Using pyAerial for decoding PUSCH transmissions from multiple cells using Aerial Data Lake data

This example shows how to use the pyAerial bindings to run cuPHY GPU accelerated PUSCH decoding for 5G NR PUSCH. The 5G NR PUSCH data is read from an example over the air captured PUSCH dataset collected from two cells and stored using Aerial Data Lake. A complete PUSCH receiver using individual separate Python function calls to individual PUSCH receiver components is used so that channel estimates can be shown.

In this setup there are two cells:

• Cell 51 is an active cell being used with the OAI L2+ using slot pattern DDDSU and commercial UEs.

• Cell 41 is a passive “listener” cell using the same slot pattern as cell 51 but is being driven by testMAC to request IQ samples for every uplink slot.

There are multiple UEs connected to cell 51, as is shown in the nUEs field of the fapi table. Both cells receive the same PUSCH data, and we attempt decoding from both cells. Note: As the UEs are connected to cell 51, it is expected that the decoding does not succeed in all cases from cell 41.

The first two plots show the power in all of the resource elements for the given slot on both cells. The plots after that show just the resource elements scheduled for a given UE (RNTI) across both cells, as well pre- and post- equalized samples, then channel estimates, for IQ samples from each cell, followed by text indicating whether the transmission decoded successfully.

Note: This example requires that the clickhouse server is running and that the example data has been stored in the database. Refer to the Aerial Data Lake documentation on how to do this.

Imports

import math
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0"

import numpy as np
import pandas as pd
from IPython.display import Markdown
from IPython.display import display

# Connecting to clickhouse on remote server
import clickhouse_connect

# Plotting with Matplotlib.
import matplotlib.pyplot as plt
from matplotlib import dates as mdates


# pyAerial imports
from aerial.phy5g.config import PuschConfig
from aerial.phy5g.config import PuschUeConfig
from aerial.phy5g.algorithms import ChannelEstimator
from aerial.phy5g.algorithms import ChannelEqualizer
from aerial.phy5g.algorithms import NoiseIntfEstimator
from aerial.phy5g.ldpc import LdpcDeRateMatch
from aerial.phy5g.ldpc import LdpcDecoder
from aerial.phy5g.ldpc import CrcChecker
from aerial.util.cuda import CudaStream
from aerial.util.fapi import dmrs_fapi_to_bit_array

# Hide log10(10) warning
_ = np.seterr(divide='ignore', invalid='ignore')
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)

np.set_printoptions(threshold=100)  # Control the number of elements to display
np.set_printoptions(edgeitems=100)  # Control the number of edge items to display
np.set_printoptions(linewidth=200) # Control the width of the display

plt.rcParams['figure.figsize'] = [10, 4]

Create the PUSCH pipelines

This is a PUSCH receiver pipeline made up of separately called pyAerial PUSCH receiver components.

# Whether to plot intermediate results within the PUSCH pipeline, such as channel estimates and equalized symbols.
plot_figures = True

num_ues = 1
num_tx_ant = 2             # UE antennas
num_rx_ant = 4             # gNB antennas
enable_pusch_tdi = 0       # Enable time interpolation for equalizer coefficients
eq_coeff_algo = 1          # Equalizer algorithm

# The PUSCH receiver chain built from separately called pyAerial Python components is defined here.
class PuschRxSeparate:
    """PUSCH receiver class.

    This class encapsulates the whole PUSCH receiver chain built using
    pyAerial components.
    """

    def __init__(self,
                 num_rx_ant,
                 enable_pusch_tdi,
                 eq_coeff_algo,
                 plot_figures):
        """Initialize the PUSCH receiver."""
        self._stream = CudaStream()

        # Build the components of the receiver.
        self.channel_estimator = ChannelEstimator(
            num_rx_ant=num_rx_ant,
            cuda_stream=self._stream)
        self.channel_equalizer = ChannelEqualizer(
            num_rx_ant=num_rx_ant,
            enable_pusch_tdi=enable_pusch_tdi,
            eq_coeff_algo=eq_coeff_algo,
            cuda_stream=self._stream)
        self.noise_intf_estimator = NoiseIntfEstimator(
            num_rx_ant=num_rx_ant,
            eq_coeff_algo=eq_coeff_algo,
            cuda_stream=self._stream)
        self.derate_match = LdpcDeRateMatch(
            enable_scrambling=True,
            cuda_stream=self._stream)
        self.decoder = LdpcDecoder(cuda_stream=self._stream)
        self.crc_checker = CrcChecker(cuda_stream=self._stream)

