基于混合模式crn的服务完成概率增强与服务公平性

A. Khan, G. Abbas, Z. Abbas, M. Waqas, Shanshan Tu, Alamgir Naushad
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引用次数: 2

摘要

认知无线电网络(crn)通过允许二级用户(su)使用许可频谱,有望在稀缺频谱内容纳数十亿物联网(IoT)设备。然而,设备需要不间断通信,这是传统crn无法满足的。这就需要在crn中提高成功服务完成概率(SSCP)。此外,在使用网络服务方面,维护系统之间的公平性是确保网络服务公平地提供给所有系统的一个考虑事项。本文提出了一种混合CRN (HCRN)方案来分析这两个问题。首先,我们利用crn的混合底层交织模式研究了SSCP增强,并提出了一种支持中断用户的动态信道保留算法。其次,我们提出了一种基于多属性的公平性驱动的信道中断判定算法(MFD),该算法保证了单元间在使用网络服务时的公平性。利用连续时间马尔可夫链进行建模,推导了SSCP的数学表达式。在不同的网络流量负载和信道故障率下对该方案进行了评估。数值结果表明,与基准相比,SSCP有显著改善,强制终止率降低。同样,MFD算法在公平性方面也有显著的提高。
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Service Completion Probability Enhancement and Fairness for SUs using Hybrid Mode CRNs
Cognitive radio networks (CRNs) promise to accommodate billions of Internet of Things (IoT) devices within scarce spectrum by allowing secondary users (SUs) to use licensed spectrum. However, the devices need uninterruptible communication, which the conventional CRNs cannot fulfill. This necessitates successful service completion probability (SSCP) enhancement in CRNs. Further, maintaining fairness among SUs, in terms of availing network services, is a matter of consideration for ensuring the network services to be fairly available to all SUs. In this paper, we propose a hybrid CRN (HCRN) scheme to analyze two problems. Firstly, we investigate SSCP enhancement by utilizing hybrid underlay-interweave mode of CRNs and propose a dynamic channel reservation algorithm to support interrupted users. Secondly, we propose a multi-attributes based fairness-driven channel determination (MFD) algorithm for channel interruption, which ensures fairness among SUs in availing network services. Furthermore, continuous-time Markov chain is used for modelling, and mathematical formulations are derived for SSCP. The proposed scheme is evaluated under various network traffic loads and channel failure rates. Numerical results show significant improvement in SSCP and reduction in forced termination rate as compared to the benchmark. Similarly, the MFD algorithm brings a prominent improvement in fairness.
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