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arXiv 1406.7620cs.ITmath.IT
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多用户MISO认知网络中频谱感知与频谱均衡的联合优化

Joint Optimization of Spectrum Sensing and Accessing in Multiuser MISO Cognitive Networks

Xiaoming Chen, Chau Yuen

摘要:

提出了一种多用户认知网络联合频谱感知和接入优化框架,以显著提高频谱利用率。对于这样一个认知网络,有两个重要的和有限的资源,应该在一个全面的方式分配,即反馈比特和时间持续时间。首先,关于反馈比特,存在两个组件:感测组件(用于传送各个用户的感测结果)和接入组件(用于反馈信道状态信息)。一个大的感知组件可以支持更多的用户进行协作感知,这导致高的感知精度。然而,大的接入组件也是优选的,因为当利用诸如迫零波束成形(ZFBF)的多天线技术时,它对多用户认知网络中的性能具有直接影响。其次,需要确定传输间隔中的感测和接入持续时间的折衷,使得在满足干扰约束的同时优化总传输速率。此外,上述两种资源在一定条件下是相互关联、相互转化的。具体地,对于给定的性能目标,可以通过利用更多的感测反馈比特来节省感测时间。因此,资源应以联合方式分配。基于联合优化框架和两种资源之间的内在关系,提出了两种多用户多天线认知网络中以最大化平均和传输速率为目标的联合资源分配方案。仿真结果表明,采用联合资源分配策略,与传统的固定策略相比,可以获得明显的性能增益。

英文摘要:

In this paper, a joint spectrum sensing and accessing optimization framework for a multiuser cognitive network is proposed to significantly improve spectrum efficiency. For such a cognitive network, there are two important and limited resources that should be distributed in a comprehensive manner, namely feedback bits and time duration. First, regarding the feedback bits, there are two components: sensing component (used to convey various users' sensing results) and accessing component (used to feedback channel state information). A large sensing component can support more users to perform cooperative sensing, which results in high sensing precision. However, a large accessing component is preferred as well, as it has a direct impact on the performance in the multiuser cognitive network when multi-antenna technique, such as zero-forcing beamforming (ZFBF), is utilized. Second, the tradeoff of sensing and accessing duration in a transmission interval needs to be determined, so that the sum transmission rate is optimized while satisfying the interference constraint. In addition, the above two resources are interrelated and inversive under some conditions. Specifically, sensing time can be saved by utilizing more sensing feedback bits for a given performance objective. Hence, the resources should be allocation in a jointly manner. Based on the joint optimization framework and the intrinsic relationship between the two resources, we propose two joint resource allocation schemes by maximizing the average sum transmission rate in a multiuser multi-antenna cognitive network. Simulation results show that, by adopting the joint resource allocation schemes, obvious performance gain can be obtained over the traditional fixed strategies.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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