From 92e109397c3be83fd96a313acafb331802c2b22d Mon Sep 17 00:00:00 2001
From: Eric Kooistra <kooistra@astron.nl>
Date: Thu, 14 Nov 2024 11:59:43 +0100
Subject: [PATCH] Compare output with delayed input.

---
 .../lofar2/model/pfb_os/multirate_mixer.ipynb | 270 ++++++++++++++----
 applications/lofar2/model/rtdsp/multirate.py  | 120 ++++++--
 2 files changed, 311 insertions(+), 79 deletions(-)

diff --git a/applications/lofar2/model/pfb_os/multirate_mixer.ipynb b/applications/lofar2/model/pfb_os/multirate_mixer.ipynb
index 1b47f011fe..6032c34f36 100644
--- a/applications/lofar2/model/pfb_os/multirate_mixer.ipynb
+++ b/applications/lofar2/model/pfb_os/multirate_mixer.ipynb
@@ -11,16 +11,20 @@
     "\n",
     "Purpose:\n",
     "* Practise DSP [1].\n",
-    "* Use multirate processing to implement a mixer \n",
+    "* Use multirate processing to implement a single channel mixer\n",
+    "* Extend single channel mixer to DFT filterbank\n",
+    "\n",
+    "Use full rate model of single channel down converter and up converter as expected exact reference result for the efficient polyphase implementation.\n",
     "\n",
     "References:\n",
     "1. dsp_study_erko, summary of DSP books\n",
-    "2. chapter 6 downconverter, 7 upconverter, 9 filterbank in [HARRIS]"
+    "2. chapter 7 in [CROCHIERE]\n",
+    "3. chapter 6 downconverter, 7 upconverter, 9 filterbank in [HARRIS]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 114,
    "id": "8043fa7b",
    "metadata": {},
    "outputs": [],
@@ -33,10 +37,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 115,
    "id": "fc530dbc",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
    "source": [
     "# Auto reload module when it is changed\n",
     "%load_ext autoreload\n",
@@ -50,13 +63,13 @@
     "    sys.path.insert(0, module_path)\n",
     "\n",
     "# Import rtdsp\n",
-    "from rtdsp.utilities import ceil_div, verify_result, is_integer_value, is_symmetrical, pow_db\n",
+    "from rtdsp.utilities import ceil_div, verify_result, is_integer_value, is_symmetrical, pow_db, snr_db\n",
     "from rtdsp.firfilter import filterbank_frequency_response\n",
     "from rtdsp.fourier import dtft\n",
     "from rtdsp.multirate import down, up, unit_circle_loops_phasor_arr, \\\n",
     "                            maximal_downsample_bpf, non_maximal_downsample_bpf, \\\n",
     "                            maximal_upsample_bpf, non_maximal_upsample_bpf, \\\n",
-    "                            analysis_dft_filterbank\n",
+    "                            analysis_dft_filterbank, synthesis_dft_filterbank\n",
     "from rtdsp.plotting import plot_power_spectrum, plot_magnitude_spectrum, plot_phase_spectrum"
    ]
   },
@@ -70,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 116,
    "id": "5b37a1dc",
    "metadata": {},
    "outputs": [
@@ -78,6 +91,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Ntaps        = 8\n",
+      "Ndft         = 16\n",
+      "Ncoefs       = 128\n",
+      "\n",
       "wgSub        = 1.0\n",
       "wgPhase      = 30.0\n",
       "wgModulation = 0\n",
@@ -97,11 +114,15 @@
     "Ndft = 16  # DFT size\n",
     "Ncoefs = Ndft * Ntaps\n",
     "#Ncoefs = Ncoefs - 1   # try odd length\n",
+    "print('Ntaps        =', Ntaps)\n",
+    "print('Ndft         =', Ndft)\n",
+    "print('Ncoefs       =', Ncoefs)\n",
     "\n",
     "# Waveform generator\n",
-    "wgSub = 1.0 # in range(Nsub)\n",
+    "wgSub = 1.0  # in range(Nsub)\n",
     "wgPhase = 30.0  # in degrees\n",
     "wgModulation = 0  # for amplitude modulation (AM) frequency fsub / wgModulation, use 0 for no AM\n",
+    "print()\n",
     "print('wgSub        =', wgSub)\n",
     "print('wgPhase      =', wgPhase)\n",