        # Whether to plot the intermediate results.
        self.plot_figures = plot_figures

    def run(
        self,
        rx_slot,
        slot,
        pusch_configs,
        cell_id
    ):
        """Run the receiver."""
        # Channel estimation.
        ch_est = self.channel_estimator.estimate(
            rx_slot=rx_slot,
            slot=slot,
            pusch_configs=pusch_configs
        )

        # Noise and interference estimation.
        lw_inv, noise_var_pre_eq = self.noise_intf_estimator.estimate(
            rx_slot=rx_slot,
            channel_est=ch_est,
            slot=slot,
            pusch_configs=pusch_configs
        )

        # Channel equalization and soft demapping. The first return value are the LLRs,
        # second are the equalized symbols. We only want the LLRs now.
        llrs, sym = self.channel_equalizer.equalize(
            rx_slot=rx_slot,
            channel_est=ch_est,
            lw_inv=lw_inv,
            noise_var_pre_eq=noise_var_pre_eq,
            pusch_configs=pusch_configs
        )

        if self.plot_figures:
            fig, axs = plt.subplots(1, 4)
            for ant in range(4):
                axs[ant].imshow(10*np.log10(np.abs(rx_slot[:, :, ant] ** 2)), aspect='auto')
                axs[ant].set_ylim([(pusch_record.rbStart + pusch_record.rbSize) * 12, pusch_record.rbStart * 12])
                axs[ant].set_title('Ant ' + str(ant))
                axs[ant].set(xlabel='Symbol', ylabel='Resource Element')
                axs[ant].label_outer()
            fig.suptitle('Power in PUSCH REs cell {} for RNTI {}'.format(cell_id, pusch_record.rnti))

            fig, axs = plt.subplots(1, 2)
            axs[0].scatter(rx_slot.reshape(-1).real, rx_slot.reshape(-1).imag)
            axs[0].set_title("Pre-Equalized samples")
            axs[0].set_aspect('equal')

            axs[1].scatter(np.array(sym).reshape(-1).real, np.array(sym).reshape(-1).imag)
            axs[1].set_title("Post-Equalized samples")
            axs[1].set_aspect('equal')

            fig, axs = plt.subplots(1)
            axs.set_title("Channel estimates from the PUSCH pipeline")
            for ant in range(4):
                axs.plot(np.abs(ch_est[0][ant, 0, :, 0]))
            axs.legend(["Rx antenna 0, estimate",
                        "Rx antenna 1, estimate",
                        "Rx antenna 2, estimate",
                        "Rx antenna 3, estimate"])
            axs.grid(True)
            plt.show()

        coded_blocks = self.derate_match.derate_match(
            input_llrs=llrs,
            pusch_configs=pusch_configs
        )

        code_blocks = self.decoder.decode(
            input_llrs=coded_blocks,
            pusch_configs=pusch_configs
        )

        decoded_tbs, _ = self.crc_checker.check_crc(
            input_bits=code_blocks,
            pusch_configs=pusch_configs
        )

        return decoded_tbs

pusch_rx_separate = PuschRxSeparate(
    num_rx_ant=num_rx_ant,
    enable_pusch_tdi=enable_pusch_tdi,
    eq_coeff_algo=eq_coeff_algo,
    plot_figures=plot_figures
)

Querying the database

Below shows how to connect to the clickhouse database and querying the data from it.

# Connect to the local database
import clickhouse_connect

client = clickhouse_connect.get_client(host='localhost')

# Pick a packet from the database,
pusch_records = client.query_df('select * from fapi order by TsTaiNs,rbStart limit 10')

Extract the PUSCH parameters and run the pipelines

In this section we use the timestamp of the start of a slot to query the IQ sample database for both cells and demonstrate that the transmission can be decoded in the IQ samples of both cells.

run_receiver = True
# Only show the full slot pattern the first time through:
shown_timestamp = -1
pusch_records = client.query_df('select * from fapi order by TsTaiNs,rbStart limit 8')
print(pusch_records[['TsTaiNs','SFN','Slot','CellId','nUEs','rnti','rbStart','rbSize','StartSymbolIndex','NrOfSymbols','nrOfLayers','TBSize','CQI']])

for index, pusch_record in pusch_records.iterrows():
    query = f"""select TsTaiNs,CellId,fhData from fh where TsTaiNs == toDateTime64(\'{pusch_record.TsTaiNs.timestamp()}\', 9)"""
    fh = client.query_df(query)

