论文标题
GPU中使用张量芯的大规模MIMO系统的通道估计
Channel Estimation for Massive MIMO systems using Tensor Cores in GPU
论文作者
论文摘要
为了有效利用大量MIMO系统，快速准确的通道估计非常重要。但是，大规模天线阵列的存在需要高驾驶机开销，以高准确的估计准确性。同样，当与CPU和GPU等基于软件的处理系统一起使用时，高处理延迟将成为一个主要问题。为了减少飞行员开销，实施了一种与基于PN序列相关的通道估计方案结合使用的飞行员传输方案。然后，为了处理高处理延迟的问题，使用NVIDIA GPU中的张核心来计算通道估计。实验是通过在轨道测试中使用NVIDIA V100 GPU进行的，以显示飞行员传输方案的性能。通过诸如PN序列长度，通道脉冲响应长度，多路复用发射器的数量以及MIMO的尺度等不同因素，评估了通道估计的张量核心实现的准确性和处理潜伏期。
For efficient use of Massive MIMO systems, fast and accurate channel estimation is very important. But the Large-scale antenna array presence requires high pilot overhead for high accuracy of estimation. Also, when used with software-based processing systems like CPUs and GPUs, high processing latency becomes a major issue. To reduce Pilot overhead, a Pilot transmission scheme in combination with PN Sequence correlation based channel estimation scheme is implemented. Then, to deal with the issue of high processing latency, Tensor Cores in Nvidia GPUs are used for computing the channel estimation. Experiments are performed by using Nvidia V100 GPU in the ORBIT Testbed to show the performance of the Pilot transmission scheme. By varying factors like PN sequence length, Channel Impulse Response length, number of multiplexed transmitters, and scale of MIMO, the accuracy and processing latency of Tensor Core implementation of the Channel Estimation is evaluated.
