<p>In recent studies on free-space optical communication, researchers have focused on improving data transmission speed. Optimizing resource management, including power allocation, in free-space optical communication enhances the number of bits received at the receiver. To calculate the optimal transmitter power, consider a power range. Allocation of different power values is followed by balancing with bit error rate (BER) and signal-to-noise ratio (SNR) values for all free-space optical communication scenarios. Channels with high BER values and low SNR are allocated higher powers. Channels with low fading and BER are assigned low transmitter powers. A real-time power allocation system is necessary due to the complex analytical equations and changing atmospheric conditions in FSO channels. Therefore, a fuzzy inference system is designed to allocate optimal power in real-time, eliminating the need to calculate and analyze all states for the free-space optical channel. The results indicate that fuzzy power allocation achieves an accuracy of 90% with an SNR input and over 95% with a BER input. With the fuzzy power allocation method, the number of received bits was optimized accurately.</p>

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Fuzzy-analytical power allocation based on SNR and balanced BER in free-space optical communication

  • Mahdi Akbari,
  • Saeed Olyaee,
  • Gholamreza Baghersalimi

摘要

In recent studies on free-space optical communication, researchers have focused on improving data transmission speed. Optimizing resource management, including power allocation, in free-space optical communication enhances the number of bits received at the receiver. To calculate the optimal transmitter power, consider a power range. Allocation of different power values is followed by balancing with bit error rate (BER) and signal-to-noise ratio (SNR) values for all free-space optical communication scenarios. Channels with high BER values and low SNR are allocated higher powers. Channels with low fading and BER are assigned low transmitter powers. A real-time power allocation system is necessary due to the complex analytical equations and changing atmospheric conditions in FSO channels. Therefore, a fuzzy inference system is designed to allocate optimal power in real-time, eliminating the need to calculate and analyze all states for the free-space optical channel. The results indicate that fuzzy power allocation achieves an accuracy of 90% with an SNR input and over 95% with a BER input. With the fuzzy power allocation method, the number of received bits was optimized accurately.