Dynamic decision-based spectrum sharing framework for next-generation (5G) systems

Z. Sadreddini, Pavel Mašek, Tugrul Çavdar, Jiri Hosek, Erkan Guler
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引用次数: 1

Abstract

Looking into the concept of next-generation (5G) cellular systems, it is necessary to do a revision of existing radio spectrum management techniques and come up with more flexible solutions. A new wave of spectrum policy reforms can be envisaged with a direction shift from static to dynamic optimization. According to the peak hours, the number of served users in mobile networks is increasing. Since the radio spectrum is limited, cognitive radio (CR) technology provides an opportunity to recognize under-utilized cellular spectrum (licensed band) resources. To this end, efficient spectrum management techniques based on CR technology should be implemented to share the spectrum between different types of users in order to maximize spectrum utilization and spectral efficiency. In this work, we present dynamic decision-based spectrum sharing model among multiple classes of users in CR network (CRN) in order to increase network utilization and the quality of experience (QoE) by increasing the users' satisfaction. Obtained simulation results from created toolkit in Matlab tool (calibrated by data set from real 3GGP LTE-Advanced system) show the performance of the developed model and appropriate user selection among multiple users' types.
下一代(5G)系统的动态决策频谱共享框架
考虑到下一代(5G)蜂窝系统的概念,有必要对现有的无线电频谱管理技术进行修订,并提出更灵活的解决方案。新一轮频谱政策改革将从静态优化转向动态优化。根据高峰时段,移动网络的服务用户数量正在增加。由于无线电频谱有限,认知无线电(CR)技术为识别未充分利用的蜂窝频谱(许可频带)资源提供了机会。为此,需要实施基于CR技术的高效频谱管理技术,实现不同类型用户之间的频谱共享,实现频谱利用率和效率的最大化。为了通过提高用户满意度来提高网络利用率和体验质量,本文提出了基于动态决策的CR网络(CRN)多类别用户频谱共享模型。在Matlab工具中创建的工具包中获得的仿真结果(通过实际3GGP LTE-Advanced系统的数据集进行校准)显示了所开发模型的性能和在多种用户类型中合理的用户选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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