{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to Iterative Detection and Decoding\n",
    "In this notebook, you will learn how to set-up an iterative detection and decoding (IDD) scheme (first presented in [1]) by combining multiple available components in Sionna.\n",
    "\n",
    "For a gentle introduction to MIMO simulations, we refer to the notebooks [\"Simple MIMO Simulations\"](https://nvlabs.github.io/sionna/phy/tutorials/notebooks/Simple_MIMO_Simulation.html) and [\"MIMO OFDM Transmissions over CDL\"](https://nvlabs.github.io/sionna/phy/tutorials/notebooks/MIMO_OFDM_Transmissions_over_CDL.html).\n",
    "\n",
    "You will evaluate the performance of IDD with OFDM MIMO detection and soft-input soft-output (SISO) LDPC decoding and compare it against several non-iterative detectors, such as soft-output LMMSE, K-Best, and expectation propagation (EP), as well as iterative SISO MMSE-PIC detection [2].\n",
    "\n",
    "For the non-IDD models, the signal processing pipeline looks as follows:"
   ]
  },
  {
   "attachments": {
    "block_diagram.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![block_diagram.png](attachment:block_diagram.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Iterative Detection and Decoding\n",
    "The IDD MIMO receiver iteratively exchanges soft-information between the data detector and the channel decoder, which works as follows:"
   ]
  },
  {
   "attachments": {
    "idd_diagram.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![idd_diagram.png](attachment:idd_diagram.png)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We denote by $\\mathrm{L}^{D}$ the *a posteriori* information (represented by log-likelihood ratios, LLRs) and by $\\mathrm{L}^{E} = \\mathrm{L}^{D} - \\mathrm{L}^{A}$ the extrinsic information, which corresponds to the information gain in $\\mathrm{L}^{D}$ relative to the *a priori* information $\\mathrm{L}^{A}$. The *a priori* LLRs represent soft information, provided to either the input of the detector (i.e., $\\mathrm{L}^{A}_{Det}$) or the decoder (i.e., $\\mathrm{L}^{A}_{Dec}$). While exchanging extrinsic information is standard for classical IDD, the SISO MMSE-PIC detector [2] turned out to work better when provided with the full *a posteriori* information from the decoder.\n",
    "\n",
    "Originally, IDD was proposed with a resetting (Turbo) decoder [1]. However, state-of-the-art IDD with LDPC message passing decoding showed better performance with a non-resetting decoder [3], particularly for a low number of decoding iterations. Therefore, we will forward the decoder state (i.e., the check node to variable node messages) from each IDD iteration to the next."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Table of contents\n",
    "* [Configuration and Imports](#Configuration-and-Imports)\n",
    "* [Simulation Parameters](#Simulation-Parameters)\n",
    "* [Setting-up an End-to-end Block](#Setting-up-an-end-to-end-Block)\n",
    "* [Non-IDD versus IDD Benchmarks](#Non-IDD-versus-IDD-Benchmarks)\n",
    "* [Discussion-Optimizing IDD with Machine Learning](#Discussion-Optimizing-IDD-with-Machine-Learning)\n",
    "* [Comments](#Comments)\n",
    "* [List of References](#List-of-References)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configuration and Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T18:38:19.706599Z",
     "iopub.status.busy": "2026-08-06T18:38:19.706481Z",
     "iopub.status.idle": "2026-08-06T18:38:22.882759Z",
     "shell.execute_reply": "2026-08-06T18:38:22.881631Z"
    }
   },
   "outputs": [],
   "source": [
    "# Import Sionna\n",
    "try:\n",
    "    import sionna.phy\n",
    "except ImportError as e:\n",
    "    import os\n",
    "    import sys\n",
    "    if 'google.colab' in sys.modules:\n",
    "       # Install Sionna in Google Colab\n",
    "       print(\"Installing Sionna and restarting the runtime. Please run the cell again.\")\n",
    "       os.system(\"pip install sionna\")\n",
    "       os.kill(os.getpid(), 5)\n",
    "    else:\n",
    "       raise e\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import torch\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\n",
    "    \"ignore\",\n",
    "    message=\"Torchinductor does not support code generation for complex operators.*\",\n",
    ")\n",
    "warnings.filterwarnings(\n",
    "    \"ignore\",\n",
    "    message=\"`torch._prims_common.check` is deprecated.*\",\n",
    "    category=FutureWarning,\n",
    ")\n",
    "\n",
    "from sionna.phy import Block\n",
    "from sionna.phy.mimo import StreamManagement\n",
    "from sionna.phy.utils import sim_ber, ebnodb2no, expand_to_rank\n",
    "from sionna.phy.mapping import Mapper, Constellation, BinarySource\n",
    "from sionna.phy.ofdm import ResourceGrid, ResourceGridMapper, LSChannelEstimator, \\\n",
    "                            LinearDetector, KBestDetector, EPDetector, \\\n",
    "                            RemoveNulledSubcarriers, MMSEPICDetector\n",
    "from sionna.phy.channel import OFDMChannel, RayleighBlockFading, gen_single_sector_topology\n",
    "from sionna.phy.channel.tr38901 import UMa, Antenna, PanelArray\n",
    "from sionna.phy.fec.ldpc import LDPC5GEncoder, LDPC5GDecoder\n",
    "\n",