     "print('wgModulation =', wgModulation)\n",
@@ -139,7 +160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 117,
    "id": "e5680c7b",
    "metadata": {},
    "outputs": [],
@@ -151,7 +172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 118,
    "id": "74ca764f",
    "metadata": {},
    "outputs": [
@@ -180,7 +201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 119,
    "id": "786af296",
    "metadata": {},
    "outputs": [],
@@ -211,7 +232,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 120,
    "id": "1bb76ada",
    "metadata": {},
    "outputs": [
@@ -243,7 +264,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 121,
    "id": "6ebc94aa",
    "metadata": {},
    "outputs": [
@@ -274,7 +295,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 122,
    "id": "3abeee86",
    "metadata": {},
    "outputs": [
@@ -330,7 +351,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 123,
    "id": "372445f4",
    "metadata": {},
    "outputs": [
@@ -362,7 +383,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 124,
    "id": "e74340e4",
    "metadata": {},
    "outputs": [],
@@ -381,7 +402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 125,
    "id": "bd2add56",
    "metadata": {},
    "outputs": [],
@@ -406,17 +427,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 126,
    "id": "7106ad3f",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f14108ec160>]"
+       "[<matplotlib.lines.Line2D at 0x7f21a4cc40a0>]"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 126,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -456,7 +477,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 127,
    "id": "da53b25e",
    "metadata": {},
    "outputs": [],
@@ -468,17 +489,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 128,
    "id": "9acf0ec2",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7f1410acb760>"
+       "<matplotlib.legend.Legend at 0x7f21a4a11c10>"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 128,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -524,7 +545,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 129,
    "id": "b8036250",
    "metadata": {},
    "outputs": [
@@ -569,7 +590,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 130,
    "id": "0663df66",
    "metadata": {},
    "outputs": [],
@@ -585,7 +606,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 131,
    "id": "3a039428",
    "metadata": {},
    "outputs": [
@@ -629,7 +650,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 132,
    "id": "327236c2",
    "metadata": {},
    "outputs": [
@@ -666,7 +687,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 133,
    "id": "aefa8615",
    "metadata": {},
    "outputs": [
@@ -690,10 +711,10 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f140afb4d60>]"
+       "[<matplotlib.lines.Line2D at 0x7f21a48d5b50>]"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 133,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -730,7 +751,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 134,
    "id": "f814c9b9",
    "metadata": {},
    "outputs": [
@@ -772,7 +793,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 135,
    "id": "dd7a9503",
    "metadata": {},
    "outputs": [],
@@ -809,7 +830,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 136,
    "id": "3cf6aa74",
    "metadata": {},
    "outputs": [],
@@ -820,7 +841,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 137,
+   "id": "43cfbcbc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Back to back, down converter up converter, reference output yrUpLpfLo\n",
+    "# With (inefficient) processing at full rate, because down sampling is done after LO and LPF and\n",
