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Spectral efficient compressive transmission framework for wireless communication systems

机译:用于无线通信系统的光谱有效压缩传输框架

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摘要

Increasing demand of high-speed data rate is leading to a challenging task to provide services to the users within exponentially growing market for wireless multimedia services. Subsequently, the available radio resources are becoming scarce because of different factors such as spectrum segmentation and dedicated frequency allocation to existing wirelessstandards. Exploring new techniques for enhancing the spectral efficiency in wireless communication has been an importantresearch challenge. In this study, the enhancement of spectral efficiency of wireless communication systems is considered. A framework is proposed to implement the concept of compressive sampling (CS) for compressing the natural random signals.The performance of proposed framework is evaluated in the context of multiple input multiple output orthogonal frequencydivision multiplexing system. Simulation-based results show that 25% of resources can be saved by marginal trade-off with the quality of service (QoS) requirement applying CS to the natural random signals. Furthermore, it can be claimed that this QoS trade-off can be optimised with dynamic selection of random measurement matrices.
机译:越来越多的高速数据速率的需求导致有挑战性的任务,为用户提供对无线多媒体服务市场的指数增长市场中的服务。随后,由于诸如频谱分割和专用频率分配的不同因素,可用的无线电资源正在变得稀缺,例如对现有的无线标准。探索用于增强无线通信频谱效率的新技术一直是重要的研究挑战。在本研究中,考虑了无线通信系统的频谱效率的增强。提出了一种框架来实现用于压缩自然随机信号的压缩采样(CS)的概念。在多输入多输出正交频率多路复用系统的上下文中评估所提出的框架的性能。基于仿真结果表明,25%的资源可通过利用服务质量(QoS)要求将CS应用于自然随机信号的资质来节省。此外,可以声称可以通过随机测量矩阵的动态选择优化该QoS权衡。

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