    "sionna.phy.config.seed = 42 # Set seed for reproducible random number generation"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation Parameters\n",
    "In the following, we set the simulation parameters. Please modify at will; adapting the batch size to your hardware setup might be beneficial.\n",
    "\n",
    "The standard configuration implements a coded 5G inspired MU-MIMO OFDM uplink transmission over 3GPP UMa channels, with 4 single-antenna UEs, 16-QAM modulation, and a 16 element dual-polarized uniform planar antenna array (UPA) at the gNB. We implement least squares channel estimation with linear interpolation. Alternatively, we implement iid Rayleigh fading channels and perfect channel state information (CSI), which can be controlled by the model parameter `perfect_csi_rayleigh`.\n",
    "As channel code, we apply a rate-matched 5G LDPC code at rate 1/2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T18:38:22.885199Z",
     "iopub.status.busy": "2026-08-06T18:38:22.884921Z",
     "iopub.status.idle": "2026-08-06T18:38:23.302867Z",
     "shell.execute_reply": "2026-08-06T18:38:23.301888Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "batch_size = 64  # number of OFDM frames to be analyzed per batch\n",
    "num_iter = 128  # number of Monte Carlo Iterations (total number of Monte Carlo trials is num_iter*batch_size)\n",
    "num_steps = 11\n",
    "\n",
    "ebno_db_min_perf_csi = -10  # min EbNo value in dB for perfect csi benchmarks\n",
    "ebno_db_max_perf_csi = 0\n",
    "ebno_db_min_cest = -10\n",
    "ebno_db_max_cest = 10\n",
    "\n",
    "\n",
    "NUM_OFDM_SYMBOLS = 14\n",
    "FFT_SIZE = 12*4 # 4 PRBs\n",
    "SUBCARRIER_SPACING = 30e3 # Hz\n",
    "CARRIER_FREQUENCY = 3.5e9 # Hz\n",
    "SPEED = 3. # m/s\n",
    "num_bits_per_symbol = 4 # 16 QAM\n",
    "n_ue = 4 # 4 UEs\n",
    "NUM_RX_ANT = 16 # 16 BS antennas\n",
    "num_pilot_symbols = 2\n",
    "\n",
    "# The user terminals (UTs) are equipped with a single antenna\n",
    "# with vertial polarization.\n",
    "UT_ANTENNA = Antenna(polarization='single',\n",
    "                     polarization_type='V',\n",
    "                     antenna_pattern='omni', # Omnidirectional antenna pattern\n",
    "                     carrier_frequency=CARRIER_FREQUENCY)\n",
    "\n",
    "# The base station is equipped with an antenna\n",
    "# array of 8 cross-polarized antennas,\n",
    "# resulting in a total of 16 antenna elements.\n",
    "BS_ARRAY = PanelArray(num_rows_per_panel=2,\n",
    "                      num_cols_per_panel=4,\n",
    "                      polarization='dual',\n",
    "                      polarization_type='cross',\n",
    "                      antenna_pattern='38.901', # 3GPP 38.901 antenna pattern\n",
    "                      carrier_frequency=CARRIER_FREQUENCY)\n",
    "\n",
    "# 3GPP UMa channel model is considered\n",
    "channel_model_uma = UMa(carrier_frequency=CARRIER_FREQUENCY,\n",
    "                    o2i_model='low',\n",
    "                    ut_array=UT_ANTENNA,\n",
    "                    bs_array=BS_ARRAY,\n",
    "                    direction='uplink',\n",
    "                    enable_shadow_fading=False,\n",
    "                    enable_pathloss=False)\n",
    "\n",
    "channel_model_rayleigh = RayleighBlockFading(num_rx=1, num_rx_ant=NUM_RX_ANT, num_tx=n_ue, num_tx_ant=1)\n",
    "\n",
    "constellation = Constellation(\"qam\", num_bits_per_symbol=num_bits_per_symbol)\n",
    "\n",
    "rx_tx_association = np.ones([1, n_ue])\n",
    "sm = StreamManagement(rx_tx_association, 1)\n",
    "\n",
    "# Parameterize the OFDM channel\n",
    "rg = ResourceGrid(num_ofdm_symbols=NUM_OFDM_SYMBOLS, pilot_ofdm_symbol_indices = [2, 11],\n",
    "                  fft_size=FFT_SIZE, num_tx=n_ue,\n",
    "                  pilot_pattern = \"kronecker\",\n",
    "                  subcarrier_spacing=SUBCARRIER_SPACING)\n",
    "\n",
    "rg.show()\n",
    "plt.show()\n",
    "\n",
    "# Parameterize the LDPC code\n",
    "R = 0.5  # rate 1/2\n",
    "N = int(FFT_SIZE * (NUM_OFDM_SYMBOLS - 2) * num_bits_per_symbol)\n",
    "# N = int((FFT_SIZE) * (NUM_OFDM_SYMBOLS - 2) * num_bits_per_symbol)\n",
    "# code length; - 12 because of 11 guard carriers and 1 DC carrier, - 2 becaues of 2 pilot symbols\n",
    "K = int(N * R)  # number of information bits per codeword\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting-up an End-to-end Block\n",
    "\n",
    "Now, we define the baseline models for benchmarking. Let us start with the non-IDD models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T18:38:23.349022Z",
     "iopub.status.busy": "2026-08-06T18:38:23.348867Z",
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     "shell.execute_reply": "2026-08-06T18:38:23.356216Z"
    }
   },
   "outputs": [],
   "source": [
    "class NonIddModel(Block):\n",
    "    def __init__(self, num_bp_iter=12, detector='lmmse', cest_type=\"LS\", interp=\"lin\", perfect_csi_rayleigh=False):\n",
    "        super().__init__()\n",
    "        self._num_bp_iter = int(num_bp_iter)\n",
    "        ######################################\n",
    "        ## Transmitter\n",
    "        self._binary_source = BinarySource()\n",
    "        self._encoder = LDPC5GEncoder(K, N, num_bits_per_symbol=num_bits_per_symbol)\n",
