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Signal Processing and Transmission Quality Improvement Strategies in Artificial Intelligence-Assisted Software Radio Systems

Zhiguang Lei

Zhiguang Lei

Lanzhou Institute of PhysicsLanzhou, China
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Lei, Zhiguang
, 
Xin’an Qiu

Xin’an Qiu

Lanzhou Institute of PhysicsLanzhou, China
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Qiu, Xin’an
, 
Jun Yang

Jun Yang

Lanzhou Institute of PhysicsLanzhou, China
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Yang, Jun
, 
Dongtao Ma

Dongtao Ma

Lanzhou Institute of PhysicsLanzhou, China
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Ma, Dongtao
 und 
Zhijun Lei

Zhijun Lei

China Electronics Technology Group Corporation 58th Research InstituteWuxi, China
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Lei, Zhijun
  
17. März 2025
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Online veröffentlicht: 17. März 2025
Eingereicht: 18. Okt. 2024
Akzeptiert: 08. Feb. 2025
DOI: https://doi.org/10.2478/amns-2025-0346
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© 2025 Zhiguang Lei et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Software architecture of software radio system
Software architecture of software radio system

Figure 2.

Channel estimation process under complex electromagnetic interference environment
Channel estimation process under complex electromagnetic interference environment

Figure 3.

Experimental deployment of anti-jamming system based on Q learning
Experimental deployment of anti-jamming system based on Q learning

Figure 4.

The 18.5kbps rate mode system anti-single tone interference capability
The 18.5kbps rate mode system anti-single tone interference capability

Figure 5.

The 18.5 kbps rate mode system hard resistance to multi-tone interference capability
The 18.5 kbps rate mode system hard resistance to multi-tone interference capability

Figure 6.

The 18.5 kbps rate mode system hard resistance to Partial-band interference capability
The 18.5 kbps rate mode system hard resistance to Partial-band interference capability

Figure 7.

Constellation diagram of a software radio system in undisturbed and disturbed conditions
Constellation diagram of a software radio system in undisturbed and disturbed conditions

Figure 8.

Comparison of bit error rates of different frequency band selection schemes
Comparison of bit error rates of different frequency band selection schemes

Fading channel simulation parameters

Channel parameter Parameter value
Rice factor 50
Maximum path delay (us) [0, 2.5, 5]
Maximum Doppler shift (kHz) 20
Average path gain (dB) [0, -10, -10]

Link false alarm probabilities with different threshold values

Threshold value Th Average false alarm probability of links
9 4.5 × 10-5
10 3.1 × 10-5
11 1.6 × 10-5
12 6.2 × 10-6
13 2.7 × 10-6
14 7.6 × 10-7
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