全双工中继协作下的认知MIMO系统吞吐量最大化研究

Average Throughput Maximization of the Full-Duplex Relay-Assisted Cognitive MIMO System

  • 摘要: 本文研究了全双工中继协作下的认知MIMO系统的平均吞吐量最大化问题。与传统的中继协作认知无线电系统不同的是,该系统模型中的双工中继节点既能协助认知用户源节点进行多天线频谱感知以提高频谱检测性能,也能解码转发认知用户源节点的发送信号以获得更大的系统吞吐量。为使系统平均吞吐量最大,首先,本文以认知用户能获得的最大平均频谱空洞被发现的概率为目标,对系统的帧结构进行优化以获得最佳的感知时间,接着对多个发送天线进行优化以选择出最佳的发送天线,并推导出了在总的发送功率和对主用户干扰受限条件下的认知用户源节点和双工中继节点的最佳功率分配方案。最后的仿真结果表明本文提出的系统模型和优化方案相比传统的双工等功率分配方案以及单工功率分配方案能够获得更大的系统平均吞吐量。

     

    Abstract: In this paper, the problem of average throughput maximization of the full-duplex relay-assisted cognitive MIMO system is considered. Compare to traditional relay-assisted cognitive radio system, the duplex relay of the proposed system model can not only cooperate with cognitive user source to perform multi-antenna spectrum sensing to enhance the performance of spectrum sensing, but also decode and forward the signal from cognitive user source to improve the system throughput. In order to maximize the system average throughput, the design optimization of frame structure is considered to obtain the optimal sensing time and maximum the average probability of spectrum holes discovery for cognitive user. And the transmit antennas are also optimized to select the best transmit antenna to send the signal. Then the optimal power allocation scheme is derived under the limitations of the total transmission power and the harmful interference to primary user. Simulation results show that the proposed system model and optimization scheme can achieve the better average throughput, compared to the traditional full duplex equal power allocation and half duplex power allocation scheme.

     

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