    # Extract all the needed parameters from the PUSCH record and create the PuschConfig.
    pusch_ue_config = PuschUeConfig(
        scid=int(pusch_record.SCID),
        layers=pusch_record.nrOfLayers,
        dmrs_ports=pusch_record.dmrsPorts,
        rnti=pusch_record.rnti,
        data_scid=pusch_record.dataScramblingId,
        mcs_table=pusch_record.mcsTable,
        mcs_index=pusch_record.mcsIndex,
        code_rate=pusch_record.targetCodeRate,
        mod_order=pusch_record.qamModOrder,
        tb_size=pusch_record.TBSize
    )

    slot = int(pusch_record.Slot)
    tb_input = np.array(pusch_record.pduData)

    # Note that this is a list. One UE group only in this case.
    pusch_configs = [PuschConfig(
        ue_configs=[pusch_ue_config],
        num_dmrs_cdm_grps_no_data=pusch_record.numDmrsCdmGrpsNoData,
        dmrs_scrm_id=pusch_record.ulDmrsScramblingId,
        start_prb=pusch_record.rbStart,
        num_prbs=pusch_record.rbSize,
        dmrs_syms=dmrs_fapi_to_bit_array(int(pusch_record.ulDmrsSymbPos)),
        dmrs_max_len=1,
        dmrs_add_ln_pos=pusch_record.ulDmrsSymbPos.bit_count() - 1,
        start_sym=pusch_record.StartSymbolIndex,
        num_symbols=pusch_record.NrOfSymbols
    )]
    num_cells = fh.index.size
    if shown_timestamp != pusch_record.TsTaiNs.timestamp():
        shown_timestamp = pusch_record.TsTaiNs.timestamp()
        display(Markdown("### SFN.Slot {}.{}, RNTI {} at time {}"
                     .format(pusch_record.SFN, pusch_record.Slot, pusch_record.rnti, pusch_record.TsTaiNs
        )))
        fig = plt.figure(constrained_layout=True)
        if num_cells > 1:
            outer = fig.subfigures(1, num_cells)
            for cell_num, cell_plot in enumerate(outer.flat):
                fh_samp = (np.array(fh['fhData'].iloc[cell_num], dtype=np.int16).view(np.float16)).astype(np.float32)
                rx_slot = np.swapaxes(fh_samp.view(np.complex64).reshape(4, 14, 273 * 12), 2, 0)

                axs = cell_plot.subplots(1, 4)
                for ant, ax in enumerate(axs.flat):
                    ax.imshow(10 * np.log10(np.abs(rx_slot[:, :, ant] ** 2)), aspect='auto')
                    ax.set_title('Ant ' + str(ant))
                    ax.set(xlabel='Symbol', ylabel='Resource Element')
                    ax.label_outer()
                    cell_plot.suptitle('Power in RU Antennas Cell ' + str(fh['CellId'].iloc[cell_num]))
            plt.show()
        else:
            cell_num = 0
            fig, axs = plt.subplots(1, 4)
            fh_samp = (np.array(fh['fhData'].iloc[cell_num], dtype=np.int16).view(np.float16)).astype(np.float32)
            rx_slot = np.swapaxes(fh_samp.view(np.complex64).reshape(4, 14, 273 * 12), 2, 0)
            for ant in range(4):
                axs[ant].imshow(10 * np.log10(np.abs(rx_slot[:, :, ant] ** 2)), aspect='auto')
                axs[ant].set_ylim([pusch_record.rbStart * 12, (pusch_record.rbStart+pusch_record.rbSize) * 12])
                axs[ant].set_title('Ant ' + str(ant))
                axs[ant].set(xlabel='Symbol', ylabel='Resource Element')
                axs[ant].label_outer()
            fig.suptitle('Power in RU Antennas')

            fig, axs = plt.subplots(1,2)
            axs[0].scatter(rx_slot.reshape(-1).real, rx_slot.reshape(-1).imag)
            axs[0].set_title("Pre-Equalized samples")
            axs[0].set_aspect('equal')

            axs[1].scatter(np.array(sym).reshape(-1).real, np.array(sym).reshape(-1).imag)
            axs[1].set_title("Post-Equalized samples")
            axs[1].set_aspect('equal')

            fig, axs = plt.subplots(1)
            axs.set_title("Channel estimates from the PUSCH pipeline")
            for ant in range(4):
                axs.plot(np.abs(ch_est[0][ant, 0, :, 0]))
            axs.legend(["Rx antenna 0, estimate",
                        "Rx antenna 1, estimate",
                        "Rx antenna 2, estimate",
                        "Rx antenna 3, estimate"])
            axs.grid(True)
            plt.show()