    "        self._mapper = Mapper(constellation=constellation)\n",
    "        self._rg_mapper = ResourceGridMapper(rg)\n",
    "\n",
    "        # Channel\n",
    "        if perfect_csi_rayleigh:\n",
    "            self._channel_model = channel_model_rayleigh\n",
    "        else:\n",
    "            self._channel_model = channel_model_uma\n",
    "\n",
    "        self._channel = OFDMChannel(channel_model=self._channel_model,\n",
    "                                    resource_grid=rg,\n",
    "                                    add_awgn=True, normalize_channel=True, return_channel=True)\n",
    "\n",
    "        # Receiver\n",
    "        self._cest_type = cest_type\n",
    "        self._interp = interp\n",
    "\n",
    "        # Channel estimation\n",
    "        self._perfect_csi_rayleigh = perfect_csi_rayleigh\n",
    "        if self._perfect_csi_rayleigh:\n",
    "            self._removeNulledSc = RemoveNulledSubcarriers(rg)\n",
    "        elif cest_type == \"LS\":\n",
    "            self._ls_est = LSChannelEstimator(rg, interpolation_type=interp)\n",
    "        else:\n",
    "            raise NotImplementedError('Not implemented:' + cest_type)\n",
    "\n",
    "        # Detection\n",
    "        if detector == \"lmmse\":\n",
    "            self._detector = LinearDetector(\"lmmse\", 'bit', \"maxlog\", rg, sm, constellation_type=\"qam\",\n",
    "                                            num_bits_per_symbol=num_bits_per_symbol, hard_out=False)\n",
    "        elif detector == \"k-best\":\n",
    "            k = 64\n",
    "            self._detector = KBestDetector('bit', n_ue, k, rg, sm, constellation_type=\"qam\",\n",
    "                                           num_bits_per_symbol=num_bits_per_symbol, hard_out=False)\n",
    "        elif detector == \"ep\":\n",
    "            l = 10\n",
    "            self._detector = EPDetector('bit', rg, sm, num_bits_per_symbol, l=l, hard_out=False)\n",
    "\n",
    "        # Forward error correction (decoder)\n",
    "        self._decoder = LDPC5GDecoder(self._encoder, return_infobits=True, hard_out=True, num_iter=num_bp_iter, cn_update='minsum')\n",
    "\n",
    "    def new_topology(self, batch_size):\n",
    "        \"\"\"Set new topology\"\"\"\n",
    "        if isinstance(self._channel_model, UMa):\n",
    "            # sensible values according to 3GPP standard, no mobility by default\n",
    "            topology = gen_single_sector_topology(batch_size,\n",
    "                                                  n_ue, max_ut_velocity=SPEED,\n",
    "                                                  scenario=\"uma\")\n",
    "            self._channel_model.set_topology(*topology)\n",
    "\n",
    "    def call(self, batch_size, ebno_db):\n",
    "        self.new_topology(batch_size)\n",
    "\n",
    "        if len(ebno_db.shape) == 0:\n",
    "            ebno_db = torch.full((batch_size,), ebno_db, dtype=torch.float32, device=ebno_db.device if isinstance(ebno_db, torch.Tensor) else None)\n",
    "\n",
    "        ######################################\n",
    "        ## Transmitter\n",
    "        no = ebnodb2no(ebno_db=ebno_db, num_bits_per_symbol=num_bits_per_symbol,\n",
    "                       coderate=R)  # normalize in OFDM freq. domain\n",
    "        b = self._binary_source([batch_size, n_ue, 1, K])\n",
    "        c = self._encoder(b)\n",
    "        # Modulation\n",
    "        x = self._mapper(c)\n",
    "        x_rg = self._rg_mapper(x)\n",
    "\n",
    "        ######################################\n",
    "        ## Channel\n",
    "        # A batch of new channel realizations is sampled and applied at every inference\n",
    "        no_ = expand_to_rank(no, x_rg.dim())\n",
    "        y, h = self._channel(x_rg, no_)\n",
    "\n",
    "        ######################################\n",
    "        ## Receiver\n",
    "        if self._perfect_csi_rayleigh:\n",
    "            h_hat = self._removeNulledSc(h)\n",
    "            chan_est_var = torch.zeros_like(h_hat)  # No channel estimation error when perfect CSI knowledge is assumed\n",
    "        else:\n",
    "            h_hat, chan_est_var = self._ls_est(y, no)\n",
    "\n",
    "        llr_ch = self._detector(y, h_hat, chan_est_var, no)  # detector\n",
    "        b_hat = self._decoder(llr_ch)\n",
    "        return b, b_hat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we implement the IDD model with a non-resetting LDPC decoder, as in [3], i.e., we forward the LLRs and decoder state from one IDD iteration to the following."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T18:38:23.359395Z",
     "iopub.status.busy": "2026-08-06T18:38:23.359220Z",
     "iopub.status.idle": "2026-08-06T18:38:23.365357Z",
     "shell.execute_reply": "2026-08-06T18:38:23.364459Z"
    }
   },
   "outputs": [],
   "source": [
    "class IddModel(NonIddModel):  # inherited from NonIddModel\n",
    "    def __init__(self, num_idd_iter=3, num_bp_iter_per_idd_iter=12, cest_type=\"LS\", interp=\"lin\", perfect_csi_rayleigh=False):\n",
    "        super().__init__(num_bp_iter=num_bp_iter_per_idd_iter, detector=\"lmmse\", cest_type=cest_type,\n",
    "                         interp=interp, perfect_csi_rayleigh=perfect_csi_rayleigh)\n",
