commit 682afabb30308f125ac566eca89c1401085c0146
parent b2eb2a6ee415168d82e791c85825047d8f1dbf10
Author: Egor Achkasov <eaachkasov@edu.hse.ru>
Date: Fri, 8 Nov 2024 13:02:56 +0100
Initial ara changes
Diffstat:
14 files changed, 172 insertions(+), 163 deletions(-)
diff --git a/.gitignore b/.gitignore
@@ -5,4 +5,5 @@ build
obj
.vscode
*__pycache__*
-.gdb_history
-\ No newline at end of file
+.gdb_history
+*.o
diff --git a/GNUmakefile b/GNUmakefile
@@ -1,7 +1,7 @@
CC = gcc
-CFLAGS = -Iinc -fno-builtin -Wall -Wextra
+CFLAGS = -Iinclude -fno-builtin -Wall -Wextra
OBJDIR = obj
-BUILDDIR = build
+BUILDDIR = .
SRC = $(wildcard src/*.c)
OBJ = $(SRC:src/%.c=$(OBJDIR)/%.o)
@@ -31,7 +31,7 @@ $(OBJDIR)/main.o: main.c
$(CC) $(CFLAGS) -c $< -o $@
clean:
- rm -rf $(OBJDIR)/* $(BUILDDIR)/*
+ rm -rf $(OBJDIR)/* $(BUILDDIR)/mmse
.PHONY: all dbg clean
diff --git a/inc/define.h b/include/define.h
diff --git a/inc/mmserv.h b/include/mmserv.h
diff --git a/main.c b/main.c
@@ -1,4 +1,4 @@
-#include "inc/mmserv.h"
+#include "include/mmserv.h"
int main() {
uint32_t i, j, k;
@@ -8,10 +8,13 @@ int main() {
data_t H_raw[NUM_RX_ANT][NUM_TX_ANT][NUM_SC][2]; /* Channel */
data_t R_raw[NUM_TX_ANT][NUM_TX_ANT][NUM_SC][2]; /* Noise covariance matrix */
data_t y_raw[NUM_RX_ANT][NUM_SC][2]; /* Received signal */
- load_data("data\\x.bin", NUM_TX_ANT*NUM_SC*2, x_raw);
- load_data("data\\H.bin", NUM_RX_ANT*NUM_TX_ANT*NUM_SC*2, H_raw);
- load_data("data\\R.bin", NUM_TX_ANT*NUM_RX_ANT*NUM_SC*2, R_raw);
- load_data("data\\y.bin", NUM_RX_ANT*NUM_SC*2, y_raw);
+
+#ifndef ARA
+ load_data("data/x.bin", NUM_TX_ANT*NUM_SC*2, x_raw);
+ load_data("data/H.bin", NUM_RX_ANT*NUM_TX_ANT*NUM_SC*2, H_raw);
+ load_data("data/R.bin", NUM_TX_ANT*NUM_RX_ANT*NUM_SC*2, R_raw);
+ load_data("data/y.bin", NUM_RX_ANT*NUM_SC*2, y_raw);
+#endif
/* Cast the data into complex data structures */
complex x[NUM_TX_ANT][NUM_SC];
diff --git a/script/gen_data.py b/script/gen_data.py
@@ -0,0 +1,96 @@
+#!/usr/bin/python
+
+from util import read_defines, interleave
+
+import numpy as np
+from numpy.random import random, normal
+from sys import argv
+from os import path, makedirs
+
+if "--help" in argv:
+ print("Usage: python scripts/gen_data.py [--txt] [--bin] [--s]")
+ print(" --txt: write the data/*.txt files")
+ print(" --bin: write the data/*.bin files")
+ print(" --s: print the .S file to stdout")
+ exit(0)
+
+# Change these flags to control the output
+WRITE_DATA_TXT = "--txt" in argv
+WRITE_DATA_BIN = "--bin" in argv
+WRITE_DATA_S = "--s" in argv or len(argv) == 1
+
+NUM_RX_ANT, NUM_TX_ANT, NUM_SC = read_defines()
+NOISE_STD_DEVIATION = np.sqrt(.5) / 100 # noise standard deviation
+
+# Transmitter signal
+x = random((NUM_TX_ANT, NUM_SC)) \
+ + 1.j * random((NUM_TX_ANT, NUM_SC))
+x = (x - 0.5 - 0.5j) * 2 # scale it from [0, 1] to [-1, 1]
+# Channel
+H = random((NUM_RX_ANT, NUM_TX_ANT, NUM_SC)) \
+ + 1.j * random((NUM_RX_ANT, NUM_TX_ANT, NUM_SC))