+    "# upsampling is done before LPF and LOp. \n",
+    "#   yDown         ycUp        ycUpLpf\n",
+    "# y[mD, k] --> U ------> LPF --------> LOp --> ycUpLpfLo\n",
+    "ycUp = up(yDown, Nup)  # insert Nup - 1 zeros\n",
+    "ycUpLpf = Nup * signal.lfilter(hPrototype, [1.0], ycUp)  # interpolate by Nup\n",
+    "ycUpLpfLo = ycUpLpf * LOp  # upconvert to positive bin kLo\n",
+    "yrUpLpfLo = ycUpLpfLo.real * nofSsb  # = ycUpLpfLo + np.conj(ycUpLpfLo), add negative bin -kLo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 138,
    "id": "03da0b30",
    "metadata": {},
    "outputs": [
@@ -841,7 +880,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 139,
    "id": "a5c60be5",
    "metadata": {},
    "outputs": [
@@ -854,7 +893,7 @@
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
        "<Figure size 700x400 with 1 Axes>"
       ]
@@ -864,18 +903,12 @@
     }
    ],
    "source": [
-    "#   yDown         ycUp        ycUpLpf\n",
-    "# y[mD, k] --> U ------> LPF --------> LOp --> ycUpLpfLo\n",
-    "ycUp = up(yDown, Nup)  # insert Nup - 1 zeros\n",
-    "ycUpLpf = Nup * signal.lfilter(hPrototype, [1.0], ycUp)  # interpolate by Nup\n",
-    "ycUpLpfLo = ycUpLpf * LOp  # upconvert to positive bin kLo\n",
-    "yrUpLpfLo = ycUpLpfLo.real * nofSsb  # = ycUpLpfLo + np.conj(ycUpLpfLo), add negative bin -kLo\n",
-    "\n",
     "# Plot original real xData recovered yrUpLpfLo\n",
     "# TODO: Why is the intGroupDelay only correct for integer wgSub ???\n",
-    "plt.plot(xData[0:len(yrUpLpfLo) - intGroupDelay], 'r.-')\n",
+    "xDelayed = xData[0:len(yrUpLpfLo) - intGroupDelay]\n",
+    "plt.plot(xDelayed, 'r.-')\n",
     "plt.plot(yrUpLpfLo[intGroupDelay:], 'b.-')\n",
-    "plt.xlim([100, 150])\n",
+    "plt.xlim([100, 200])\n",
     "\n",
     "if not wgModulation:\n",
     "    yrAmpl = np.sqrt(np.mean(np.abs(yrUpLpfLo[Ncoefs:]**2)) * nofSsb)\n",
@@ -896,7 +929,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 140,
    "id": "7049249e",
    "metadata": {},
    "outputs": [
@@ -930,7 +963,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 141,
    "id": "64cc34f3",
    "metadata": {},
    "outputs": [],
@@ -946,7 +979,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 142,
    "id": "71a91beb",
    "metadata": {},
    "outputs": [
@@ -995,7 +1028,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 143,
    "id": "a3aae48a",
    "metadata": {},
    "outputs": [
@@ -1032,7 +1065,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 144,
    "id": "3c2c8ec5",
    "metadata": {},
    "outputs": [
@@ -1046,7 +1079,7 @@
    ],
    "source": [
     "ycLoBpfUp = non_maximal_upsample_bpf(yDown, Nup, kLo, Ndft, hPrototype)\n",
-    "if ycLoBpfUp:\n",
+    "if ycLoBpfUp is not None:\n",
     "    yrLoBpfUp = ycLoBpfUp.real * nofSsb  # add negative bin -kLo to make real\n",
     "\n",
     "    result = np.all(np.isclose(yrUpLpfLo, yrLoBpfUp))\n",
@@ -1062,7 +1095,9 @@
    "id": "ee9daf9f",
    "metadata": {},
    "source": [
-    "# 5 Compare with DFT filterbank"
+    "# 5 Compare with DFT filterbank\n",
+    "\n",
+    "Can use 'cw' or 'ccw' independently for analysis and synthesis PFB, because with fold() the IDFT can be expressed as a DFT and vice versa. However to have back to back DFT - IDFT in pipeline, use analysis 'cw' and synthesis 'ccw' [CROCHIERE 7.2.3]."
    ]
   },
   {
@@ -1075,7 +1110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 145,
    "id": "b0f997d3",
    "metadata": {},
    "outputs": [
@@ -1091,13 +1126,14 @@
       "  . Ndown      = 12\n",
       "  . Ndft       = 16\n",
       "  . commutator = cw\n",
-      "\n"
+      "\n",
+      "PASSED\n"
      ]
     }
    ],
    "source": [
