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Optimal Power Allocation for MIMO-OFDM Based Cognitive Radio Systems with Arbitrary Input Distributions

机译:具有任意输入分布的基于MIMO-OFDM的认知无线电系统的最佳功率分配

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摘要

In Cognitive Radio (CR) systems, the data rate of the Secondary User (SU) can be maximized by optimizing the transmit power, given a threshold for the interference caused to the Primary User (PU). In conventional power optimization algorithms, the Gaussian input distribution is assumed, which is unrealistic, whereas the Finite Symbol Alphabet (FSA) input distribution, (i.e., M-QAM) is more applicable to practical systems. In this paper, we consider the power optimization problem in multiple input multiple output orthogonal frequency division multiplexing based CR systems given FSA inputs, and derive an optimal power allocation scheme by capitalizing on the relationship between mutual information and minimum mean square error. The proposed scheme is shown to save transmit power compared to its conventional counterpart. Furthermore, our proposed scheme achieves higher data rate compared to the Gaussian optimized power due to fewer number of subcarriers being nulled. The proposed optimal power algorithm is evaluated and compared with the conventional power allocation algorithms using Monte Carlo simulations. Numerical results reveal that, for distances between the SU transmitter and the PU receiver ranging between 50m to 100m, the transmit power saving with the proposed algorithm is in the range 13-90%, whereas the rate gain is in the range 5-31% depending on the modulation scheme (i.e., BPSK, QPSK and 16-QAM) used
机译:在认知无线电(CR)系统中,给定对主要用户(PU)造成干扰的阈值,可以通过优化发射功率来最大化次要用户(SU)的数据速率。在常规的功率优化算法中,假定了高斯输入分布,这是不现实的,而有限符号字母(FSA)输入分布(即M-QAM)更适用于实际系统。在本文中,我们考虑了在给定FSA输入的情况下基于多输入多输出正交频分复用的CR系统中的功率优化问题,并利用互信息和最小均方误差之间的关系推导了最优功率分配方案。与传统的方案相比,该方案可以节省发射功率。此外,由于减少了子载波的数量,与高斯优化功率相比,我们提出的方案实现了更高的数据速率。使用蒙特卡洛模拟对提出的最佳功率算法进行评估,并与常规功率分配算法进行比较。数值结果表明,对于SU发射机和PU接收机之间的距离在50m至100m之间,该算法节省的发射功率在13-90%的范围内,而速率增益在5-31%的范围内取决于所使用的调制方案(即BPSK,QPSK和16-QAM)

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