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.
翻译:为了有效使用大型MIMO系统,快速和准确的频道估计非常重要。但是,大型天线阵列的存在需要高水平的试点间接费用,以便进行高准确的估计。此外,当用于基于软件的处理系统,如CPUs和GPUs时,高处理延迟期就成为一个重大问题。为了减少试点间接费用,将实施一个试点传输计划,同时采用基于PN序列相关频道估计计划。然后,为了处理高处理延迟度问题,使用Nvidia GPUs的Tensor核心来计算频道估计。通过在ORBIT测试床使用Nvidia V100 GPU来进行实验,以显示试点传输计划的性能。通过PN序列长度、Channel Inmpulse反应长度、多轴发射机数量和MIMO的规模等不同因素,对频道刺激的Tensor核心执行的精确度和处理延迟度进行了评估。