-    "Yc = analysis_dft_filterbank(xData, Ndown, Ndft, hPrototype, commutator='cw', verbosity=1)\n",
-    "yDownBin = Yc[kLo]\n",
+    "Ac = analysis_dft_filterbank(xData, Ndown, Ndft, hPrototype, commutator='cw')\n",
+    "yDownBin = Ac[kLo]\n",
     "\n",
     "result = np.all(np.isclose(yDown, yDownBin))\n",
     "if not result:\n",
@@ -1105,8 +1141,7 @@
     "    plt.plot(m_sub, yDown.imag, 'g.--')\n",
     "    plt.plot(m_sub, yDownBin.real, 'r-')\n",
     "    plt.plot(m_sub, yDownBin.imag, 'r--')\n",
-    "\n",
-    "# verify_result(result)"
+    "verify_result(result)"
    ]
   },
   {
@@ -1119,9 +1154,122 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 146,
    "id": "47d5bf5b",
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "> synthesis_dft_filterbank():\n",
+      "  . Nblocks    = 32\n",
+      "  . Ros        = 1.3333333333333333\n",
+      "  . Nup        = 12\n",
+      "  . Ndft       = 16\n",
+      "  . commutator = ccw\n",
+      "\n",
+      "PASSED\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Keep bin kLo and force all other bins to zero, to have exact comparison with full rate\n",
+    "# single channel reference.\n",
+    "Yc = Ac * 0\n",
+    "Yc[kLo] = yDownBin\n",
+    "Yc[Ndft - kLo] = np.conjugate(yDownBin)\n",
+    "\n",
+    "# Single bin from PFB\n",
+    "yr = synthesis_dft_filterbank(Yc, Nup, Ndft, hPrototype, commutator='ccw')\n",
+    "yr = yr[0 : len(yrUpLpfLo)]\n",
+    "\n",
+    "result = np.all(np.isclose(yrUpLpfLo, yr))\n",
+    "if not result:\n",
+    "    plt.plot(n_sub, yrUpLpfLo, 'g.-')\n",
+    "    plt.plot(n_sub, yr, 'r-')\n",
+    "verify_result(result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "id": "4818ad5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "> synthesis_dft_filterbank():\n",
+      "  . Nblocks    = 32\n",
+      "  . Ros        = 1.3333333333333333\n",
+      "  . Nup        = 12\n",
+      "  . Ndft       = 16\n",
+      "  . commutator = ccw\n",
+      "\n",
+      "SNR_yr = 85.77 [dB], single channel\n",
+      "SNR_sr = 60.15 [dB], all channels\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f21a48b3df0>]"
+      ]
+     },
+     "execution_count": 148,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 700x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compare output with input\n",
+    "# All bins from PFB\n",
+    "sr = synthesis_dft_filterbank(Ac, Nup, Ndft, hPrototype, commutator='ccw')\n",
+    "sr = sr[0 : len(yrUpLpfLo)]\n",
+    "\n",
+    "# Output time aligned with input\n",
+    "x_yr = yr[intGroupDelay:]\n",
+    "x_sr = sr[intGroupDelay:]\n",
+    "\n",
+    "offset = Ncoefs\n",
+    "SNR_yr = snr_db(xDelayed, xDelayed[offset:] - x_yr[offset:])\n",
+    "SNR_sr = snr_db(xDelayed, xDelayed[offset:] - x_sr[offset:])\n",
+    "\n",
+    "print('SNR_yr = %.2f [dB], single bin' % SNR_yr)\n",
+    "print('SNR_sr = %.2f [dB], all bins' % SNR_sr)\n",
+    "\n",
+    "# Plot original real xData recovered yr and sr\n",
+    "plt.plot(xDelayed, 'r.-')\n",
+    "plt.plot(x_yr, 'b.-')\n",
+    "plt.plot(x_sr, 'g.-')\n",
+    "#plt.xlim([offset, len(xDelayed)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a16ef270",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "314e3e71",
+   "metadata": {},
    "outputs": [],
    "source": []
   }
diff --git a/applications/lofar2/model/rtdsp/multirate.py b/applications/lofar2/model/rtdsp/multirate.py
index 7c3d14862d..9fdb962103 100644
--- a/applications/lofar2/model/rtdsp/multirate.py
+++ b/applications/lofar2/model/rtdsp/multirate.py
@@ -212,8 +212,11 @@ class PolyPhaseFirFilterStructure:
     def reset_poly_delays(self):
         self.polyDelays = zeros((self.Nphases, self.Ntaps), self.cmplx)
 