    "        # first IDD detector is LMMSE as MMSE-PIC with zero-prior boils down to soft-output LMMSE\n",
    "        self._num_idd_iter = num_idd_iter\n",
    "        self._siso_detector = MMSEPICDetector(output=\"bit\", resource_grid=rg, stream_management=sm,\n",
    "                                              demapping_method='maxlog', constellation=constellation, num_iter=1,\n",
    "                                              hard_out=False)\n",
    "        self._siso_decoder = LDPC5GDecoder(self._encoder, return_infobits=False,\n",
    "                                           num_iter=num_bp_iter_per_idd_iter, return_state=True, hard_out=False, cn_update='minsum')\n",
    "        self._decoder = LDPC5GDecoder(self._encoder, return_infobits=True, return_state=True, hard_out=True, num_iter=num_bp_iter_per_idd_iter, cn_update='minsum')\n",
    "        # last decoder must also be stateful\n",
    "\n",
    "    def call(self, batch_size, ebno_db):\n",
    "        self.new_topology(batch_size)\n",
    "\n",
    "        if len(ebno_db.shape) == 0:\n",
    "            ebno_db = torch.full((batch_size,), ebno_db, dtype=torch.float32, device=ebno_db.device if isinstance(ebno_db, torch.Tensor) else None)\n",
    "\n",
    "        ######################################\n",
    "        ## Transmitter\n",
    "        no = ebnodb2no(ebno_db=ebno_db, num_bits_per_symbol=num_bits_per_symbol,\n",
    "                       coderate=R)  # normalize in OFDM freq. domain\n",
    "        b = self._binary_source([batch_size, n_ue, 1, K])\n",
    "        c = self._encoder(b)\n",
    "        # Modulation\n",
    "        x = self._mapper(c)\n",
    "        x_rg = self._rg_mapper(x)\n",
    "\n",
    "        ######################################\n",
    "        ## Channel\n",
    "        # A batch of new channel realizations is sampled and applied at every inference\n",
    "        no_ = expand_to_rank(no, x_rg.dim())\n",
    "        y, h = self._channel(x_rg, no_)\n",
    "\n",
    "        ######################################\n",
    "        ## Receiver\n",
    "        if self._perfect_csi_rayleigh:\n",
    "            h_hat = self._removeNulledSc(h)\n",
    "            chan_est_var = torch.zeros_like(h_hat)\n",
    "        else:\n",
    "            h_hat, chan_est_var = self._ls_est(y, no)\n",
    "\n",
    "        llr_ch = self._detector(y, h_hat, chan_est_var, no)  # soft-output LMMSE detection\n",
    "        msg_v2c = None\n",
    "\n",
    "        if self._num_idd_iter >= 2:\n",
    "            # perform first iteration outside the loop to initialize msg_v2c\n",
    "            llr_dec, msg_v2c = self._siso_decoder(llr_ch, msg_v2c=msg_v2c)\n",
    "            # forward a posteriori information from decoder\n",
    "\n",
    "            llr_ch = self._siso_detector(y, h_hat, llr_dec, chan_est_var, no)\n",
    "            # forward extrinsic information\n",
    "\n",
    "            # IDD iteration loop (PyTorch: use simple Python for loop)\n",
    "            for _ in range(self._num_idd_iter - 2):\n",
    "                llr_dec, msg_v2c = self._siso_decoder(llr_ch, msg_v2c=msg_v2c)\n",
    "                # forward a posteriori information from decoder\n",
    "                llr_ch = self._siso_detector(y, h_hat, llr_dec, chan_est_var, no)\n",
    "                # forward extrinsic information from detector\n",
    "\n",
    "        b_hat, _ = self._decoder(llr_ch, msg_v2c=msg_v2c)    # final hard-output decoding (only returning information bits)\n",
    "        return b, b_hat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Non-IDD versus IDD Benchmarks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T18:38:23.367213Z",
     "iopub.status.busy": "2026-08-06T18:38:23.367088Z",
     "iopub.status.idle": "2026-08-06T18:56:32.226419Z",
     "shell.execute_reply": "2026-08-06T18:56:32.225351Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 2.1196e-01 | 1.0000e+00 |      250039 |     1179648 |         1024 |        1024 |        19.8 |reached target block errors\n",
      "     -9.0 | 1.8540e-01 | 1.0000e+00 |      218710 |     1179648 |         1024 |        1024 |         0.0 |reached target block errors\n",
      "     -8.0 | 1.1020e-01 | 9.6582e-01 |      130003 |     1179648 |          989 |        1024 |         0.0 |reached target block errors\n",
      "     -7.0 | 1.6189e-02 | 3.5234e-01 |       47743 |     2949120 |          902 |        2560 |         0.1 |reached target block errors\n",
      "     -6.0 | 1.1558e-03 | 3.3923e-02 |       32381 |    28016640 |          825 |       24320 |         0.9 |reached target block errors\n",
      "     -5.0 | 7.4810e-05 | 2.5940e-03 |        2824 |    37748736 |           85 |       32768 |         1.2 |reached max iterations\n",
      "     -4.0 | 2.8875e-06 | 1.8311e-04 |         109 |    37748736 |            6 |       32768 |         1.2 |reached max iterations\n",
      "     -3.0 | 0.0000e+00 | 0.0000e+00 |           0 |    37748736 |            0 |       32768 |         1.2 |reached max iterations\n",
      "\n",
      "Simulation stopped as no error occurred @ EbNo = -3.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 2.1057e-01 | 1.0000e+00 |      248398 |     1179648 |         1024 |        1024 |        18.1 |reached target block errors\n",
