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An Adaptive Cooperative Strategy for Underlay MIMO Cognitive Radio Networks: An Opportunistic and Low-Complexity Approach

机译:底层MIMO认知无线电网络的自适应合作策略:机会和低复杂度方法

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The core aim of this work is the maximization of the achievable data rate of the secondary user pairs (SU pairs), while ensuring the QoS of primary users (PUs). All users are assumed to be equipped with multiple antennas. It is assumed that when PUs are present, the direct communications between SU pairs introduces intolerable interference to PUs and thereby SUs transmit signal using the cooperation of other SUs and avoid transmitting in the direct channel. In brief, an adaptive cooperative strategy for multiple- input/multiple-output (MIMO) cognitive radio networks is proposed. At the presence of PUs, the issue of joint relay selection and power allocation in Underlay MIMO Cooperative Cognitive Radio Networks (U-MIMO-CCRN) is addressed. The optimal approach for determining the power allocation and the cooperating SU is proposed. Besides, the outage probability of the proposed communication protocol is further derived. Due to high complexity of the optimal approach, a low-complexity approach is further proposed and its performance is evaluated using simulations. The simulation results reveal that the performance loss due to the low-complexity approach is only about 14%, while the complexity is greatly reduced.
机译:这项工作的核心目标是最大程度地提高次要用户对(SU对)的数据速率,同时确保主要用户(PU)的QoS。假定所有用户都配备了多个天线。假设当存在PU时,SU对之间的直接通信给PU带来了无法忍受的干扰,从而SU使用其他SU的协作来发送信号,并避免在直接信道中发送。简而言之,提出了用于多输入/多输出(MIMO)认知无线电网络的自适应协作策略。在PU的存在下,解决了底层MIMO协作认知无线电网络(U-MIMO-CCRN)中联合中继选择和功率分配的问题。提出了确定功率分配和协同SU的最佳方法。此外,进一步推导了所提出的通信协议的中断概率。由于最佳方法的高度复杂性,因此进一步提出了一种低复杂度的方法,并通过仿真对其性能进行了评估。仿真结果表明,低复杂度方法造成的性能损失仅为14%左右,而复杂度却大大降低了。

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