+H = (H - 0.5 - 0.5j) * 2 # scale it from [0, 1] to [-1, 1]
+# Noise
+n = normal(0, NOISE_STD_DEVIATION, (NUM_RX_ANT, NUM_SC)) \
+ + 1.j * normal(0, NOISE_STD_DEVIATION, (NUM_RX_ANT, NUM_SC))
+# Received signal
+y = np.einsum("ijk,jk->ik", H, x) + n
+
+# Noise covariance matrix
+R = np.eye(NUM_TX_ANT, NUM_TX_ANT, dtype=np.complex64) * NOISE_STD_DEVIATION**2
+
+# Cast the complex data to int16
+x_data = interleave(x)
+H_data = interleave(H)
+R_data = interleave(R)
+y_data = interleave(y)
+data_tuple = (x_data, H_data, R_data, y_data)
+
+
+class Section:
+ def __init__(self, name, source, align, sizeof, length, duplicate=False):
+ self.name = name
+ self.source = source
+ self.align = align
+ self.sizeof = sizeof
+ self.length = length
+ self.duplicate = duplicate
+
+
+sections = [
+ Section("x_raw", "data/x.txt", "3", 32, x.size * 2),
+ Section("H_raw", "data/H.txt", "3", 32, H.size * 2),
+ Section("R_raw", "data/R.txt", "3", 32, R.size * 2),
+ Section("y_raw", "data/y.txt", "3", 32, y.size * 2),
+]
+
+# Create "data" directory if it does not exist
+if WRITE_DATA_BIN or WRITE_DATA_TXT:
+ data_dir = path.join(path.dirname(__file__), "..", "data")
+ if not path.exists(data_dir):
+ makedirs(data_dir)
+
+if WRITE_DATA_TXT:
+ for data, sec in zip(data_tuple, sections):
+ with open(sec.source, "w") as f:
+ for sample in data:
+ f.write(f"{sample}\n")
+
+if WRITE_DATA_BIN:
+ for data, sec in zip(data_tuple, sections):
+ with open(sec.source.replace(".txt", ".bin"), "wb") as f:
+ f.write(data.tobytes())
+
+if WRITE_DATA_S:
+ print(".section .data,\"aw\",@progbits")
+ for data, sec in zip(data_tuple, sections):
+ print(f".global {sec.name}")
+ print(f"{sec.name}:")
+ for sample in data:
+ bs = sample.tobytes()
+ for i in range(0, len(bs), 4):
+ s = ""
+ for n in range(4):
+ s += "%02x" % bs[i+3-n]
+ print(" .word 0x%s" % s)
+
diff --git a/scripts/mmse.py b/script/mmse.py
diff --git a/scripts/mmse_nosqrt.py b/script/mmse_nosqrt.py
diff --git a/scripts/simulation-run.fish b/script/simulation-run.fish
diff --git a/script/util.py b/script/util.py
@@ -0,0 +1,59 @@
+from os import path
+import numpy as np
+
+
+def read_defines():
+ """Read the defines from the define.h file
+
+ Returns:
+ int: Number of receive antennas
+ int: Number of transmit antennas
+ int: Number of subcarriers
+ """
+ with open(path.join(path.dirname(__file__), "..", "include", "define.h"), "r") as f:
+ lines = f.read().split("\n")
+ for line in lines:
+ if line.startswith("#define NUM_RX_ANT "):
+ NUM_RX_ANT = int(line[19:])
+ if line.startswith("#define NUM_TX_ANT "):
+ NUM_TX_ANT = int(line[19:])
+ if line.startswith("#define NUM_SC "):
+ NUM_SC = int(line[15:])
+
+ # Assert that all the defines are read
+ assert NUM_RX_ANT
+ assert NUM_TX_ANT
+ assert NUM_SC
+
+ return NUM_RX_ANT, NUM_TX_ANT, NUM_SC
+
+
+def interleave(data: np.ndarray) -> np.ndarray:
+ """Cast a np.complex64 array to np.float32 array.