      "     -9.0 | 1.8344e-01 | 1.0000e+00 |      216399 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -8.0 | 1.0231e-01 | 9.6387e-01 |      120694 |     1179648 |          987 |        1024 |         0.1 |reached target block errors\n",
      "     -7.0 | 1.1886e-02 | 2.7441e-01 |       42065 |     3538944 |          843 |        3072 |         0.2 |reached target block errors\n",
      "     -6.0 | 5.1496e-04 | 1.5411e-02 |       19439 |    37748736 |          505 |       32768 |         2.0 |reached max iterations\n",
      "     -5.0 | 3.3114e-06 | 3.3569e-04 |         125 |    37748736 |           11 |       32768 |         2.0 |reached max iterations\n",
      "     -4.0 | 0.0000e+00 | 0.0000e+00 |           0 |    37748736 |            0 |       32768 |         2.0 |reached max iterations\n",
      "\n",
      "Simulation stopped as no error occurred @ EbNo = -4.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 2.1118e-01 | 1.0000e+00 |      249118 |     1179648 |         1024 |        1024 |        12.6 |reached target block errors\n",
      "     -9.0 | 1.8525e-01 | 1.0000e+00 |      218526 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -8.0 | 1.1738e-01 | 9.9512e-01 |      138464 |     1179648 |         1019 |        1024 |         0.1 |reached target block errors\n",
      "     -7.0 | 2.1787e-02 | 6.2370e-01 |       38552 |     1769472 |          958 |        1536 |         0.2 |reached target block errors\n",
      "     -6.0 | 8.9383e-04 | 4.9579e-02 |       17134 |    19169280 |          825 |       16640 |         1.7 |reached target block errors\n",
      "     -5.0 | 4.4107e-05 | 1.3123e-03 |        1665 |    37748736 |           43 |       32768 |         3.2 |reached max iterations\n",
      "     -4.0 | 0.0000e+00 | 0.0000e+00 |           0 |    37748736 |            0 |       32768 |         3.2 |reached max iterations\n",
      "\n",
      "Simulation stopped as no error occurred @ EbNo = -4.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 2.1150e-01 | 1.0000e+00 |      249496 |     1179648 |         1024 |        1024 |        38.6 |reached target block errors\n",
      "     -9.0 | 1.8541e-01 | 1.0000e+00 |      218720 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -8.0 | 8.6595e-02 | 7.0469e-01 |      127690 |     1474560 |          902 |        1280 |         0.1 |reached target block errors\n",
      "     -7.0 | 4.0342e-03 | 5.6469e-02 |       67814 |    16809984 |          824 |       14592 |         1.1 |reached target block errors\n",
      "     -6.0 | 7.0784e-05 | 1.0986e-03 |        2672 |    37748736 |           36 |       32768 |         2.6 |reached max iterations\n",
      "     -5.0 | 0.0000e+00 | 0.0000e+00 |           0 |    37748736 |            0 |       32768 |         2.6 |reached max iterations\n",
      "\n",
      "Simulation stopped as no error occurred @ EbNo = -5.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 2.1197e-01 | 1.0000e+00 |      250046 |     1179648 |         1024 |        1024 |        61.7 |reached target block errors\n",
      "     -9.0 | 1.8645e-01 | 9.9805e-01 |      219951 |     1179648 |         1022 |        1024 |         0.1 |reached target block errors\n",
      "     -8.0 | 8.0347e-02 | 6.0547e-01 |      142171 |     1769472 |          930 |        1536 |         0.2 |reached target block errors\n",
      "     -7.0 | 1.7055e-03 | 1.9592e-02 |       64379 |    37748736 |          642 |       32768 |         3.9 |reached max iterations\n",
      "     -6.0 | 8.7950e-06 | 1.5259e-04 |         332 |    37748736 |            5 |       32768 |         3.9 |reached max iterations\n",
      "     -5.0 | 0.0000e+00 | 0.0000e+00 |           0 |    37748736 |            0 |       32768 |         3.9 |reached max iterations\n",
      "\n",
      "Simulation stopped as no error occurred @ EbNo = -5.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 2.9994e-01 | 1.0000e+00 |      353818 |     1179648 |         1024 |        1024 |       398.0 |reached target block errors\n",
      "     -8.0 | 2.6506e-01 | 1.0000e+00 |      312680 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -6.0 | 2.3112e-01 | 1.0000e+00 |      272642 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -4.0 | 1.4539e-01 | 8.5254e-01 |      171508 |     1179648 |          873 |        1024 |         0.1 |reached target block errors\n",
      "     -2.0 | 5.5352e-02 | 3.7934e-01 |      146917 |     2654208 |          874 |        2304 |         0.2 |reached target block errors\n",
      "      0.0 | 1.9135e-02 | 1.5004e-01 |      124147 |     6488064 |          845 |        5632 |         0.4 |reached target block errors\n",
      "      2.0 | 6.3241e-03 | 4.7564e-02 |      126824 |    20054016 |          828 |       17408 |         1.3 |reached target block errors\n",
      "      4.0 | 2.4039e-03 | 1.8585e-02 |       90743 |    37748736 |          609 |       32768 |         2.4 |reached max iterations\n",
      "      6.0 | 1.4846e-03 | 1.0406e-02 |       56041 |    37748736 |          341 |       32768 |         2.4 |reached max iterations\n",
      "      8.0 | 9.0758e-04 | 6.4087e-03 |       34260 |    37748736 |          210 |       32768 |         2.4 |reached max iterations\n",
