{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f543de9b-3858-45dd-bddf-cddddcc60da3",
   "metadata": {},
   "source": [
    "# Part 2: Differentiable Communication Systems"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c55670f1-3ee6-481d-9661-d59e61074818",
   "metadata": {},
   "source": [
    "This tutorial will guide you through Sionna, from its basic principles to the implementation of a point-to-point link with a 5G NR compliant code and a 3GPP channel model.\n",
    "You will also learn how to write custom trainable layers by implementing a state of the art neural receiver, and how to train and evaluate end-to-end communication systems.\n",
    "\n",
    "The tutorial is structured in four notebooks:\n",
    "\n",
    "- Part I: Getting started with Sionna\n",
    "\n",
    "- **Part II: Differentiable Communication Systems**\n",
    "\n",
    "- Part III: Advanced Link-level Simulations\n",
    "\n",
    "- Part IV: Toward Learned Receivers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28fa5595",
   "metadata": {},
   "source": [
    "The [official documentation](https://nvlabs.github.io/sionna/index.html) provides key material on how to use Sionna and how its components are implemented."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7c4211f-beee-4142-9289-c385d0180877",
   "metadata": {},
   "source": [
    "* [Imports](#Imports)\n",
    "* [Gradient Computation Through End-to-end Systems](#Gradient-Computation-Through-End-to-end-Systems)\n",
    "* [Creating Custom Layers](#Creating-Custom-Layers)\n",
    "* [Setting up Training Loops](#Setting-up-Training-Loops)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74a184ac-1f64-407f-9a24-c53d40799be2",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d84bd69e-59f2-4a42-8dd3-730c8c1d821e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:36.012741Z",
     "iopub.status.busy": "2026-08-06T15:53:36.012627Z",
     "iopub.status.idle": "2026-08-06T15:53:42.250109Z",
     "shell.execute_reply": "2026-08-06T15:53:42.249334Z"
    }
   },
   "outputs": [],
   "source": [
    "import os # Configure which GPU\n",
    "if os.getenv(\"CUDA_VISIBLE_DEVICES\") is None:\n",
    "    gpu_num = 0 # Use \"\" to use the CPU\n",
    "    os.environ[\"CUDA_VISIBLE_DEVICES\"] = f\"{gpu_num}\"\n",
    "\n",
    "# Import Sionna\n",
    "try:\n",
    "    import sionna as sn\n",
    "    import sionna.phy\n",
    "except ImportError as e:\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",
    "import numpy as np\n",
    "\n",
    "# For plotting\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# PyTorch imports for the implementation of the neural receiver\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "# Set seed for reproducible results\n",
    "sn.phy.config.seed = 42"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dacb1e70",
   "metadata": {},
   "source": [
    "## Gradient Computation Through End-to-end Systems<a class=\"anchor\" id=\"Gradient-Computation-Through-End-to-end-Systems\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f617618",
   "metadata": {},
   "source": [
    "Let's start by setting up a simple communication system that transmit bits modulated as QAM symbols over an AWGN channel.\n",
    "\n",
    "However, compared to what we have previously done, we now make the constellation\n",
    "*trainable*. With Sionna, achieving this by assigning trainable points to a\n",
    "`Constellation` instance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a7f9b5bd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:42.252964Z",
     "iopub.status.busy": "2026-08-06T15:53:42.252693Z",
     "iopub.status.idle": "2026-08-06T15:53:42.447090Z",
     "shell.execute_reply": "2026-08-06T15:53:42.446142Z"
    }
   },
   "outputs": [],
   "source": [
    "# Binary source to generate uniform i.i.d. bits\n",
    "binary_source = sn.phy.mapping.BinarySource()\n",
    "\n",
    "# 64-QAM constellation\n",
    "NUM_BITS_PER_SYMBOL = 6\n",
    "qam_constellation = sn.phy.mapping.Constellation(\"qam\", NUM_BITS_PER_SYMBOL)\n",
    "\n",
    "# Make a trainable constellation initialized with QAM points\n",
    "# In PyTorch, we use tensors with requires_grad=True for trainable parameters\n",
    "trainable_points = torch.stack([qam_constellation.points.real.clone(),\n",
    "                                qam_constellation.points.imag.clone()], dim=0)\n",
    "trainable_points.requires_grad_(True)\n",
    "\n",
    "constellation = sn.phy.mapping.Constellation(\"custom\",\n",
