Efficient Spectral Allocation for Cognitive Full Duplex Relay Network Systems Based Soft Computing Technique

C. Senthamarai, N. Malmurugan
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引用次数: 1

Abstract

Due to the huge development of wireless devices and mobile data traffic had gained attention towards identifying accurate solutions for more proficient utilization of the wireless spectrum. An essential issue confronting the future in wireless systems is to identify the appropriate spectrum bands to satisfy the request of future administrations. While the greater part of the radio spectrum is allocated to various services, applications and users show that spectrum usage is quite low. The spectrum sensing is performed at the start of each time slot before the data transmission. As a promising framework to improve the spectrum utilization, Cognitive Radio (CR) technique has the immense potential to meet such a necessity by permitting unlicensed users to exist together in licensed bands. In this paper Cognitive radio and Full-Duplex (FD) based two-way relay communications are developed to enhance spectrum utilization for multichannel and to decrease the false alarm rate. To solve the optimization problems in spectral efficiency, soft computing techniques is proposed to minimize the self-interference and delay to the licensed users. In this proposed work the kurtosis parameter is used for channel detection to determine whether the signal is present or not. The performance results of the proposed method are evaluated in terms of spectral allocation and outage probability which achieves better performance than the existing Multi- Objective Genetic Algorithm (MOGA) optimization.
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基于软计算技术的认知全双工中继网络系统的有效频谱分配
由于无线设备和移动数据业务的巨大发展,人们开始关注确定准确的解决方案,以更熟练地利用无线频谱。未来无线系统面临的一个重要问题是确定合适的频段以满足未来管理部门的要求。虽然大部分无线电频谱被分配给各种服务,但应用程序和用户表明频谱使用率相当低。频谱感测在数据传输之前的每个时隙的开始处执行。作为提高频谱利用率的一个很有前途的框架,认知无线电(CR)技术具有巨大的潜力,可以通过允许未经许可的用户一起存在于许可的频带中来满足这一需求。本文开发了基于认知无线电和全双工(FD)的双向中继通信,以提高多信道的频谱利用率,降低误报率。为了解决频谱效率的优化问题,提出了软计算技术,以最大限度地减少对授权用户的自干扰和延迟。在这项提出的工作中,峰度参数用于信道检测,以确定信号是否存在。根据频谱分配和中断概率对所提出方法的性能结果进行了评估,该方法比现有的多目标遗传算法(MOGA)优化取得了更好的性能。
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来源期刊
CiteScore
1.70
自引率
0.00%
发文量
18
审稿时长
>12 weeks
期刊介绍: In recent years a breakthrough has occurred in our understanding of the molecular pathomechanisms of human diseases whereby most of our diseases are related to intra and intercellular communication disorders. The concept of signal transduction therapy has got into the front line of modern drug research, and a multidisciplinary approach is being used to identify and treat signaling disorders. The journal publishes timely in-depth reviews, research article and drug clinical trial studies in the field of signal transduction therapy. Thematic issues are also published to cover selected areas of signal transduction therapy. Coverage of the field includes genomics, proteomics, medicinal chemistry and the relevant diseases involved in signaling e.g. cancer, neurodegenerative and inflammatory diseases. Current Signal Transduction Therapy is an essential journal for all involved in drug design and discovery.
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