      "     10.0 | 7.9258e-04 | 5.6152e-03 |       29919 |    37748736 |          184 |       32768 |         2.5 |reached max iterations\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 3.0036e-01 | 1.0000e+00 |      354323 |     1179648 |         1024 |        1024 |        69.6 |reached target block errors\n",
      "     -8.0 | 2.6705e-01 | 1.0000e+00 |      315026 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -6.0 | 2.2823e-01 | 1.0000e+00 |      269232 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -4.0 | 1.4329e-01 | 8.7207e-01 |      169032 |     1179648 |          893 |        1024 |         0.1 |reached target block errors\n",
      "     -2.0 | 5.1803e-02 | 3.6589e-01 |      137497 |     2654208 |          843 |        2304 |         0.2 |reached target block errors\n",
      "      0.0 | 1.5784e-02 | 1.2425e-01 |      121028 |     7667712 |          827 |        6656 |         0.7 |reached target block errors\n",
      "      2.0 | 4.5270e-03 | 3.6111e-02 |      120155 |    26542080 |          832 |       23040 |         2.3 |reached target block errors\n",
      "      4.0 | 1.5330e-03 | 1.2238e-02 |       57870 |    37748736 |          401 |       32768 |         3.2 |reached max iterations\n",
      "      6.0 | 8.7129e-04 | 6.5613e-03 |       32890 |    37748736 |          215 |       32768 |         3.2 |reached max iterations\n",
      "      8.0 | 8.8427e-04 | 6.8054e-03 |       33380 |    37748736 |          223 |       32768 |         3.2 |reached max iterations\n",
      "     10.0 | 8.9539e-04 | 6.5308e-03 |       33800 |    37748736 |          214 |       32768 |         3.2 |reached max iterations\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 3.0795e-01 | 1.0000e+00 |      363274 |     1179648 |         1024 |        1024 |        45.8 |reached target block errors\n",
      "     -8.0 | 2.6963e-01 | 1.0000e+00 |      318069 |     1179648 |         1024 |        1024 |         0.3 |reached target block errors\n",
      "     -6.0 | 2.3311e-01 | 1.0000e+00 |      274990 |     1179648 |         1024 |        1024 |         0.3 |reached target block errors\n",
      "     -4.0 | 1.5972e-01 | 9.6973e-01 |      188412 |     1179648 |          993 |        1024 |         0.3 |reached target block errors\n",
      "     -2.0 | 5.7947e-02 | 4.2871e-01 |      136713 |     2359296 |          878 |        2048 |         0.7 |reached target block errors\n",
      "      0.0 | 1.3108e-02 | 1.0729e-01 |      115975 |     8847360 |          824 |        7680 |         2.6 |reached target block errors\n",
      "      2.0 | 2.7485e-03 | 2.3041e-02 |      103753 |    37748736 |          755 |       32768 |        11.1 |reached max iterations\n",
      "      4.0 | 9.6032e-04 | 6.8054e-03 |       36251 |    37748736 |          223 |       32768 |        11.1 |reached max iterations\n",
      "      6.0 | 5.9427e-04 | 4.4250e-03 |       22433 |    37748736 |          145 |       32768 |        11.1 |reached max iterations\n",
      "      8.0 | 6.7970e-04 | 4.2114e-03 |       25658 |    37748736 |          138 |       32768 |        11.1 |reached max iterations\n",
      "     10.0 | 7.9907e-04 | 5.2795e-03 |       30164 |    37748736 |          173 |       32768 |        11.1 |reached max iterations\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 3.0577e-01 | 1.0000e+00 |      360697 |     1179648 |         1024 |        1024 |       110.2 |reached target block errors\n",
      "     -8.0 | 2.6854e-01 | 1.0000e+00 |      316784 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -6.0 | 2.3107e-01 | 1.0000e+00 |      272579 |     1179648 |         1024 |        1024 |         0.1 |reached target block errors\n",
      "     -4.0 | 1.4383e-01 | 7.6328e-01 |      212089 |     1474560 |          977 |        1280 |         0.2 |reached target block errors\n",
      "     -2.0 | 4.0266e-02 | 2.4730e-01 |      154374 |     3833856 |          823 |        3328 |         0.4 |reached target block errors\n",
      "      0.0 | 1.1274e-02 | 7.5127e-02 |      142973 |    12681216 |          827 |       11008 |         1.3 |reached target block errors\n",
      "      2.0 | 2.8745e-03 | 2.0508e-02 |      108508 |    37748736 |          672 |       32768 |         3.9 |reached max iterations\n",
      "      4.0 | 9.6946e-04 | 6.7749e-03 |       36596 |    37748736 |          222 |       32768 |         3.9 |reached max iterations\n",
      "      6.0 | 5.9507e-04 | 3.9368e-03 |       22463 |    37748736 |          129 |       32768 |         3.9 |reached max iterations\n",
      "      8.0 | 6.4415e-04 | 3.9978e-03 |       24316 |    37748736 |          131 |       32768 |         3.9 |reached max iterations\n",
      "     10.0 | 7.4620e-04 | 4.9438e-03 |       28168 |    37748736 |          162 |       32768 |         3.9 |reached max iterations\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "    -10.0 | 3.0289e-01 | 1.0000e+00 |      357298 |     1179648 |         1024 |        1024 |       135.1 |reached target block errors\n",
      "     -8.0 | 2.6773e-01 | 1.0000e+00 |      315824 |     1179648 |         1024 |        1024 |         0.2 |reached target block errors\n",
