论文标题
MMWave的软输出有限字母均衡
Soft-Output Finite Alphabet Equalization for mmWAVE Massive MIMO
论文作者
论文摘要
预计下一代无线系统将组合毫米波（MMWAVE）和大量的多用户多输入多输出（MU-MIMO）技术，以提供高数据速率。这些技术要求基地（BSS）以极高的速度处理高维数据，从而导致高功率耗散和系统成本。最近已经提出了有限的alphabet均等化，以减少BS上上行空间均衡电路的功耗和硅面积，通过粗略量化均衡矩阵。在这项工作中，我们通过对编码系统执行无偏估计和软输出计算来改善有限的alphabet均等化。通过模拟使用正交频分多路复用和每个用户卷积编码的庞大的MU-MIMO系统，我们表明，即使在均衡矩阵的每个条目中，软输出有限的alphabet均等均衡均衡只能使用竞争性的误差率性能，甚至用于提起挑战MMWave频道。
Next-generation wireless systems are expected to combine millimeter-wave (mmWave) and massive multi-user multiple-input multiple-output (MU-MIMO) technologies to deliver high data-rates. These technologies require the basestations (BSs) to process high-dimensional data at extreme rates, which results in high power dissipation and system costs. Finite-alphabet equalization has been proposed recently to reduce the power consumption and silicon area of uplink spatial equalization circuitry at the BS by coarsely quantizing the equalization matrix. In this work, we improve upon finite-alphabet equalization by performing unbiased estimation and soft-output computation for coded systems. By simulating a massive MU-MIMO system that uses orthogonal frequency-division multiplexing and per-user convolutional coding, we show that soft-output finite-alphabet equalization delivers competitive error-rate performance using only 1 to 3 bits per entry of the equalization matrix, even for challenging mmWave channels.
