance from the SUs as well energy saving for the PUs. Joint cell switching and spectrum leasing has been considered in [23] and [24] to maximize the profit of both PN and SN as well as to minimize the energy consumption of PN.…”

Section: Related Workmentioning

confidence: 99%

Revenue Maximization Through Cell Switching and Spectrum Leasing in 5G HetNets

Abubakar

Öztürk

et al. 2022

IEEE Access

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Even though dynamic cell switching is a prominent approach for energy optimization in heterogeneous wireless communication networks, it results in spectrum under-utilization as the spectrum originally occupied by the base stations that are turned off remain dormant. In order to make the businesses of primary network (PN) operators, who hold the spectrum license, more profitable and sustainable as well as to avoid spectrum under-utilization, this dormant spectrum can be leased to the secondary network (SN) operators who cannot afford to purchase the spectrum license. In this study, first, the cell switching problem, which solely focuses on the amount of energy saved, is translated to a problem of revenue maximization by including the spectrum leasing concept and converting the energy saving to monetary saving from reduced electricity bills. In this regard, two spectrum demand scenarios are considered for the SN operator: delay tolerant (DT), for non-real time applications, and non-delay tolerant (NDT), for real time applications. Then, a cell switching and spectrum leasing framework based on simulated annealing algorithm is developed to maximize the revenue of the PN while respecting the quality-of-service constraints. The simulation results reveal that the DT spectrum demand is more beneficial to both PN and SN operators as it results in greater revenue for the former while the latter is able to access more spectrum to meet higher service demands. This finding suggests that if the application can tolerate delays, then it makes more sense for both PN and SN to adopt the DT scenario. In addition, it is observed that the performance of the proposed framework is very close to that of the optimal solution with a significant reduction in the computation complexity.INDEX TERMS 5G, HetNet, cell switching, energy efficiency, green communications, spectrum leasing, simulated annealing algorithm.

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Section: Related Workmentioning

confidence: 99%

Revenue Maximization Through Cell Switching and Spectrum Leasing in 5G HetNets

Abubakar

Öztürk

et al. 2022

IEEE Access

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“…A neural network based solution was proposed to determine the optimal transmission policy that would result in minimal spectrum leasing cost while considering the QoS of the CRN. The works in [19] and [20] considered the problem of resource allocation and spectrum leasing in CRNs where the PUs lease part of their spectrum to the SUs in exchange for data transmission assistance from the SUs as well energy saving for the PUs.…”

Section: Related Workmentioning

confidence: 99%

“…However, it focuses on specific regions in the search space in the final stages. The probability of increase at temperature, T (in Kelvin), of δE amplitude in energy is presented in (20), where K is Boltzman constant:…”

Section: A Simulated Annealing (Sa) Algorithmmentioning

confidence: 99%

Revenue Maximization through Cell Switching and Spectrum Leasing in 5G HetNets

Abubakar¹,

Öztürk²,

Öztürk³

et al. 2021

Preprint

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One of the ways of achieving improved capacity in mobile cellular networks is via network densification. Even though densification increases the capacity of the network, it also leads to increased energy consumption which can be curbed by dynamically switching off some base stations (BSs) during periods of low traffic. However, dynamic cell switching has the challenge of spectrum under-utilization as the spectrum originally occupied by the BSs that are turned off remains dormant. This dormant spectrum can be leased by the primary network (PN) operators, who hold the license, to the secondary network (SN) operators who cannot afford to purchase the spectrum license. Thus enabling the PN to gain additional revenue from spectrum leasing as well as from electricity cost savings due to reduced energy consumption. Therefore, in this work, we propose a cell switching and spectrum leasing framework based on simulated annealing (SA) algorithm to maximize the revenue of the PN while respecting the quality-of-service constraints. The performance evaluation reveals that the proposed method is very close to optimal exhaustive search method with a significant reduction in the computation complexity.

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“…Meanwhile, SUs use the residual idle subchannels to transmit their data. Considering the channel gain uncertainty, Liu et al proposed an optimal resource allocation algorithm with probability constrained in Reference 33. By classifying SU, Xu et al proposed power allocation within a cluster by using the Karush‐Kuhn‐Tucker optimality condition in Reference 34.…”

Section: Introductionmentioning

confidence: 99%

Joint spectrum sensing and resource allocation against byzantine attack in overlay cognitive radio networks

Gan

et al. 2022

Trans Emerging Tel Tech

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Cognitive radio (CR) technology has emerged as a viable solution to solve the dilemma of spectrum scarcity and underutilization. It allows secondary users (SUs) to opportunistically access the primary user (PU) channel. Cooperative spectrum sensing (CSS) further improves the accuracy of detecting spectrum availability by exploiting spatial diversity gain. However, the open nature of CR networks (CRNs) makes CSS process be prone to Byzantine attack, resulting in the excessive interference to the PU and the waste of spectrum resources. To this end, we propose a joint spectrum sensing and resource allocation scheme to defend against Byzantine attack. Specifically, we develop a probabilistic Byzantine attack model to characterize attack behaviors from malicious users (MUs) and evaluate its negative impact on the CSS performance. Then, the delivery evaluation mechanism is designed to evaluate the sensing performance of SUs and distinguish between normal users and MUs. Based on this, we propose a selection-majority algorithm to improve CSS performance by exploiting sensing reports from MUs. To further solve the Byzantine attack, we propose a spectrum resource allocation algorithm, which allocates corresponding spectrum resources according to the historical behavior of SUs. By reducing the resources allocated to poorly performing SUs, this scheme incentivizes them to report correct sensing results and drive MUs to stop attacking or leave CRN. Extensive simulation results corroborate the correctness and effectiveness of our theoretical analysis and show that our proposed scheme can effectively resist Byzantine attack.

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Approach of Robust Resource Allocation in Cognitive Radio Network With Spectrum Leasing

Cited by 10 publications

References 35 publications

Revenue Maximization Through Cell Switching and Spectrum Leasing in 5G HetNets

Revenue Maximization Through Cell Switching and Spectrum Leasing in 5G HetNets

Revenue Maximization through Cell Switching and Spectrum Leasing in 5G HetNets

Joint spectrum sensing and resource allocation against byzantine attack in overlay cognitive radio networks

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