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Computationally Efficient Lattice Reduction Aided Detection for MIMO-OFDM Systems under Correlated Fading Channels

机译:相关衰落信道下MIMO-OFDM系统的高效计算格子减少辅助检测

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We analyze the relationship between channel coherence bandwidth and two complexity-reduced lattice reduction aided detection (LRAD) algorithms for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems in correlated fading channels. In both the adaptive LR algorithm and the fixed interval LR algorithm, we exploit the inherent feature of unimodular transformation matrix P that remains the same for the adjacent highly correlated subcarriers. Complexity simulations demonstrate that the adaptive LR algorithm could eliminate up to approximately 90 percent of the multiplications and 95 percent of the divisions of the brute-force LR algorithm with large coherence bandwidth. The results also show that the adaptive algorithm with both optimum and globally suboptimum initial interval settings could significantly reduce the LR complexity, compared with the brute-force LR and fixed interval LR algorithms, while maintaining the system performance.
机译:针对相关衰落信道中的多输入多输出(MIMO)正交频分复用(OFDM)系统,我们分析了信道相干带宽与两种降低复杂度的点阵减少辅助检测(LRAD)算法之间的关系。在自适应LR算法和固定间隔LR算法中,我们都利用了单模变换矩阵P的固有特征,该特征对于相邻的高度相关子载波保持不变。复杂度仿真表明,自适应LR算法可以消除具有大相干带宽的蛮力LR算法的大约90%的乘法和95%的除法。结果还表明,与强力LR和固定间隔LR算法相比,具有最佳和全局次最佳初始间隔设置的自适应算法可以显着降低LR复杂度。

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