-    def map_to_delay_line(self):
-        delayLine = self.polyDelays.T.reshape(-1)
+    def map_to_delay_line(self, polyDelays=None):
+        if polyDelays is None:
+            delayLine = self.polyDelays.T.reshape(-1)
+        else:
+            delayLine = polyDelays.T.reshape(-1)
         return delayLine
 
     def map_to_poly_delays(self, delayLine):
@@ -249,6 +252,23 @@ class PolyPhaseFirFilterStructure:
             self.polyDelays = np.roll(self.polyDelays, 1, axis=1)
             self.polyDelays[:, 0] = xData
 
+    def load_in_data(self, inData, flipped):
+        """Load block of data into each tap of the polyDelays structure.
+
+        Length L of inData is L = Nphases, so load the data directly at
+        each column of polyDelays.
+
+        Input:
+        . inData: Block of input samples with index as time index n in
+            inData[n], so oldest sample at index 0 and newest sample at
+            index -1.
+        . flipped: False then inData order is inData[n] and still needs to be
+            flipped. If True then the inData is already flipped.
+        """
+        xData = inData if flipped else np.flip(inData)
+        for tap in range(self.Ntaps):
+            self.polyDelays[:, tap] = xData
+
     def filter_block(self, inData, flipped):
         """Filter block of inData per polyphase.
 
@@ -830,11 +850,9 @@ def non_maximal_downsample_bpf(x, Ndown, k, Ndft, coefs, verbosity=1):
     """
     Ros = Ndft / Ndown
 
-    # Prepend x with Ndown - 1 zeros, and represent x in Nblocks of Ndown
-    # samples
+    # Prepend x with Ndown - 1 zeros, and represent x in Nblocks of Ndown samples
     Nzeros = Ndown - 1
     xBlocks, Nx, Nblocks = polyphase_data_for_downsampling_whole_x(x, Ndown, Nzeros)
-    # print(xBlocks[:, 0])
 
     # Prepare output
     yc = np.zeros(Nblocks, dtype='cfloat')
@@ -960,9 +978,10 @@ def non_maximal_upsample_bpf(xBase, Nup, k, Ndft, coefs, verbosity=1):
 
 
 def analysis_dft_filterbank(x, Ndown, Ndft, coefs, commutator, verbosity=1):
-    """DFT filterbank with Ros = Ndft / Ndown.
+    """Analysis DFT filterbank with Ros = Ndft / Ndown.
 
-    Implements WOLA structure for DFT filterbank [CROCHIERE 7.2.5]. Key steps:
+    Implements WOLA structure for DFT filterbank [CROCHIERE Fig 7.19]. Key
+    steps:
 
     - Signal x has time index n. Mixer local oscillator (LO) and LPF and
       downsampler M, yields the short-time spectrum of signal x at time n = mM,
@@ -971,9 +990,9 @@ def analysis_dft_filterbank(x, Ndown, Ndft, coefs, commutator, verbosity=1):
     - Change from fixed signal time frame n and sliding filter, to sliding time
       frame r with fixed filter. This yields factor W_K^(kmM) [CROCHIERE Eq
       7.69], with K = Ndft.
-    - Assume filter h length is Ncoef = Ntaps * K, for K frequency bins. The
+    - Assume filter h length is Ncoefs = Ntaps * K, for K frequency bins. The
       h[-r] weights the signal at n = nM, so the DFT of the weighted signal has
-      Ncoef bins k', but for the filterbank only bins k' = k Ntaps are needed.
+      Ncoefs bins k', but for the filterbank only bins k' = k Ntaps are needed.
       This pruned DFT can be calculated by stacking the blocks of K samples of
       the weighted signal and then calculating the K point DFT [CROCHIERE Eq
       7.73, Fig 7.19, BUNTON]. The stacking sum is like polyphase FIR with K
@@ -981,12 +1000,12 @@ def analysis_dft_filterbank(x, Ndown, Ndft, coefs, commutator, verbosity=1):
     - The time (m) and bin (k) dependend phase shift W_K^(kmM) =
       exp(-j 2pi k m M / K) of the DFT output is equivalent to a circular time
       shift by l = (m M) % K samples of the DFT input. Circular time shift DFT
-      theorem:
+      theorem [CROCHIERE Fig 7.21]:
         x[n] <= DFT => X(k), then
         x[(n - l) % K] <= DFT => X(k) exp(-j 2pi k l / K)
     - For counter clockwise commutator use Ndft * IDFT(pfsData).
       For clockwise commutator use DFT(fold(pfsData)), because
-      DFT(x) = Ndft * IDFT(fold(x)).
+      IDFT(x) = 1/Ndft * DFT(fold(x)).
 
