Improved K-Best Signal Detection Algorithm for MIMO Systems
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摘要:
MIMO 是一种显著降低未来塔康(TACAN)导航系统的信号检测的误码率的技术。 最大似然算法(ML)是 MIMO 无线系统的最佳硬判决检测方式，但是其会随着天线数目和调制阶数的增加，其复杂度呈指数规律增加。传统 K-Best 算法虽克服 ML 算法的缺点，降低了检测算法的计算复杂度，节约计算成本，但其 BER 性能略有下降。改进型 K-Best 算法采用最优检测快速 QR 分解、预处理技术(SE)和球型译码技术(SDA)检测手段克服传统 K-Best 算法的缺点。 仿真结果表明改进型 K-Best 算法相对于传统算法，明显提高了 BER 性能。
Abstract:
MIMO is a technology that can significantly reduce the error rate of future TACAN navigation systems. The maximum likelihood algorithm (ML) is the best way to detect hard decision MIMO wireless systems. However， its complexity increases exponentially with increase of the number of antennas and the modulation order. Although the traditional K-Best algorithm has overcame the shortcomings ML， reduced the computational complexity of the detection algorithm and save the calculation cost and decreased its BER performance. The improved K-Best algorithm adopting optimum detection fast QR decomposition， optimal pretreatment technology (SE)and the sphere decoding algorithm (SDA)detection overcomes the shortcomings of the traditional K-Best algorithm. Simulation results show that the improved K-Best algorithm not only reduces the computational complexity and cost savings， but also significantly improves the BER performance compared with the traditional method.
