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Legend dictionary: UWCA (trained) in fairness figure, UWCA (oracle) in real-data figure

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KiHoLee
2026-08-25 22:11:43 +09:00
parent 587a653f6b
commit 5020ab0569
5 changed files with 2 additions and 2 deletions
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experiments/make_figures.py
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@@ -65,7 +65,7 @@ for ax, sc, ttl in zip(axs, ["HIGH", "MIX"], ["(a) HIGH", "(b) MIX"]):
ax.semilogy(snr, v["lmmse_blind"]["ser"], "v-", color=C["blind"], ax.semilogy(snr, v["lmmse_blind"]["ser"], "v-", color=C["blind"],
markevery=(1, 2), label="LMMSE-blind") markevery=(1, 2), label="LMMSE-blind")
ax.semilogy(snr, v["noma"]["ser"], "^-.", color=C["noma"], label="NOMA-SIC") ax.semilogy(snr, v["noma"]["ser"], "^-.", color=C["noma"], label="NOMA-SIC")
ax.semilogy(snr, v["uwca"]["ser"], "o-", color=C["uwca"], label="UWCA (proposed)") ax.semilogy(snr, v["uwca"]["ser"], "o-", color=C["uwca"], label="UWCA (trained)")
ax.semilogy(snr, v["lmmse_genie"]["ser"], "d:", color=C["genie"], ax.semilogy(snr, v["lmmse_genie"]["ser"], "d:", color=C["genie"],
label="LMMSE-genie") label="LMMSE-genie")
ax.set_xlabel("SNR (dB)") ax.set_xlabel("SNR (dB)")
fig/fig_fair.pdf
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fig/fig_realdata_c.pdf
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fig/fig_resorth.pdf
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simulation/realdata_plot.py
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@@ -107,7 +107,7 @@ for j, s in enumerate(['HIGH', 'LOW', 'MIX']):
a.plot(SNR, ana[s]['OFDMA'], 's--', color=COL['OFDMA'], lw=2, ms=5, label='OMA') a.plot(SNR, ana[s]['OFDMA'], 's--', color=COL['OFDMA'], lw=2, ms=5, label='OMA')
a.plot(SNR, ana[s]['SFDMA'], 'v:', color=COL['SFDMA'], lw=2, ms=5, mfc='none', label='SFDMA') a.plot(SNR, ana[s]['SFDMA'], 'v:', color=COL['SFDMA'], lw=2, ms=5, mfc='none', label='SFDMA')
a.plot(SNR, ana[s]['NOMA-SIC'], '^-.', color=COL['NOMA-SIC'], lw=2, ms=5, label='NOMA-SIC') a.plot(SNR, ana[s]['NOMA-SIC'], '^-.', color=COL['NOMA-SIC'], lw=2, ms=5, label='NOMA-SIC')
a.plot(SNR, ana[s]['UWCA (analytical)'], ':', color=COL['UWCA (analytical)'], lw=2.4, label='UWCA (analytical)') a.plot(SNR, ana[s]['UWCA (analytical)'], ':', color=COL['UWCA (analytical)'], lw=2.4, label='UWCA (oracle)')
a.plot(SNR, trained[s]['UWCA w/ MAML'], 'o-', color=COL['UWCA w/ MAML'], lw=1.6, ms=6, mfc='none', mew=1.6, label='UWCA (trained)') a.plot(SNR, trained[s]['UWCA w/ MAML'], 'o-', color=COL['UWCA w/ MAML'], lw=1.6, ms=6, mfc='none', mew=1.6, label='UWCA (trained)')
a.set_ylim(0.1, 1.02); a.set_xlim(0, 20); a.grid(alpha=.3); a.set_box_aspect(0.85) a.set_ylim(0.1, 1.02); a.set_xlim(0, 20); a.grid(alpha=.3); a.set_box_aspect(0.85)
a.set_xlabel('SNR (dB)', fontsize=10) a.set_xlabel('SNR (dB)', fontsize=10)