     Input:
     . x: Input signal x[n]
@@ -1019,21 +1038,18 @@ def analysis_dft_filterbank(x, Ndown, Ndft, coefs, commutator, verbosity=1):
         inData = xBlocks[:, b]
         pfsData = pfs.filter_block(inData, flipped=True)
 
-        # Default with 'ccw' keep the pfsData to apply IDFT
-        if commutator == 'cw':
-            # For 'cw' fold (= circular flip) the pfsData to apply the DFT
-            pfsData = fold(pfsData)
-
         # Apply time (m) and bin (k) dependend phase shift W_K^(kmM) by circular
         # time shift of DFT input
         tShift = (b * Ndown) % Ndft
+        pfsShifted = np.roll(pfsData, -tShift)
 
         # For 'ccw' apply IDFT, for 'cw' apply DFT
         if commutator == 'cw':  # DFT
-            pfsShifted = np.roll(pfsData, tShift)
+            # For 'cw' fold the pfsData to apply the DFT
+            pfsShifted = fold(pfsShifted)
             Yc[:, b] = np.fft.fft(pfsShifted)
         else:  # 'ccw', IDFT
-            pfsShifted = np.roll(pfsData, -tShift)
+            # With 'ccw' keep the pfsData to apply IDFT
             Yc[:, b] = np.fft.ifft(pfsShifted) * Ndft
 
     if verbosity:
@@ -1047,3 +1063,71 @@ def analysis_dft_filterbank(x, Ndown, Ndft, coefs, commutator, verbosity=1):
         print('  . commutator =', commutator)
         print('')
     return Yc
+
+
+def synthesis_dft_filterbank(Xbase, Nup, Ndft, coefs, commutator, verbosity=1):
+    """Synthesis DFT filterbank with Ros = Ndft / Nup.
+
+    Implements WOLA structure for DFT filterbank [CROCHIERE Fig 7.20]. Key
+    steps:
+
+    - Signal Xbase has time index m and Ndft values.
+
+    Input:
+    . Xbase: Complex baseband signals for Ndft bins, and Nblocks in time m.
+    . Nup: upsample factor and output block size
+    . Ndft: DFT size, number of polyphases in PFS FIR filter
+    . coefs: prototype LPF FIR filter coefficients for anti aliasing and
+      interpolating BPF
+    . commutator: 'ccw' to use DFT or 'cw' to use IDFT
+    - verbosity: when > 0 print() status, else no print()
+    Return:
+    . y: Upsampled and upconverted output signal y[n].
+    """
+    Ros = Ndft / Nup
+
+    # Xbase has Ndft rows and Nblocks columns
+    Nblocks = np.size(Xbase, axis=1)
+
+    # PFS with Ndft polyphases
+    pfs = PolyPhaseFirFilterStructure(Ndft, coefs)
+
+    # Prepare output
+    Noutput = Nup * Nblocks + pfs.Ncoefs
+    y = np.zeros(Noutput, dtype='float')
+
+    # Oversampling DFT filterbank
+    for b in range(Nblocks):
+        # For 'ccw' apply DFT, for 'cw' apply IDFT
+        if commutator == 'cw':  # DFT
+            # For 'cw' fold the Xbase to apply the DFT
+            xTime = np.real(np.fft.fft(fold(Xbase[:, b])))
+        else:  # 'ccw', IDFT
+            # With 'ccw' keep the Xbase to apply IDFT
+            xTime = Ndft * np.real(np.fft.ifft(Xbase[:, b]))
+
+        # Apply time (m) and bin (k) dependend phase shift W_K^(kmM) by circular
+        # time shift of DFT output
+        tShift = (b * Nup) % Ndft
+        xShifted = np.roll(xTime, -tShift)
+
+        # Load xTime at each tap in polyDelays
+        pfs.load_in_data(xShifted, flipped=True)
+
+        # Apply FIR coefs per delay element
+        zPoly = Nup * pfs.polyDelays * pfs.polyCoefs
+        zData = pfs.map_to_delay_line(zPoly)
+
+        # Overlap add weigthed input to the output
+        tRange = np.arange(pfs.Ncoefs) + b * Nup
+        y[tRange] += zData
+
+    if verbosity:
+        print('> synthesis_dft_filterbank():')
+        print('  . Nblocks    =', str(Nblocks))
+        print('  . Ros        =', str(Ros))
+        print('  . Nup        =', str(Nup))
+        print('  . Ndft       =', str(Ndft))
+        print('  . commutator =', commutator)
+        print('')
+    return y
-- 
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