    if run_receiver:
        for cell_num in range(0, num_cells):
            cell_id = fh['CellId'].iloc[cell_num]
            fh_samp = (np.array(fh['fhData'].iloc[cell_num], dtype=np.int16).view(np.float16)).astype(np.float32)
            rx_slot = np.swapaxes(fh_samp.view(np.complex64).reshape(4, 14, 273 * 12), 2, 0)
            tbs = pusch_rx_separate.run(
                rx_slot=rx_slot,
                slot=slot,
                pusch_configs=pusch_configs,
                cell_id=cell_id
            )
            if np.array_equal(tbs[0][:tb_input.size], tb_input):
                display(Markdown("**PUSCH decoding success** for SFN.Slot {}.{} RNTI {} originally on cell {} using IQ data from cell {} "
                         .format(pusch_record.SFN, pusch_record.Slot, pusch_record.rnti, pusch_record.CellId, cell_id)))
            else:
                display(Markdown("**PUSCH decoding failure** for SFN.Slot {}.{} RNTI {} originally on cell {} using IQ data from cell {} "
                         .format(pusch_record.SFN, pusch_record.Slot, pusch_record.rnti, pusch_record.CellId, cell_id)))
                print("Output bytes:")
                print(tbs[0][:tb_input.size])
                print("Expected output:")
                print(tb_input)

                  TsTaiNs  SFN  Slot  CellId  nUEs   rnti  rbStart  rbSize  StartSymbolIndex  NrOfSymbols  nrOfLayers  TBSize        CQI
0 2024-07-19 10:42:46.272  391     4      41     7  20000        0       8                 0           10           1      63  -7.352562
1 2024-07-19 10:42:46.272  391     4      51     7  62290        0       5                 0           13           1     185  31.755341
2 2024-07-19 10:42:46.272  391     4      51     7  53137        5       5                 0           13           1     185  30.275444
3 2024-07-19 10:42:46.272  391     4      51     7   1624       10       5                 0           13           1     185  31.334328
4 2024-07-19 10:42:46.272  391     4      51     7  47905       15       5                 0           13           1     185  30.117304
5 2024-07-19 10:42:46.272  391     4      51     7  57375       20       5                 0           13           1     185  29.439499
6 2024-07-19 10:42:46.272  391     4      51     7  20216       25     248                 0           13           1   19985  25.331459
7 2024-07-19 10:42:47.292  493     4      41     6  20000        0       8                 0           10           1      63  -7.845479

SFN.Slot 391.4, RNTI 20000 at time 2024-07-19 10:42:46.272000

PUSCH decoding success for SFN.Slot 391.4 RNTI 20000 originally on cell 41 using IQ data from cell 41

PUSCH decoding success for SFN.Slot 391.4 RNTI 20000 originally on cell 41 using IQ data from cell 51

PUSCH decoding success for SFN.Slot 391.4 RNTI 62290 originally on cell 51 using IQ data from cell 41

PUSCH decoding success for SFN.Slot 391.4 RNTI 62290 originally on cell 51 using IQ data from cell 51

PUSCH decoding success for SFN.Slot 391.4 RNTI 53137 originally on cell 51 using IQ data from cell 41

PUSCH decoding success for SFN.Slot 391.4 RNTI 53137 originally on cell 51 using IQ data from cell 51

PUSCH decoding failure for SFN.Slot 391.4 RNTI 1624 originally on cell 51 using IQ data from cell 41

Output bytes:
[  2  32 217  29   5  72 230 133  18   7 249 217  29 192 195 211  75  91 138 229  10   7 106 121 229  69  70  88 148 140 106 242 236 205 149  11 103 225  17 212  96  72 128 196 211 223  93 129  42
 105 190 143 210  13 147  99  66 229  82 113 100 198 131 100 212 179 133  51  81 125 173  25 253  57 122 193  19 201 180  38 145 112 250  74 205 147  91  32 160 193 175 111 193  82 178 204  90   0
 212  53  45 107 195  85 225 208 202  11  84 211  36 217  30 144 187  18 198  75 137 227 186 151  55 252 186 113  95  89 183 132 145  63 138 125 202 148 178 113  98 112   3 126  87  31 114 115  75
 161  51 215 185 137 116 136 134   1  57 218 125 214  80  59 132  79 104  77 219 137 213 217  33  13  55   7  65 251 239 146 219  35 250  17   0  14  60]
Expected output:
[61  0 57 63 51 63 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33]