    "                                             num_bits_per_symbol=NUM_BITS_PER_SYMBOL,\n",
    "                                             points=torch.complex(trainable_points[0], trainable_points[1]),\n",
    "                                             normalize=True,\n",
    "                                             center=True)\n",
    "\n",
    "# Mapper and demapper\n",
    "mapper = sn.phy.mapping.Mapper(constellation=constellation)\n",
    "demapper = sn.phy.mapping.Demapper(\"app\", constellation=constellation)\n",
    "\n",
    "# AWGN channel\n",
    "awgn_channel = sn.phy.channel.AWGN()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1b8e774",
   "metadata": {},
   "source": [
    "As we have already seen, we can now easily simulate forward passes through the system we have just setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6afe9194",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:42.449232Z",
     "iopub.status.busy": "2026-08-06T15:53:42.449099Z",
     "iopub.status.idle": "2026-08-06T15:53:42.719595Z",
     "shell.execute_reply": "2026-08-06T15:53:42.718701Z"
    }
   },
   "outputs": [],
   "source": [
    "BATCH_SIZE = 128 # How many examples are processed by Sionna in parallel\n",
    "EBN0_DB = 17.0 # Eb/N0 in dB\n",
    "\n",
    "no = sn.phy.utils.ebnodb2no(ebno_db=EBN0_DB,\n",
    "                        num_bits_per_symbol=NUM_BITS_PER_SYMBOL,\n",
    "                        coderate=1.0) # Coderate set to 1 as we do uncoded transmission here\n",
    "\n",
    "bits = binary_source([BATCH_SIZE,\n",
    "                        1200]) # Blocklength\n",
    "x = mapper(bits)\n",
    "y = awgn_channel(x, no)\n",
    "llr = demapper(y,no)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39061033",
   "metadata": {},
   "source": [
    "Just for fun, let's visualize the channel inputs and outputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3538928a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:42.721896Z",
     "iopub.status.busy": "2026-08-06T15:53:42.721760Z",
     "iopub.status.idle": "2026-08-06T15:53:43.820428Z",
     "shell.execute_reply": "2026-08-06T15:53:43.819663Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "plt.axes().set_aspect(1.0)\n",
    "plt.grid(True)\n",
    "plt.scatter(y.real.cpu().detach(), y.imag.cpu().detach(), label='Output')\n",
    "plt.scatter(x.real.cpu().detach(), x.imag.cpu().detach(), label='Input')\n",
    "plt.legend(fontsize=20);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2dc0b529",
   "metadata": {},
   "source": [
    "Let's now *optimize* the constellation through *stochastic gradient descent* (SGD). As we will see, this is made very easy by Sionna.\n",
    "\n",
    "We need to define a *loss function* that we will aim to minimize.\n",
    "\n",
    "We can see the task of the receiver as jointly solving, for each received symbol, `NUM_BITS_PER_SYMBOL` binary classification problems in order to reconstruct the transmitted bits.\n",
    "Therefore, a natural choice for the loss function is the *binary cross-entropy* (BCE) applied to each bit and to each received symbol.\n",
    "\n",
    "*Remark:* The LLRs computed by the demapper are *logits* on the transmitted bits, and can therefore be used as-is to compute the BCE without any additional processing.\n",
    "*Remark 2:* The BCE is closely related to an achievable information rate for bit-interleaved coded modulation systems [1,2]\n",
    "\n",
    "[1] Georg Böcherer, \"Principles of Coded Modulation\", [available online](http://www.georg-boecherer.de/bocherer2018principles.pdf)\n",
    "\n",
    "[2] F. Ait Aoudia and J. Hoydis, \"End-to-End Learning for OFDM: From Neural Receivers to Pilotless Communication,\" in IEEE Transactions on Wireless Communications, vol. 21, no. 2, pp. 1049-1063, Feb. 2022, doi: 10.1109/TWC.2021.3101364."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "03d7c7b5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:43.822805Z",
     "iopub.status.busy": "2026-08-06T15:53:43.822665Z",
     "iopub.status.idle": "2026-08-06T15:53:43.831103Z",
     "shell.execute_reply": "2026-08-06T15:53:43.830173Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BCE: 0.00020045811834279448\n"
     ]
    }
   ],
   "source": [
    "# Compute Binary Cross-Entropy loss\n",
    "# In PyTorch, we use F.binary_cross_entropy_with_logits\n",
    "loss = F.binary_cross_entropy_with_logits(llr, bits.float())\n",
    "\n",
    "print(f\"BCE: {loss.item()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "393dc7d2",
   "metadata": {},
   "source": [
