论文标题
基于最佳通道刺穿的低复杂性软输出MIMO探测器
Low-Complexity Soft-Output MIMO Detectors Based on Optimal Channel Puncturing
论文作者
论文摘要
通道的刺穿使用所谓的WL分解方案将多输入多输出（MIMO）通道转换为稀疏的下三角形形式，以降低基于树的检测复杂性。我们建议基于两种形式的通道刺穿形式的计算有效的软输出检测器：增强和双向。增强的WL检测器（AWLD）采用了通过以增强形式将真实通道的三角形衍生的刺穿通道，其次是左侧的高斯消除。双面WL检测器（称为WLZ）采用右侧还原和左侧消除来刺穿通道。我们证明，基于新的不匹配的检测模型，增强通道的刺穿是最大程度地提高可达到的信息率（AIR）较低限制的最佳选择。我们表明，AWLD分解为MMSE前过滤器和通道增益薪酬阶段，然后是定期的WL检测器（WLD），该检测器（WLD）计算了最小二乘软件估算值。同样，WLZ分解为预处理的还原步骤，其次是WLD。 AWLD的性能与现有的基于空气的部分边缘化（PM）检测器相同，但计算复杂性较小。我们从经验上表明，WLZ在基于树的检测器中达到了最佳的复杂性表现折衷。
Channel puncturing transforms a multiple-input multiple-output (MIMO) channel into a sparse lower-triangular form using the so-called WL decomposition scheme in order to reduce tree-based detection complexity. We propose computationally efficient soft-output detectors based on two forms of channel puncturing: augmented and two-sided. The augmented WL detector (AWLD) employs a punctured channel derived by triangularizing the true channel in augmented form, followed by leftsided Gaussian elimination. The two-sided WL detector (dubbed WLZ) employs right-sided reduction and left-sided elimination to puncture the channel. We prove that augmented channel puncturing is optimal in maximizing the lower-bound on the achievable information rate (AIR) based on a new mismatched detection model. We show that the AWLD decomposes into an MMSE prefilter and channel gain compensation stages, followed by a regular WL detector (WLD) that computes least-squares softdecision estimates. Similarly, WLZ decomposes into a pre-processing reduction step followed by WLD. AWLD attains the same performance as the existing AIR-based partial marginalization (PM) detector, but with less computational complexity. We empirically show that WLZ attains the best complexityperformance tradeoff among tree-based detectors.