PUSCH decoding success for SFN.Slot 391.4 RNTI 1624 originally on cell 51 using IQ data from cell 51

PUSCH decoding failure for SFN.Slot 391.4 RNTI 47905 originally on cell 51 using IQ data from cell 41

Output bytes:
[191 131  42 160 120 171   5 122 183  48 200  46 220 202  78 207  17   8 250 235 190  59  64  14 105 130  35 209  70  51  14 157 223  29 184 127 228  88   7 175  67 103 113 194  28  97 168 251  19
 207 117 170 102  35  17 226 165 243 249 218 239  31  57   8  28 244 146 107   2  89 180 202 164  70 140 134  78  10 138 214 228 136  36 179 154 136  94 187 167 204  70 127  33  96 176 116 127 246
  24  81  21 227 134 231 188   8 151  72   1 250  48  44 178 192 113 141  11  85 172 118 182 217   8 182  99  26 161 187 160  23 160   8  86 167  64  86  54 217 151 205 208   5  95  15 156   7  96
 252 211 183 113 214 194 111  75  79  70 114 139  39 203  54  25  91 224 135  42 253  47 105 118 123 122  41  27 104 151  76 176 133  55  95  18 179 105]
Expected output:
[61  0 57 63 51 63 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33]

PUSCH decoding success for SFN.Slot 391.4 RNTI 47905 originally on cell 51 using IQ data from cell 51

PUSCH decoding failure for SFN.Slot 391.4 RNTI 57375 originally on cell 51 using IQ data from cell 41

Output bytes:
[165 153 165   3  61 136 161  91  85   2  26 149 119 112 106  42 211  37  32  49 199 135  82 105 162  70 176 163 253  91 187 141  45  88  42  36  38  11  22   2  81 114 219   8  27 199 181 168 139
  25 220  25  76 135 114  88 140 103 152 101  78   6 146   8 148 167  82 161  13 137 195 186 129  75  91 218 215  51 225 194  97 174 178 174 190  94  61  30   3 128 108 127 225 180  84 201  36 196
  91 241   9  51  58  25 112  49 232 151  34 242 250 250 133 126 143 243 105  60  70 102  70  79  40 151 168 109 133 106  66 102 189 123 231 127  10  76  80 250  44 190 162 205  12 110  70 179 103
 105 208 102  69 171 184 187 195 190 169 235 124 218  36 253  29  89 246 121  36  32 191  58 235  74  80  66 153  73  84 127  59 231 174  46 197   9 116]
Expected output:
[ 4  3  0  0 80 61  0 57 63 51 63 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33
 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33 33]

PUSCH decoding success for SFN.Slot 391.4 RNTI 57375 originally on cell 51 using IQ data from cell 51

PUSCH decoding failure for SFN.Slot 391.4 RNTI 20216 originally on cell 51 using IQ data from cell 41

Output bytes:
[129 110 210  96   4 183 250 172 186 215 150  23 114  98 223  24  93 251 134 128 106   6 130 139 237 194 193  24 217 180 109  76 218  57  36  16 215 138 143 180 158 192  60  49  73 133 249 120 147
 105 189 181 202   4  92 174  16   1 253 128 138 195  58 243 144 215 209 185 156 167  72  40 151  29 127 220  51  83 120 114 250 224  52  71  13 101 186  80 229 239 202  85  96 202 213  96  46  87
 166 142 ... 113 143 157 254   1  27 247  25 255 249  59  38   4 213  83  30 111  25  78 205 102  73 100 144  43  57 151  47 197  79 155 124 142 205 113 138 181 185 116  84  50 148 137  88  36  15
 167 142  45 136 202 179 110 254   4 148 237 153 250  16 237 252  75 178 255 194 176   0 114  46 201 223 128 121  11  86 216  79  83  42  25  37 164  14 206 115  10  38 193 131 160 117  44  15  17
 147 118  80   7  33]
Expected output:
[ 68   1 133 160  13 151   4  71  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52
  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51
  52  53 ...  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54
  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53  54  55  56  57  48  49  50  51  52  53
  54  55  56  57  48]

PUSCH decoding success for SFN.Slot 391.4 RNTI 20216 originally on cell 51 using IQ data from cell 51

SFN.Slot 493.4, RNTI 20000 at time 2024-07-19 10:42:47.292000

PUSCH decoding success for SFN.Slot 493.4 RNTI 20000 originally on cell 41 using IQ data from cell 41

PUSCH decoding success for SFN.Slot 493.4 RNTI 20000 originally on cell 41 using IQ data from cell 51