    "One iteration of SGD consists in three steps:\n",
    "1. Perform a forward pass through the end-to-end system and compute the loss function\n",
    "2. Compute the gradient of the loss function with respect to the trainable weights\n",
    "3. Apply the gradient to the weights\n",
    "\n",
    "To enable gradient computation, we need to ensure our trainable parameters have `requires_grad=True`. PyTorch's autograd automatically tracks operations on such tensors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a6654b8a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:43.833270Z",
     "iopub.status.busy": "2026-08-06T15:53:43.833111Z",
     "iopub.status.idle": "2026-08-06T15:53:43.839695Z",
     "shell.execute_reply": "2026-08-06T15:53:43.838922Z"
    }
   },
   "outputs": [],
   "source": [
    "# Forward pass with gradient tracking (trainable_points has requires_grad=True)\n",
    "bits = binary_source([BATCH_SIZE, 1200]) # Blocklength\n",
    "mapper.constellation.points = torch.complex(trainable_points[0], trainable_points[1])\n",
    "x = mapper(bits)\n",
    "y = awgn_channel(x, no)\n",
    "llr = demapper(y, no)\n",
    "loss = F.binary_cross_entropy_with_logits(llr, bits.float())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12d20342",
   "metadata": {},
   "source": [
    "Computing the gradient is done by calling `backward()` on the loss tensor. The gradients are then stored in the `.grad` attribute of each parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a68657af",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:43.841486Z",
     "iopub.status.busy": "2026-08-06T15:53:43.840896Z",
     "iopub.status.idle": "2026-08-06T15:53:43.904480Z",
     "shell.execute_reply": "2026-08-06T15:53:43.903150Z"
    }
   },
   "outputs": [],
   "source": [
    "# Compute gradients by calling backward()\n",
    "loss.backward()\n",
    "# The gradient is stored in trainable_points.grad\n",
    "gradient = trainable_points.grad"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "318aa681",
   "metadata": {},
   "source": [
    "`gradient` is a tensor with the same shape as the trainable variable it corresponds to.\n",
    "\n",
    "For this model, we only have a single trainable tensor: The constellation of shape [`2`, `2^NUM_BITS_PER_SYMBOL`], the first dimension corresponding to the real and imaginary components of the constellation points.\n",
    "\n",
    "*Remark:* It is important to notice that the gradient computation was performed *through the demapper and channel*, which are conventional non-trainable algorithms implemented as *differentiable* Sionna blocks. This key feature of Sionna enables the training of end-to-end communication systems that combine both trainable and conventional and/or non-trainable signal processing algorithms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7437d3f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:43.906384Z",
     "iopub.status.busy": "2026-08-06T15:53:43.906251Z",
     "iopub.status.idle": "2026-08-06T15:53:43.909594Z",
     "shell.execute_reply": "2026-08-06T15:53:43.909156Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([2, 64])\n"
     ]
    }
   ],
   "source": [
    "print(gradient.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4f7a8cc",
   "metadata": {},
   "source": [
    "Applying the gradient (third step) is performed using an *optimizer*. [Many optimizers are available as part of PyTorch](https://pytorch.org/docs/stable/optim.html), and we use in this notebook ``Adam``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "26b73d64",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:43.911173Z",
     "iopub.status.busy": "2026-08-06T15:53:43.911059Z",
     "iopub.status.idle": "2026-08-06T15:53:43.913188Z",
     "shell.execute_reply": "2026-08-06T15:53:43.912683Z"
    }
   },
   "outputs": [],
   "source": [
    "optimizer = torch.optim.Adam([trainable_points], lr=1e-2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd2b15d3",
   "metadata": {},
   "source": [
    "Using the optimizer, the gradients can be applied to the trainable weights to update them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "54565c6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:43.914311Z",
     "iopub.status.busy": "2026-08-06T15:53:43.914193Z",
     "iopub.status.idle": "2026-08-06T15:53:44.003759Z",
     "shell.execute_reply": "2026-08-06T15:53:44.002940Z"
    }
   },
   "outputs": [],
   "source": [
    "# Apply the gradients to update the trainable parameters\n",
    "optimizer.step()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9ef8110",