      "     -6.0 | 2.3291e-01 | 1.0000e+00 |      274754 |     1179648 |         1024 |        1024 |         0.2 |reached target block errors\n",
      "     -4.0 | 1.3728e-01 | 7.0078e-01 |      202426 |     1474560 |          897 |        1280 |         0.2 |reached target block errors\n",
      "     -2.0 | 3.8758e-02 | 2.1484e-01 |      171454 |     4423680 |          825 |        3840 |         0.6 |reached target block errors\n",
      "      0.0 | 9.7918e-03 | 5.6127e-02 |      164600 |    16809984 |          819 |       14592 |         2.4 |reached target block errors\n",
      "      2.0 | 2.4890e-03 | 1.4191e-02 |       93956 |    37748736 |          465 |       32768 |         5.3 |reached max iterations\n",
      "      4.0 | 9.6239e-04 | 5.3101e-03 |       36329 |    37748736 |          174 |       32768 |         5.3 |reached max iterations\n",
      "      6.0 | 6.0132e-04 | 3.8757e-03 |       22699 |    37748736 |          127 |       32768 |         5.3 |reached max iterations\n",
      "      8.0 | 7.8652e-04 | 4.3030e-03 |       29690 |    37748736 |          141 |       32768 |         5.3 |reached max iterations\n",
      "     10.0 | 5.5300e-04 | 3.9673e-03 |       20875 |    37748736 |          130 |       32768 |         5.3 |reached max iterations\n"
     ]
    }
   ],
   "source": [
    "# Range of SNR (dB)\n",
    "snr_range_cest = np.linspace(ebno_db_min_cest, ebno_db_max_cest, num_steps)\n",
    "snr_range_perf_csi = np.linspace(ebno_db_min_perf_csi, ebno_db_max_perf_csi, num_steps)\n",
    "\n",
    "def run_idd_sim(snr_range, perfect_csi_rayleigh):\n",
    "    lmmse = NonIddModel(detector=\"lmmse\", perfect_csi_rayleigh=perfect_csi_rayleigh)\n",
    "    k_best = NonIddModel(detector=\"k-best\", perfect_csi_rayleigh=perfect_csi_rayleigh)\n",
    "    ep = NonIddModel(detector=\"ep\", perfect_csi_rayleigh=perfect_csi_rayleigh)\n",
    "    idd2 = IddModel(num_idd_iter=2, perfect_csi_rayleigh=perfect_csi_rayleigh)\n",
    "    idd3 = IddModel(num_idd_iter=3, perfect_csi_rayleigh=perfect_csi_rayleigh)\n",
    "\n",
    "    if not perfect_csi_rayleigh:\n",
    "        lmmse._channel_model.allocate_topology_tensors(batch_size=batch_size, num_bs=1, num_ut=n_ue)\n",
    "        ep._channel_model.allocate_topology_tensors(batch_size=batch_size, num_bs=1, num_ut=n_ue)\n",
    "        idd2._channel_model.allocate_topology_tensors(batch_size=batch_size, num_bs=1, num_ut=n_ue)\n",
    "        idd3._channel_model.allocate_topology_tensors(batch_size=batch_size, num_bs=1, num_ut=n_ue)\n",
    "\n",
    "    ber_lmmse, bler_lmmse = sim_ber(lmmse,\n",
    "                                    snr_range,\n",
    "                                    batch_size=batch_size,\n",
    "                                    max_mc_iter=num_iter,\n",
    "                                    num_target_block_errors=int(batch_size * num_iter * 0.1),\n",
    "                                    compile_mode=\"default\",\n",
    "                                    verbose=True)\n",
    "\n",
    "    ber_ep, bler_ep = sim_ber(ep,\n",
    "                              snr_range,\n",
    "                              batch_size=batch_size,\n",
    "                              max_mc_iter=num_iter,\n",
    "                              num_target_block_errors=int(batch_size * num_iter * 0.1),\n",
    "                              compile_mode=\"default\",\n",
    "                              verbose=True)\n",
    "\n",
    "    ber_kbest, bler_kbest = sim_ber(k_best,\n",
    "                                    snr_range,\n",
    "                                    batch_size=batch_size,\n",
    "                                    max_mc_iter=num_iter,\n",
    "                                    num_target_block_errors=int(batch_size * num_iter * 0.1),\n",
    "                                    compile_mode=\"default\",\n",
    "                                    verbose=True)\n",
    "\n",
    "    ber_idd2, bler_idd2 = sim_ber(idd2,\n",
    "                                  snr_range,\n",
    "                                  batch_size=batch_size,\n",
    "                                  max_mc_iter=num_iter,\n",
    "                                  num_target_block_errors=int(batch_size * num_iter * 0.1),\n",
    "                                  compile_mode=\"default\",\n",
    "                                  verbose=True)\n",
    "\n",
    "    ber_idd3, bler_idd3 = sim_ber(idd3,\n",
    "                                  snr_range,\n",
    "                                  batch_size=batch_size,\n",
    "                                  max_mc_iter=num_iter,\n",
    "                                  num_target_block_errors=int(batch_size * num_iter * 0.1),\n",
    "                                  compile_mode=\"default\",\n",
    "                                  verbose=True)\n",
    "\n",
    "    return bler_lmmse, bler_ep, bler_kbest, bler_idd2, bler_idd3\n",
    "\n",
    "\n",
    "BLER = {}\n",
    "\n",
    "# Perfect CSI\n",
    "bler_lmmse, bler_ep, bler_kbest, bler_idd2, bler_idd3 = run_idd_sim(snr_range_perf_csi, perfect_csi_rayleigh=True)\n",
    "BLER['Perf. CSI / LMMSE'] = bler_lmmse\n",
    "BLER['Perf. CSI / EP'] = bler_ep\n",
    "BLER['Perf. CSI / K-Best'] = bler_kbest\n",
    "BLER['Perf. CSI / IDD2'] = bler_idd2\n",
