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Two-Stage Analog Combining in Hybrid Beamforming Systems With Low-Resolution ADCs

机译:带有低分辨率ADC的混合波束成形系统中的两阶段模拟组合

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In this paper, we investigate hybrid analog/digital beamforming for multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters for millimeter wave (mmWave) communications. In the receiver, we propose to split the analog combining subsystem into a channel gain aggregation stage followed by a spreading stage. Both stages use phase shifters. Our goal is to design the two-stage analog combiner to optimize mutual information (MI) between the transmitted and quantized signals by effectively managing quantization error. To this end, we formulate an unconstrained MI maximization problem without a constant modulus constraint on analog combiners, and derive a two-stage analog combining solution. The solution achieves the optimal scaling law with respect to the number of radio frequency chains and maximizes the MI for homogeneous singular values of a MIMO channel. We further develop a two-stage analog combining algorithm to implement the derived solution for mmWave channels. By decoupling channel gain aggregation and spreading functions from the derived solution, the proposed algorithm implements the two functions by using array response vectors and a discrete Fourier transform matrix under the constant modulus constraint on each matrix element. Therefore, the proposed algorithm provides a near-optimal solution for the unconstrained problem, whereas conventional hybrid approaches offer a near optimal solution only for a constrained problem. The closed-form approximation of the ergodic rate is derived for the algorithm, showing that a practical digital combiner with two-stage analog combining also achieves the optimal scaling law. Simulation results validate the algorithm performance and the derived ergodic rate.
机译:在本文中,我们研究了用于毫米波(mmWave)通信的低分辨率模数转换器的多输入多输出(MIMO)系统的混合模拟/数字波束成形。在接收器中,我们建议将模拟合并子系统分为一个信道增益聚合阶段,然后是扩频阶段。两个阶段均使用移相器。我们的目标是设计一种两级模拟组合器,以通过有效管理量化误差来优化传输信号与量化信号之间的互信息(MI)。为此,我们在模拟组合器上制定了一个没有恒定模数约束的无约束MI最大化问题,并得出了两阶段模拟组合解决方案。该解决方案实现了有关射频链数量的最佳缩放定律,并针对MIMO信道的同质奇异值最大化了MI。我们进一步开发了两阶段模拟组合算法,以实现毫米波通道的导出解决方案。通过将信道增益聚集和扩展函数与导出的解耦,该算法通过在每个矩阵元素上具有恒定模数约束的情况下,通过使用阵列响应矢量和离散傅立叶变换矩阵来实现这两个函数。因此,所提出的算法为无约束的问题提供了近乎最优的解决方案,而常规的混合方法仅为有约束的问题提供了近乎最优的解决方案。该算法得出了遍历速率的闭合形式的近似值,表明具有两级模拟组合的实用数字组合器也可以达到最佳的缩放定律。仿真结果验证了算法性能和推导的遍历率。

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