   "metadata": {},
   "source": [
    "Let's compare the constellation before and after the gradient application"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "31dd793c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:44.006027Z",
     "iopub.status.busy": "2026-08-06T15:53:44.005891Z",
     "iopub.status.idle": "2026-08-06T15:53:44.425027Z",
     "shell.execute_reply": "2026-08-06T15:53:44.424366Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = sn.phy.mapping.Constellation(\"qam\", NUM_BITS_PER_SYMBOL).show()\n",
    "fig.axes[0].scatter(trainable_points[0].detach().cpu(), trainable_points[1].detach().cpu(), label='After SGD')\n",
    "fig.axes[0].legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a936c10b",
   "metadata": {},
   "source": [
    "The SGD step has led to slight change in the position of the constellation points. Training of a communication system using SGD consists in looping over such SGD steps until a stop criterion is met."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "008a93d5",
   "metadata": {},
   "source": [
    "## Creating Custom Layers<a class=\"anchor\" id=\"Creating-Custom-Layers\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "244c594f",
   "metadata": {},
   "source": [
    "Custom trainable (or not trainable) algorithms can be implemented as [PyTorch\n",
    "modules](https://pytorch.org/docs/stable/nn.html) (`nn.Module`) or Sionna\n",
    "blocks. All Sionna components, such as the mapper, demapper, channel... are\n",
    "implemented as Sionna blocks which inherit from the `nn.Module`.\n",
    "\n",
    "To illustrate how this can be done, the next cell implements a simple neural network-based demapper which consists of three dense (linear) layers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9670872b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:44.427339Z",
     "iopub.status.busy": "2026-08-06T15:53:44.427209Z",
     "iopub.status.idle": "2026-08-06T15:53:44.430831Z",
     "shell.execute_reply": "2026-08-06T15:53:44.430249Z"
    }
   },
   "outputs": [],
   "source": [
    "class NeuralDemapper(nn.Module): # Inherits from PyTorch Module\n",
    "\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "\n",
    "        # The three linear layers that form the custom trainable neural network-based demapper\n",
    "        self.dense_1 = nn.Linear(2, 64)\n",
    "        self.dense_2 = nn.Linear(64, 64)\n",
    "        self.dense_3 = nn.Linear(64, NUM_BITS_PER_SYMBOL) # The last layer has no activation and therefore outputs logits, i.e., LLRs\n",
    "\n",
    "    def forward(self, y):\n",
    "\n",
    "        # y : complex-valued with shape [batch size, block length]\n",
    "        # y is first mapped to a real-valued tensor with shape\n",
    "        #  [batch size, block length, 2]\n",
    "        # where the last dimension consists of the real and imaginary components\n",
    "        # The linear layers operate on the last dimension, and treat the inner dimensions as batch dimensions, i.e.,\n",
    "        # all the received symbols are independently processed.\n",
    "        nn_input = torch.stack([y.real, y.imag], dim=-1)\n",
    "        z = F.relu(self.dense_1(nn_input))\n",
    "        z = F.relu(self.dense_2(z))\n",
    "        z = self.dense_3(z) # [batch size, number of symbols per block, number of bits per symbol]\n",
    "        llr = z.reshape(y.shape[0], -1) # [batch size, number of bits per block]\n",
    "        return llr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6552c1a7",
   "metadata": {},
   "source": [
    "A custom PyTorch module is used as any other Sionna layer, and therefore integration to a Sionna-based communication is straightforward.\n",
    "\n",
    "The following model uses the neural demapper instead of the conventional demapper. It takes at initialization a parameter that indicates if the model is instantiated to be trained or evaluated. When instantiated to be trained, the loss function is returned. Otherwise, the transmitted bits and LLRs are returned."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "502066d5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:44.432578Z",
     "iopub.status.busy": "2026-08-06T15:53:44.432467Z",
     "iopub.status.idle": "2026-08-06T15:53:44.436772Z",
     "shell.execute_reply": "2026-08-06T15:53:44.436174Z"
    }
   },
   "outputs": [],
   "source": [
    "class End2EndSystem(nn.Module): # Inherits from PyTorch Module\n",
    "\n",
    "    def __init__(self, training):\n",
