itted DMRS sequence. That will give a channel estimate per subcarrier. Optionally, this channel estimate is then passed through a smoothing filter to improve estimation quality. From a complexity perspective that means that once per slot (2 slot/second) a complex MAC (CMAC) is applied to all subcarriers in a layer. Computational complexity scaled with Ncarrier X NReceive Antenna X Nlayer Optionally, this step can be implemented in the antenna processor/digital front end, but this would add additional antenna processor complexity as well as additional communication overhead between distributed unit (DU) and antenna processor. 1 carrier X 3276 subcarriers/received symbol X 0.5 DMRS sequence RE occupancy X 8 received antennas X 4 layers X 2000 slot/second = 105 MCMAC/s or 420 MRMAC/s. Equalization Matrix Compute. Equalization can be done in different ways, we assume Minimum Mean Square Error, a commonly used algorithm (MMSE) on a resource block (RB) granularity. 1280 CMAC/8 X 8 matrix X 1 carrier X 273 RB/DMRS X 2000 slot/second = 699 MCMAC/s or 2796 MRMAC/s. Time-frequency offset estimation. Time offset estimation is done by doing a power delay profile of the channel estimation: ~ 3210 MRMAC/s. Inverse FFT (IFFT) of channel estimates to go to time domain. 1 carrier X 4096 X log2(4096) (IFFT) X 8 received antennas X 2000 slot/ second = 786 MCMAC/s or 3145 MRMAC/s. I2 + Q2 to compute power. 4096 X 8 X 2000 = 65 MRMAC/s. Find peak around expected Time Alignment (TA). Marginal and not accounted here. Frequency offset estimate. Compute phase deviations across consecutive symbols over Phase Tracking Reference Signal (PTRS), Channel State Information Reference Symbol (CSI-RS), and Demodulation Reference Symbol (DMRS). Assuming worst case of DMRS: 3276 subcarriers X8 received antennas X 2000 slot/second = 52 MCMAC/s or 210 MRMAC/s. If phase noise is significant, an average over many symbols is required to remove phase noise. Chapter 9 Software performance Channel equalization. This is the application of the MMSE weights SO