Yeah, forgot the patch. On Thu, Jul 12, 2012 at 01:45:53PM +0200, Martin Braun (CEL) wrote: > Hi Tom/Johnathan, > > can you please add this example to gr-digital. It's a classic BER/SNR > simulation *not* written in GRC; something I think is missing in the > examples. > > MB > > -- > Karlsruhe Institute of Technology (KIT) > Communications Engineering Lab (CEL) > > Dipl.-Ing. Martin Braun > Research Associate > > Kaiserstraße 12 > Building 05.01 > 76131 Karlsruhe > > Phone: +49 721 608-43790 > Fax: +49 721 608-46071 > www.cel.kit.edu > > KIT -- University of the State of Baden-Württemberg and > National Laboratory of the Helmholtz Association
> _______________________________________________ > Patch-gnuradio mailing list > Patch-gnuradio@gnu.org > https://lists.gnu.org/mailman/listinfo/patch-gnuradio -- Karlsruhe Institute of Technology (KIT) Communications Engineering Lab (CEL) Dipl.-Ing. Martin Braun Research Associate Kaiserstraße 12 Building 05.01 76131 Karlsruhe Phone: +49 721 608-43790 Fax: +49 721 608-46071 www.cel.kit.edu KIT -- University of the State of Baden-Württemberg and National Laboratory of the Helmholtz Association
From 215a4ec6b7aa7805ba985cf380bfcd5c1d826f48 Mon Sep 17 00:00:00 2001
From: Martin Braun <martin.br...@kit.edu>
Date: Thu, 12 Jul 2012 13:43:04 +0200
Subject: [PATCH] digital: added example to sim BER in AWGN and show together
w/ theoretical values
---
gr-digital/examples/berawgn.py | 104 ++++++++++++++++++++++++++++++++++++++++
1 file changed, 104 insertions(+)
create mode 100755 gr-digital/examples/berawgn.py
diff --git a/gr-digital/examples/berawgn.py b/gr-digital/examples/berawgn.py
new file mode 100755
index 0000000..d58dfba
--- /dev/null
+++ b/gr-digital/examples/berawgn.py
@@ -0,0 +1,104 @@
+#!/usr/bin/env python
+"""
+BER simulation for QPSK signals, compare to theoretical values.
+Change the N_BITS value to simulate more bits per Eb/N0 value,
+thus allowing to check for lower BER values.
+
+Lower values will work faster, higher values will use a lot of RAM.
+Also, this app isn't highly optimized--the flow graph is completely
+reinstantiated for every Eb/N0 value.
+Of course, expect the maximum value for BER to be one order of
+magnitude below what you chose for N_BITS.
+"""
+
+
+import math
+import numpy
+from scipy.special import erfc
+import pylab
+from gnuradio import gr, digital
+
+# Best to choose powers of 10
+N_BITS = 1e7
+RAND_SEED = 42
+
+def berawgn(EbN0):
+ """ Calculates theoretical bit error rate in AWGN (for BPSK and given Eb/N0) """
+ return 0.5 * erfc(math.sqrt(10**(float(EbN0)/10)))
+
+class BitErrors(gr.hier_block2):
+ """ Two inputs: true and received bits. We compare them and
+ add up the number of incorrect bits. Because integrate_ff()
+ can only add up a certain number of values, the output is
+ not a scalar, but a sequence of values, the sum of which is
+ the BER. """
+ def __init__(self, bits_per_byte):
+ gr.hier_block2.__init__(self, "BitErrors",
+ gr.io_signature(2, 2, gr.sizeof_char),
+ gr.io_signature(1, 1, gr.sizeof_int))
+
+ # Bit comparison
+ comp = gr.xor_bb()
+ intdump_decim = 100000
+ if N_BITS < intdump_decim:
+ intdump_decim = int(N_BITS)
+ self.connect(self,
+ comp,
+ gr.unpack_k_bits_bb(bits_per_byte),
+ gr.uchar_to_float(),
+ gr.integrate_ff(intdump_decim),
+ gr.multiply_const_ff(1.0/N_BITS),
+ self)
+ self.connect((self, 1), (comp, 1))
+
+class BERAWGNSimu(gr.top_block):
+ " This contains the simulation flow graph "
+ def __init__(self, EbN0):
+ gr.top_block.__init__(self)
+ self.const = digital.qpsk_constellation()
+ # Source is N_BITS bits, non-repeated
+ data = map(int, numpy.random.randint(0, self.const.arity(), N_BITS/self.const.bits_per_symbol()))
+ src = gr.vector_source_b(data, False)
+ mod = gr.chunks_to_symbols_bc((self.const.points()), 1)
+ add = gr.add_vcc()
+ noise = gr.noise_source_c(gr.GR_GAUSSIAN,
+ self.EbN0_to_noise_voltage(EbN0),
+ RAND_SEED)
+ demod = digital.constellation_decoder_cb(self.const.base())
+ ber = BitErrors(self.const.bits_per_symbol())
+ self.sink = gr.vector_sink_f()
+ self.connect(src, mod, add, demod, ber, self.sink)
+ self.connect(noise, (add, 1))
+ self.connect(src, (ber, 1))
+
+ def EbN0_to_noise_voltage(self, EbN0):
+ """ Converts Eb/N0 to a single-sided noise voltage (assuming unit symbol power) """
+ return 1.0 / math.sqrt(2.0 * self.const.bits_per_symbol() * 10**(float(EbN0)/10))
+
+
+def simulate_ber(EbN0):
+ """ All the work's done here: create flow graph, run, read out BER """
+ print "Eb/N0 = %d dB" % EbN0
+ fg = BERAWGNSimu(EbN0)
+ fg.run()
+ return numpy.sum(fg.sink.data())
+
+if __name__ == "__main__":
+ EbN0_min = 0
+ EbN0_max = 15
+ EbN0_range = range(EbN0_min, EbN0_max+1)
+ ber_theory = [berawgn(x) for x in EbN0_range]
+ print "Simulating..."
+ ber_simu = [simulate_ber(x) for x in EbN0_range]
+
+ f = pylab.figure()
+ s = f.add_subplot(1,1,1)
+ s.semilogy(EbN0_range, ber_theory, 'g-.', label="Theoretical")
+ s.semilogy(EbN0_range, ber_simu, 'b-o', label="Simulated")
+ s.set_title('BER Simulation')
+ s.set_xlabel('Eb/N0 (dB)')
+ s.set_ylabel('BER')
+ s.legend()
+ s.grid()
+ pylab.show()
+
--
1.7.9.5
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