    "\n",
    "        super().__init__() # Must call the PyTorch module initializer\n",
    "\n",
    "        qam_constellation = sn.phy.mapping.Constellation(\"qam\", NUM_BITS_PER_SYMBOL)\n",
    "\n",
    "        # Trainable constellation points as nn.Parameter\n",
    "        self.points = nn.Parameter(torch.stack([qam_constellation.points.real.clone(),\n",
    "                                                qam_constellation.points.imag.clone()], dim=0))\n",
    "\n",
    "        self.constellation = sn.phy.mapping.Constellation(\"custom\",\n",
    "                                                    num_bits_per_symbol=NUM_BITS_PER_SYMBOL,\n",
    "                                                    points=torch.complex(self.points[0], self.points[1]),\n",
    "                                                    normalize=True,\n",
    "                                                    center=True)\n",
    "        self.mapper = sn.phy.mapping.Mapper(constellation=self.constellation)\n",
    "        self.demapper = NeuralDemapper() # Instantiate the NeuralDemapper custom module as any other\n",
    "        self.binary_source = sn.phy.mapping.BinarySource()\n",
    "        self.awgn_channel = sn.phy.channel.AWGN()\n",
    "        self._training_mode = training\n",
    "\n",
    "    def forward(self, batch_size, ebno_db):\n",
    "\n",
    "        # no channel coding used; we set coderate=1.0\n",
    "        no = sn.phy.utils.ebnodb2no(ebno_db,\n",
    "                                num_bits_per_symbol=NUM_BITS_PER_SYMBOL,\n",
    "                                coderate=1.0)\n",
    "        bits = self.binary_source([batch_size, 1200]) # Blocklength set to 1200 bits\n",
    "\n",
    "        # Assign points to constellation\n",
    "        self.mapper.constellation.points = torch.complex(self.points[0], self.points[1])\n",
    "\n",
    "        x = self.mapper(bits)\n",
    "        y = self.awgn_channel(x, no)\n",
    "        llr = self.demapper(y)  # Call the NeuralDemapper custom module as any other\n",
    "        if self._training_mode:\n",
    "            loss = F.binary_cross_entropy_with_logits(llr, bits.float())\n",
    "            return loss\n",
    "        else:\n",
    "            return bits, llr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af122bb3",
   "metadata": {},
   "source": [
    "When a model that includes a neural network is created, the neural network weights are randomly initialized typically leading to very poor performance.\n",
    "\n",
    "To see this, the following cell benchmarks the previously defined untrained model against a conventional baseline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6eda9275",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:44.438473Z",
     "iopub.status.busy": "2026-08-06T15:53:44.438363Z",
     "iopub.status.idle": "2026-08-06T15:53:45.640247Z",
     "shell.execute_reply": "2026-08-06T15:53:45.639490Z"
    }
   },
   "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 | 2.7044e-02 | 1.0000e+00 |        4154 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   10.526 | 2.0892e-02 | 1.0000e+00 |        3209 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   11.053 | 1.7057e-02 | 1.0000e+00 |        2620 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   11.579 | 1.2350e-02 | 1.0000e+00 |        1897 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   12.105 | 8.9062e-03 | 1.0000e+00 |        1368 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   12.632 | 6.8815e-03 | 1.0000e+00 |        1057 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   13.158 | 4.4727e-03 | 1.0000e+00 |         687 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   13.684 | 2.7604e-03 | 9.4531e-01 |         424 |      153600 |          121 |         128 |         0.0 |reached target block errors\n",
      "   14.211 | 1.8034e-03 | 9.2188e-01 |         277 |      153600 |          118 |         128 |         0.0 |reached target block errors\n",
      "   14.737 | 1.0449e-03 | 7.0312e-01 |         321 |      307200 |          180 |         256 |         0.0 |reached target block errors\n",
      "   15.263 | 5.7943e-04 | 4.7656e-01 |         178 |      307200 |          122 |         256 |         0.0 |reached target block errors\n",
      "   15.789 | 2.7778e-04 | 2.7865e-01 |         128 |      460800 |          107 |         384 |         0.0 |reached target block errors\n",
      "   16.316 | 1.2912e-04 | 1.3932e-01 |         119 |      921600 |          107 |         768 |         0.0 |reached target block errors\n",