+
+ Args:
+ data (np.ndarray): The complex data to be casted. Dtype: np.complex64
+
+ Returns:
+ np.ndarray: The interleaved data. Dtype: np.float32
+ """
+ res = np.empty(2 * data.size, dtype=np.float32)
+ res[0::2] = data.flatten().real.astype(np.float32)
+ res[1::2] = data.flatten().imag.astype(np.float32)
+ return res
+
+
+def deinterleave(data: np.ndarray, shape: tuple) -> np.ndarray:
+ """Cast a np.float32 array to np.complex64 array.
+
+ Args:
+ data (np.ndarray): The interleaved data to be casted. Dtype: np.float32
+ shape (tuple): The shape of the deinterleaved data.
+
+ Returns:
+ np.ndarray: The deinterleaved data. Dtype: np.complex64
+ """
+ res = np.empty(shape, np.complex64)
+ res.real = data[0::2].reshape(shape)
+ res.imag = data[1::2].reshape(shape)
+ return res
diff --git a/scripts/viz_compare_x.py b/script/viz_compare_x.py
diff --git a/scripts/gen_data.py b/scripts/gen_data.py
@@ -1,90 +0,0 @@
-#!/usr/bin/python
-
-from util import read_defines, interleave
-
-import numpy as np
-from numpy.random import random, normal
-from sys import argv
-from os import path, makedirs
-
-if "--help" in argv:
- print("Usage: python scripts/gen_data.py [--txt] [--bin] [--s]")
- print(" --txt: write the data/*.txt files")
- print(" --bin: write the data/*.bin files")
- print(" --s: print the .S file to stdout")
- exit(0)
-
-# Change these flags to control the output
-WRITE_DATA_TXT = "--txt" in argv
-WRITE_DATA_BIN = "--bin" in argv
-WRITE_DATA_S = "--s" in argv
-
-NUM_RX_ANT, NUM_TX_ANT, NUM_SC = read_defines()
-NOISE_STD_DEVIATION = np.sqrt(.5) / 100 # noise standard deviation
-
-# Transmitter signal
-x = random((NUM_TX_ANT, NUM_SC)) \
- + 1.j * random((NUM_TX_ANT, NUM_SC))
-x = (x - 0.5 - 0.5j) * 2 # scale it from [0, 1] to [-1, 1]
-# Channel
-H = random((NUM_RX_ANT, NUM_TX_ANT, NUM_SC)) \
- + 1.j * random((NUM_RX_ANT, NUM_TX_ANT, NUM_SC))
-H = (H - 0.5 - 0.5j) * 2 # scale it from [0, 1] to [-1, 1]
-# Noise
-n = normal(0, NOISE_STD_DEVIATION, (NUM_RX_ANT, NUM_SC)) \
- + 1.j * normal(0, NOISE_STD_DEVIATION, (NUM_RX_ANT, NUM_SC))
-# Received signal
-y = np.einsum("ijk,jk->ik", H, x) + n
-
-# Noise covariance matrix
-R = np.eye(NUM_TX_ANT, NUM_TX_ANT, dtype=np.complex64) * NOISE_STD_DEVIATION**2
-
-# Cast the complex data to int16
-x_data = interleave(x)
-H_data = interleave(H)
-R_data = interleave(R)
-y_data = interleave(y)
-data_tuple = (x_data, H_data, R_data, y_data)
-
-
-class Section:
- def __init__(self, name, source, align, sizeof, length, duplicate=False):
- self.name = name
- self.source = source
- self.align = align
- self.sizeof = sizeof
- self.length = length
- self.duplicate = duplicate
-
-
-sections = [
- Section("x", "data/x.txt", "3", 32, x.size * 2),
- Section("H", "data/H.txt", "3", 32, H.size * 2),
- Section("R", "data/R.txt", "3", 32, R.size * 2),
- Section("y", "data/y.txt", "3", 32, y.size * 2),
-]
-
-# Create "data" directory if it does not exist
-if WRITE_DATA_BIN or WRITE_DATA_TXT:
- data_dir = path.join(path.dirname(__file__), "..", "data")
