An Iterative Algorithm with Adjustable Weight for Inference Channel
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摘要: 在多入多出的干扰网络中，干扰对齐由于仅考虑干扰，而忽略期望信号的影响，在低信噪比(Signal-to-Noise Ratio, SNR)时性能损失严重。该文提出一种同时考虑干扰与期望信号的算法，把二者泄露出相应子空间的功率加权和作为目标函数，而且权值在不同SNR时可调，通过迭代获得预编码矩阵。仿真表明该算法在低信噪比时，可以有效提高系统容量。Abstract: In multiple-input multiple-output interference channels, Interference alignment suffers from performance loss at low Signal-to-Noise Ratio (SNR) due to it neglecting the desired signal power. An algorithm is proposed that iteratively minimizes weighted sum of leakages caused by both interference and desired signal out of their corresponding subspace. The weighted factors are allowed to be adjusted according to SNR. Simulation result shows that the proposed algorithm can improve sum rate effectively at low SNR.
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