      "   16.842 | 5.7509e-05 | 6.7057e-02 |         106 |     1843200 |          103 |        1536 |         0.0 |reached target block errors\n",
      "   17.368 | 2.7083e-05 | 3.1875e-02 |         104 |     3840000 |          102 |        3200 |         0.0 |reached target block errors\n",
      "   17.895 | 7.7974e-06 | 9.0843e-03 |         103 |    13209600 |          100 |       11008 |         0.1 |reached target block errors\n",
      "   18.421 | 2.4089e-06 | 2.8906e-03 |          37 |    15360000 |           37 |       12800 |         0.1 |reached max iterations\n",
      "   18.947 | 8.4635e-07 | 1.0156e-03 |          13 |    15360000 |           13 |       12800 |         0.1 |reached max iterations\n",
      "   19.474 | 6.5104e-08 | 7.8125e-05 |           1 |    15360000 |            1 |       12800 |         0.1 |reached max iterations\n",
      "     20.0 | 0.0000e+00 | 0.0000e+00 |           0 |    15360000 |            0 |       12800 |         0.1 |reached max iterations\n",
      "\n",
      "Simulation stopped as no error occurred @ EbNo = 20.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "     10.0 | 5.2380e-01 | 1.0000e+00 |       80455 |      153600 |          128 |         128 |         0.1 |reached target block errors\n",
      "   10.526 | 5.2522e-01 | 1.0000e+00 |       80674 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   11.053 | 5.2592e-01 | 1.0000e+00 |       80782 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   11.579 | 5.2693e-01 | 1.0000e+00 |       80937 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   12.105 | 5.2683e-01 | 1.0000e+00 |       80921 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   12.632 | 5.2392e-01 | 1.0000e+00 |       80474 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   13.158 | 5.2674e-01 | 1.0000e+00 |       80908 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   13.684 | 5.2599e-01 | 1.0000e+00 |       80792 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   14.211 | 5.2521e-01 | 1.0000e+00 |       80673 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   14.737 | 5.2607e-01 | 1.0000e+00 |       80804 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   15.263 | 5.2429e-01 | 1.0000e+00 |       80531 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   15.789 | 5.2418e-01 | 1.0000e+00 |       80514 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   16.316 | 5.2365e-01 | 1.0000e+00 |       80433 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   16.842 | 5.2637e-01 | 1.0000e+00 |       80851 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   17.368 | 5.2438e-01 | 1.0000e+00 |       80544 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   17.895 | 5.2335e-01 | 1.0000e+00 |       80386 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   18.421 | 5.2558e-01 | 1.0000e+00 |       80729 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   18.947 | 5.2402e-01 | 1.0000e+00 |       80489 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   19.474 | 5.2444e-01 | 1.0000e+00 |       80554 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "     20.0 | 5.2452e-01 | 1.0000e+00 |       80566 |      153600 |          128 |         128 |         0.0 |reached target block errors\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "EBN0_DB_MIN = 10.0\n",
    "EBN0_DB_MAX = 20.0\n",
    "\n",
    "\n",
    "###############################\n",
    "# Baseline\n",
    "###############################\n",
    "\n",
    "class Baseline(nn.Module): # Inherits from PyTorch Module\n",
    "\n",
    "    def __init__(self):\n",
    "\n",
    "        super().__init__() # Must call the PyTorch module initializer\n",
    "\n",
    "        self.constellation = sn.phy.mapping.Constellation(\"qam\", NUM_BITS_PER_SYMBOL)\n",
    "        self.mapper = sn.phy.mapping.Mapper(constellation=self.constellation)\n",
    "        self.demapper = sn.phy.mapping.Demapper(\"app\", constellation=self.constellation)\n",
    "        self.binary_source = sn.phy.mapping.BinarySource()\n",
    "        self.awgn_channel = sn.phy.channel.AWGN()\n",
    "\n",
    "    def forward(self, batch_size, ebno_db):\n",
    "\n",
    "        # no channel coding used; we set coderate=1.0\n",
    "        no = sn.phy.utils.ebnodb2no(ebno_db,\n",
    "                                num_bits_per_symbol=NUM_BITS_PER_SYMBOL,\n",
    "                                coderate=1.0)\n",
    "        bits = self.binary_source([batch_size, 1200]) # Blocklength set to 1200 bits\n",