    "BLER['Perf. CSI / IDD3'] = bler_idd3\n",
    "\n",
    "# Estimated CSI\n",
    "bler_lmmse, bler_ep, bler_kbest, bler_idd2, bler_idd3 = run_idd_sim(snr_range_cest, perfect_csi_rayleigh=False)\n",
    "BLER['Ch. Est. / LMMSE'] = bler_lmmse\n",
    "BLER['Ch. Est. / EP'] = bler_ep\n",
    "BLER['Ch. Est. / K-Best'] = bler_kbest\n",
    "BLER['Ch. Est. / IDD2'] = bler_idd2\n",
    "BLER['Ch. Est. / IDD3'] = bler_idd3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we plot the simulation results and observe that IDD outperforms the non-iterative methods by about 1 dB in the scenario with iid Rayleigh fading channels and perfect CSI. In the scenario with 3GPP UMa channels and estimated CSI, IDD performs slightly better than K-best, at considerably lower runtime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T18:56:32.228728Z",
     "iopub.status.busy": "2026-08-06T18:56:32.228430Z",
     "iopub.status.idle": "2026-08-06T18:56:32.656316Z",
     "shell.execute_reply": "2026-08-06T18:56:32.655615Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,2, figsize=(16,7))\n",
    "fig.suptitle(f\"{n_ue}x{NUM_RX_ANT} MU-MIMO UL | {2**num_bits_per_symbol}-QAM\")\n",
    "\n",
    "# Put all results on cpu\n",
    "BLER = {key: value.cpu().numpy() for key, value in BLER.items()}\n",
    "## Perfect CSI Rayleigh\n",
    "ax[0].set_title(\"Perfect CSI iid. Rayleigh\")\n",
    "ax[0].semilogy(snr_range_perf_csi, BLER['Perf. CSI / LMMSE'], 'x-', label='LMMSE', c='C0')\n",
    "ax[0].semilogy(snr_range_perf_csi, BLER['Perf. CSI / EP'], 'o--', label='EP', c='C0')\n",
    "ax[0].semilogy(snr_range_perf_csi, BLER['Perf. CSI / K-Best'], 's-.', label='K-Best', c='C0')\n",
    "ax[0].semilogy(snr_range_perf_csi, BLER['Perf. CSI / IDD2'], 'd:', label=r'IDD $I=2$', c='C1')\n",
    "ax[0].semilogy(snr_range_perf_csi, BLER['Perf. CSI / IDD3'], 'd:', label=r'IDD $I=3$', c='C2')\n",
    "\n",
    "ax[0].set_xlabel(r\"$E_b/N0$\")\n",
    "ax[0].set_ylabel(\"BLER\")\n",
    "ax[0].set_ylim((1e-4, 1.0))\n",
    "ax[0].legend()\n",
    "ax[0].grid(True)\n",
    "\n",
    "## Estimated CSI Rayleigh\n",
    "ax[1].set_title(\"Estimated CSI 3GPP UMa\")\n",
    "ax[1].semilogy(snr_range_cest, BLER['Ch. Est. / LMMSE'], 'x-', label='LMMSE', c='C0')\n",
    "ax[1].semilogy(snr_range_cest, BLER['Ch. Est. / EP'], 'o--', label='EP', c='C0')\n",
    "ax[1].semilogy(snr_range_cest, BLER['Ch. Est. / K-Best'], 's-.', label='K-Best', c='C0')\n",
    "ax[1].semilogy(snr_range_cest, BLER['Ch. Est. / IDD2'], 'd:', label=r'IDD $I=2$', c='C1')\n",
    "ax[1].semilogy(snr_range_cest, BLER['Ch. Est. / IDD3'], 'd:', label=r'IDD $I=3$', c='C2')\n",
    "\n",
    "ax[1].set_xlabel(r\"$E_b/N0$\")\n",
    "ax[1].set_ylabel(\"BLER\")\n",
    "ax[1].set_ylim((1e-3, 1.0))\n",
    "ax[1].legend()\n",
    "ax[1].grid(True)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Discussion-Optimizing IDD with Machine Learning\n",
    "Recent work [4] showed that IDD can be significantly improved by deep-unfolding, which applies machine learning to automatically tune hyperparameters of classical algorithms. The proposed *Deep-Unfolded Interleaved Detection and Decoding* method showed performance gains of up to 1.4 dB at the same computational complexity. A link to the simulation code is available in the [\"Made with Sionna\"](https://nvlabs.github.io/sionna/made_with_sionna.html#duidd-deep-unfolded-interleaved-detection-and-decoding-for-mimo-wireless-systems) section. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comments\n",
    "\n",
    "- As discussed in [3], IDD receivers with a non-resetting decoder converge faster than with resetting decoders. However, a resetting decoder (which does not forward `msg_vn`) might perform slightly better for a large number of message passing decoding iterations. Among other quantities, a scaling of the forwarded decoder state is optimized in the DUIDD receiver [4].\n",
    "- With estimated channels, we observed that the MMSE-PIC output LLRs become large, much larger as with non-iterative receive processing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## List of References\n",
    "\n",
    "[1] B. Hochwald and S. Ten Brink, [*\"Achieving near-capacity on a multiple-antenna channel,\"*](https://ieeexplore.ieee.org/abstract/document/1194444) IEEE Trans. Commun., vol. 51, no. 3, pp. 389–399, Mar. 2003.\n",
    "\n",
    "[2] C. Studer, S. Fateh, and D. Seethaler, [*\"ASIC implementation of soft-input soft-output MIMO detection\n",
    "using MMSE parallel interference cancellation,\"*](https://ieeexplore.ieee.org/abstract/document/5779722) IEEE Journal of Solid-State Circuits, vol. 46, no. 7, pp. 1754–1765, Jul. 2011.\n",
    "\n",
    "[3] W.-C. Sun, W.-H. Wu, C.-H. Yang, and Y.-L. Ueng, [*\"An iterative detection and decoding receiver for LDPC-coded MIMO systems,\"*](https://ieeexplore.ieee.org/abstract/document/7272776) IEEE Trans. Circuits Syst. I, vol. 62, no. 10, pp. 2512–2522, Oct. 2015.\n",
    "\n",
    "[4] R. Wiesmayr, C. Dick, J. Hoydis, and C. Studer, [*\"DUIDD: Deep-unfolded interleaved detection and decoding for MIMO wireless systems,\"*](https://arxiv.org/abs/2212.07816) in Asilomar Conf. Signals, Syst., Comput., Oct. 2022."
   ]
  }
 ],
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