You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
V2 Tx: apply SSB BPF to data and EOO uniformly, default on
radae_v2.py's RADEv2Transmitter (used by tx2.py, the streaming reference
rade_c ports) previously used a different, narrower carrier-bandwidth-derived
filter than inference.py's actual SSB radio emulation (300-2700Hz, matching
training), and never filtered the EOO frame at all. Both now use the same
300-2700Hz filter, applied continuously across data and EOO through one
persistent filter state -- a real SSB radio's front end doesn't distinguish
data samples from EOO ones.
tx2.py's --ssb_bpf flipped to default-on (--no_bpf added as opt-out,
matching the existing --no_auxdata/--no_eoo pattern), since this is the
filter the model was actually trained under. inference.py's own default is
left untouched; --ssb_bpf added explicitly to the v2_tx2 ctest to keep it
matched now that tx2.sh defaults to filtered.
Also replaces rade_c_v2_rx_eoo (which used inference.py's --end_of_over_v2
splice -- AWGN-only on the EOO tail regardless of channel flags, and never
SSB-filtered) with a tx2.py -> ch -> C rx stack that genuinely fades/filters
the whole continuous data+EOO stream, plus MPP variants for both tx2.py and
the C Tx.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PzNQqmYXwUStAMrN4a5GFy
0 commit comments