    "        x = self.mapper(bits)\n",
    "        y = self.awgn_channel(x, no)\n",
    "        llr = self.demapper(y, no)\n",
    "        return bits, llr\n",
    "\n",
    "###############################\n",
    "# Benchmarking\n",
    "###############################\n",
    "\n",
    "baseline = Baseline()\n",
    "model = End2EndSystem(False).to(sn.phy.config.device)  # Move model to GPU/CPU\n",
    "ber_plots = sn.phy.utils.PlotBER(\"Neural Demapper\")\n",
    "ber_plots.simulate(baseline,\n",
    "                  ebno_dbs=np.linspace(EBN0_DB_MIN, EBN0_DB_MAX, 20),\n",
    "                  batch_size=BATCH_SIZE,\n",
    "                  num_target_block_errors=100, # simulate until 100 block errors occurred\n",
    "                  legend=\"Baseline\",\n",
    "                  soft_estimates=True,\n",
    "                  max_mc_iter=100, # run 100 Monte-Carlo simulations (each with batch_size samples)\n",
    "                  show_fig=False);\n",
    "ber_plots.simulate(model,\n",
    "                  ebno_dbs=np.linspace(EBN0_DB_MIN, EBN0_DB_MAX, 20),\n",
    "                  batch_size=BATCH_SIZE,\n",
    "                  num_target_block_errors=100, # simulate until 100 block errors occurred\n",
    "                  legend=\"Untrained model\",\n",
    "                  soft_estimates=True,\n",
    "                  max_mc_iter=100, # run 100 Monte-Carlo simulations (each with batch_size samples)\n",
    "                  show_fig=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4982feda-3b93-46dc-a936-bd225d7260dd",
   "metadata": {},
   "source": [
    "## Setting up Training Loops <a class=\"anchor\" id=\"Setting-up-Training-Loops\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "257d7e00-7341-4542-bc75-d9a612fba091",
   "metadata": {},
   "source": [
    "Training of end-to-end communication systems consists in iterating over SGD steps.\n",
    "\n",
    "The next cell implements a training loop of `NUM_TRAINING_ITERATIONS` iterations.\n",
    "The training SNR is set to $E_b/N_0 = 15$ dB.\n",
    "\n",
    "At each iteration:\n",
    "- A forward pass through the end-to-end system is performed within a gradient tape\n",
    "- The gradients are computed using the gradient tape, and applied using the Adam optimizer\n",
    "- The estimated loss is periodically printed to follow the progress of training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c53960db-28ee-4f33-8840-7b1373348162",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:53:45.642466Z",
     "iopub.status.busy": "2026-08-06T15:53:45.642340Z",
     "iopub.status.idle": "2026-08-06T15:54:19.221738Z",
     "shell.execute_reply": "2026-08-06T15:54:19.220463Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9900/10000  Loss: 2.02E-03\r"
     ]
    }
   ],
   "source": [
    "# Number of iterations used for training\n",
    "NUM_TRAINING_ITERATIONS = 10000\n",
    "\n",
    "# Instantiating the end-to-end model for training\n",
    "model_train = End2EndSystem(training=True).to(sn.phy.config.device)\n",
    "\n",
    "# Adam optimizer (SGD variant)\n",
    "optimizer = torch.optim.Adam(model_train.parameters())\n",
    "\n",
    "# Training loop\n",
    "for i in range(NUM_TRAINING_ITERATIONS):\n",
    "    # Zero gradients from previous iteration\n",
    "    optimizer.zero_grad()\n",
    "    # Forward pass\n",
    "    loss = model_train(BATCH_SIZE, 15.0) # The model returns the loss\n",
    "    # Backward pass to compute gradients\n",
    "    loss.backward()\n",
    "    # Apply gradients to update parameters\n",
    "    optimizer.step()\n",
    "    # Print progress\n",
    "    if i % 100 == 0:\n",
    "        print(f\"{i}/{NUM_TRAINING_ITERATIONS}  Loss: {loss.item():.2E}\", end=\"\\r\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "185884d2",
   "metadata": {},
   "source": [
    "The weights of the trained model are saved using PyTorch's `torch.save()` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c1eaf2c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:54:19.224184Z",
     "iopub.status.busy": "2026-08-06T15:54:19.223956Z",
     "iopub.status.idle": "2026-08-06T15:54:19.231134Z",
     "shell.execute_reply": "2026-08-06T15:54:19.230119Z"
    }
   },
   "outputs": [],
   "source": [
    "# Save the weights in a file\n",
    "torch.save(model_train.state_dict(), 'weights-neural-demapper.pt')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bc9252a-47ee-4c2b-9224-194c90d7f4f2",
   "metadata": {},
   "source": [
