Ryan Malloy
ec0dfedc50
Implement precision timing recovery functions: - _refine_symbol_boundary(): Scans at 1/32-symbol resolution to find exact chirp boundary by maximizing dechirped SNR - _find_sfd_boundary(): FFT-based correlation with downchirp template to find exact data start position Bug fixes: - Fix _is_downchirp() false positives by comparing both correlations - Fix _estimate_cfo() to return values in [0, N) range The improved sync_from_samples() now produces bins identical to the reference lora_decode_gpu decoder.
105 lines
3.5 KiB
Python
105 lines
3.5 KiB
Python
#!/usr/bin/env python3
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"""Test PHYDecode using symbols extracted by the existing decoder."""
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import sys
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from pathlib import Path
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import numpy as np
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sys.path.insert(0, str(Path(__file__).parent.parent / "python"))
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sys.path.insert(0, str(Path(__file__).parent.parent.parent / "gnuradio"))
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from rylr998 import Channelizer, PHYDecode
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from lora_decode_gpu import GPULoraDecoder, channelize
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from lora_phy import decode_frame_grlora, sync_word_to_networkid
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# Params
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SF = 9
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BW = 125e3
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# Load capture
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capture_path = Path(__file__).parent.parent.parent / "gnuradio" / "logs" / "capture_multi.raw"
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iq_raw = np.fromfile(capture_path, dtype=np.complex64)
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print(f"Loaded {len(iq_raw):,} samples")
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# Channelize using existing function
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iq_ch = channelize(iq_raw, 2e6, 915e6, 915e6, BW)
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print(f"Channelized to {len(iq_ch):,} samples")
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# Create existing decoder
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dec = GPULoraDecoder(sf=SF, bw=BW, sample_rate=BW, use_gpu=False)
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# Detect symbols
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print("\nDetecting symbols with existing decoder...")
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symbols, snrs = dec.batch_detect_symbols(iq_ch)
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print(f"Got {len(symbols)} symbols")
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# Find preambles
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preambles = dec.find_preambles(symbols, snrs)
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print(f"Found {len(preambles)} preambles")
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for i, (start_idx, length, avg_snr) in enumerate(preambles[:3]):
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print(f"\n{'='*70}")
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print(f"Frame {i+1}: preamble at symbol {start_idx}, len={length}, SNR={avg_snr:.1f}dB")
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print("="*70)
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# Use existing decoder's demodulate_payload
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preamble_bin = int(symbols[start_idx])
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preamble_start_samples = start_idx * dec.samples_per_symbol
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result = dec.demodulate_payload(
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iq_ch,
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preamble_start_samples,
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length,
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preamble_snr=avg_snr,
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preamble_bin=preamble_bin,
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)
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if result is None:
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print(" demodulate_payload returned None")
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continue
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data_bins, cfo_bin = result
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print(f" CFO bin (preamble bin): {cfo_bin}")
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print(f" Data bins: {len(data_bins)} symbols")
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print(f" First 15 data bins: {list(data_bins[:15])}")
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# Decode with existing lora_phy
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print("\n Decoding with existing lora_phy.decode_frame_grlora:")
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frame = decode_frame_grlora(list(data_bins), sf=SF, cfo_bin=int(cfo_bin))
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print(f" Header OK: {frame.header_ok}")
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print(f" Payload len: {frame.payload_length}")
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print(f" CR: {frame.coding_rate}")
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print(f" CRC: {frame.has_crc} / OK={frame.crc_ok}")
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if frame.payload:
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try:
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text = frame.payload.decode('utf-8', errors='replace')
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print(f" Payload: {repr(text)}")
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except:
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print(f" Payload hex: {frame.payload.hex()}")
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# Decode with our PHYDecode
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print("\n Decoding with gr-rylr998 PHYDecode:")
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our_decoder = PHYDecode(sf=SF)
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our_frame = our_decoder.decode(
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list(data_bins),
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cfo_bin=int(cfo_bin),
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use_grlora_gray=True,
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soft_decoding=False,
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)
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print(f" Header OK: {our_frame.header_ok}")
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print(f" Payload len: {our_frame.payload_length}")
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print(f" CR: {our_frame.coding_rate}")
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print(f" CRC: {our_frame.has_crc} / OK={our_frame.crc_ok}")
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if our_frame.payload:
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try:
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text = our_frame.payload.decode('utf-8', errors='replace')
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print(f" Payload: {repr(text)}")
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except:
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print(f" Payload hex: {our_frame.payload.hex()}")
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# Check if they match
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if frame.payload == our_frame.payload:
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print("\n ✓ MATCH: Both decoders produced identical output!")
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else:
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print("\n ✗ MISMATCH: Decoders produced different output")
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