- if not path.exists(data_dir):
- makedirs(data_dir)
-
-if WRITE_DATA_TXT:
- for data, sec in zip(data_tuple, sections):
- with open(sec.source, "w") as f:
- for sample in data:
- f.write(f"{sample}\n")
-
-if WRITE_DATA_BIN:
- for data, sec in zip(data_tuple, sections):
- with open(sec.source.replace(".txt", ".bin"), "wb") as f:
- f.write(data.tobytes())
-
-if WRITE_DATA_S:
- print(".section .data,\"aw\",@progbits")
- for data, sec in zip(data_tuple, sections):
- print(f".global {sec.name}")
- print(f"{sec.name}:")
- for sample in data:
- print(f" .hword 0x{sample.view(np.uint16):04x} // {sample}")
diff --git a/scripts/util.py b/scripts/util.py
@@ -1,59 +0,0 @@
-from os import path
-import numpy as np
-
-
-def read_defines():
- """Read the defines from the define.h file
-
- Returns:
- int: Number of receive antennas
- int: Number of transmit antennas
- int: Number of subcarriers
- """
- with open(path.join(path.dirname(__file__), "..", "inc", "define.h"), "r") as f:
- lines = f.read().split("\n")
- for line in lines:
- if line.startswith("#define NUM_RX_ANT "):
- NUM_RX_ANT = int(line[19:])
- if line.startswith("#define NUM_TX_ANT "):
- NUM_TX_ANT = int(line[19:])
- if line.startswith("#define NUM_SC "):
- NUM_SC = int(line[15:])
-
- # Assert that all the defines are read
- assert NUM_RX_ANT
- assert NUM_TX_ANT
- assert NUM_SC
-
- return NUM_RX_ANT, NUM_TX_ANT, NUM_SC
-
-
-def interleave(data: np.ndarray) -> np.ndarray:
- """Cast a np.complex64 array to np.float32 array.
-
- Args:
- data (np.ndarray): The complex data to be casted. Dtype: np.complex64
-
- Returns:
- np.ndarray: The interleaved data. Dtype: np.float32
- """
- res = np.empty(2 * data.size, dtype=np.float32)
- res[0::2] = data.flatten().real.astype(np.float32)
- res[1::2] = data.flatten().imag.astype(np.float32)
- return res
-
-
-def deinterleave(data: np.ndarray, shape: tuple) -> np.ndarray:
- """Cast a np.float32 array to np.complex64 array.
-
- Args:
- data (np.ndarray): The interleaved data to be casted. Dtype: np.float32
- shape (tuple): The shape of the deinterleaved data.
-
- Returns:
- np.ndarray: The deinterleaved data. Dtype: np.complex64
- """
- res = np.empty(shape, np.complex64)
- res.real = data[0::2].reshape(shape)
- res.imag = data[1::2].reshape(shape)
- return res
diff --git a/src/mmserv.c b/src/mmserv.c
@@ -1,4 +1,4 @@
-#include "mmserv.h"
+#include "../include/mmserv.h"
#include <stdlib.h> // for exit
@@ -18,7 +18,7 @@ complex cmul(IN complex a, IN complex b)
complex t;
t.re = a.re * b.re - a.im * b.im;
t.im = a.im * b.re + a.re * b.im;
- return t;
+ return t;
}
data_t cabs2(IN complex a)
{
@@ -292,7 +292,7 @@ void load_data(
OUT data_t *out)
{
FILE *fp = fopen(file, "rb");
-
+
if (fp == NULL) {
fprintf(stderr, "Error opening file %s.\n", file);
exit(8);
@@ -310,7 +310,7 @@ void save_data(
IN data_t x_mmse[NUM_TX_ANT][NUM_SC][2])
{
FILE *fp = fopen(file, "wb");
-
+
if (fp == NULL) {
fprintf(stderr, "Error opening file %s.\n", file);
exit(8);
