Multi-User Downlink Beamforming Using Uplink Downlink Duality With 1-Bit Converters for Flat Fading Channels
Multi-User Downlink Beamforming Using Uplink Downlink Duality With 1-Bit Converters for Flat Fading Channels
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DOI：
10.1109/tvt.2022.3196603
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发表时间：
2022-06
影响因子：
6.8
通讯作者：
K. Mazher;A. Mezghani;R. Heath
中科院分区：
文献类型：
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作者：
K. Mazher;A. Mezghani;R. Heath
高分辨率数据转换器在更高载波频率和更大带宽下的功耗增加正成为通信系统的瓶颈。在本文中，我们考虑一个全数字基站配备1位模拟到数字（上行链路）和数字到模拟（下行链路）转换器的每个射频链。基站与具有单独SINR约束的多个单天线用户通信。我们首先建立了1比特硬件约束下的上行链路下行链路的对偶性原则下，不相关的量化噪声的假设。然后，我们提出了一个线性的解决方案的多用户下行波束成形问题的基础上，上行链路下行链路的对偶原则。所提出的解决方案考虑了硬件约束，并联合优化下行链路波束形成器和分配给每个用户的功率。通过将虚拟用户添加到真实系统用户而获得的优化抖动确保不相关量化噪声假设在现实设置下为真。使用Quadriga生成的3GPP信道模型进行的详细仿真表明，我们提出的解决方案在遍历和最小速率方面优于现有技术的解决方案，特别是当用户数量很大时。我们还表明，所提出的解决方案显着减少了性能差距，从非线性解决方案的未编码的误码率在一小部分的计算复杂度。
The increased power consumption of high-resolution data converters at higher carrier frequencies and larger bandwidths is becoming a bottleneck for communication systems. In this paper, we consider a fully digital base station equipped with 1-bit analog-to-digital (in uplink) and digital-to-analog (in downlink) converters on each radio frequency chain. The base station communicates with multiple single antenna users with individual SINR constraints. We first establish the uplink downlink duality principle under 1-bit hardware constraints under an uncorrelated quantization noise assumption. We then present a linear solution to the multi-user downlink beamforming problem based on the uplink downlink duality principle. The proposed solution takes into account the hardware constraints and jointly optimizes the downlink beamformers and the power allocated to each user. Optimized dithering obtained by adding dummy users to the true system users ensures that the uncorrelated quantization noise assumption is true under realistic settings. Detailed simulations carried out using 3GPP channel models generated from Quadriga show that our proposed solution outperforms state of the art solutions in terms of the ergodic sum and minimum rate especially when the number of users is large. We also demonstrate that the proposed solution significantly reduces the performance gap from non-linear solutions in terms of the uncoded bit error rate at a fraction of the computational complexity.