    "Finally, we evaluate the trained model and benchmark it against the previously introduced baseline.\n",
    "\n",
    "We first instantiate the model for evaluation and load the saved weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6a0e6e6b-3650-4524-9c83-46c715493e3f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:54:19.233585Z",
     "iopub.status.busy": "2026-08-06T15:54:19.233374Z",
     "iopub.status.idle": "2026-08-06T15:54:19.243470Z",
     "shell.execute_reply": "2026-08-06T15:54:19.242585Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Instantiating the end-to-end model for evaluation\n",
    "model = End2EndSystem(training=False).to(sn.phy.config.device)\n",
    "# Load the trained weights\n",
    "model.load_state_dict(torch.load('weights-neural-demapper.pt', weights_only=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61e6372e-d5a4-40ae-90fb-2bb1694dd533",
   "metadata": {},
   "source": [
    "The trained model is then evaluated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fc0e47a5-7d61-4e8b-b077-8fc63a33057f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-06T15:54:19.245992Z",
     "iopub.status.busy": "2026-08-06T15:54:19.245765Z",
     "iopub.status.idle": "2026-08-06T15:54:20.375368Z",
     "shell.execute_reply": "2026-08-06T15:54:20.374375Z"
    }
   },
   "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 | 2.5781e-02 | 1.0000e+00 |        3960 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   10.526 | 2.0052e-02 | 1.0000e+00 |        3080 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   11.053 | 1.6204e-02 | 1.0000e+00 |        2489 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   11.579 | 1.2161e-02 | 1.0000e+00 |        1868 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   12.105 | 8.1771e-03 | 1.0000e+00 |        1256 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   12.632 | 5.7161e-03 | 1.0000e+00 |         878 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   13.158 | 4.1732e-03 | 1.0000e+00 |         641 |      153600 |          128 |         128 |         0.0 |reached target block errors\n",
      "   13.684 | 2.6693e-03 | 9.4531e-01 |         410 |      153600 |          121 |         128 |         0.0 |reached target block errors\n",
      "   14.211 | 1.8034e-03 | 8.9844e-01 |         277 |      153600 |          115 |         128 |         0.0 |reached target block errors\n",
      "   14.737 | 1.0579e-03 | 7.1875e-01 |         325 |      307200 |          184 |         256 |         0.0 |reached target block errors\n",
      "   15.263 | 6.8034e-04 | 5.5859e-01 |         209 |      307200 |          143 |         256 |         0.0 |reached target block errors\n",
      "   15.789 | 3.1250e-04 | 2.9948e-01 |         144 |      460800 |          115 |         384 |         0.0 |reached target block errors\n",
      "   16.316 | 1.4193e-04 | 1.6406e-01 |         109 |      768000 |          105 |         640 |         0.0 |reached target block errors\n",
      "   16.842 | 7.1615e-05 | 7.9687e-02 |         110 |     1536000 |          102 |        1280 |         0.0 |reached target block errors\n",
      "   17.368 | 2.3251e-05 | 2.7902e-02 |         100 |     4300800 |          100 |        3584 |         0.0 |reached target block errors\n",
      "   17.895 | 8.1380e-06 | 9.7656e-03 |         100 |    12288000 |          100 |       10240 |         0.1 |reached target block errors\n",
      "   18.421 | 2.4089e-06 | 2.8906e-03 |          37 |    15360000 |           37 |       12800 |         0.1 |reached max iterations\n",
      "   18.947 | 8.4635e-07 | 1.0156e-03 |          13 |    15360000 |           13 |       12800 |         0.1 |reached max iterations\n",
      "   19.474 | 2.6042e-07 | 3.1250e-04 |           4 |    15360000 |            4 |       12800 |         0.1 |reached max iterations\n",
      "     20.0 | 6.5104e-08 | 7.8125e-05 |           1 |    15360000 |            1 |       12800 |         0.1 |reached max iterations\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Computing and plotting BER\n",
    "ber_plots.simulate(model,\n",
    "                  ebno_dbs=np.linspace(EBN0_DB_MIN, EBN0_DB_MAX, 20),\n",
    "                  batch_size=BATCH_SIZE,\n",
    "                  num_target_block_errors=100,\n",
    "                  legend=\"Trained model\",\n",
    "                  soft_estimates=True,\n",
    "                  max_mc_iter=100,\n",
    "                  show_fig=True);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.12"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}