Modeling and investigation on the performance enhancement of hovering UAV-based FSO relay optical wireless communication systems under pointing errors and atmospheric turbulence effects
Mohammed R. Hayal, Ebrahim E. Elsayed, Dhiman Kakati, Mehtab Singh, Abdelrahman Elfikky, Ayman I. Boghdady, Amit Grover, Shilpa Mehta, Syed Agha Hassnain Mohsan, Irfan Nurhidayat
Abstract
Abstract This paper investigates and enhances unmanned aerial vehicle (UAV) relay-assisted free-space optics (FSO) optical wireless communication (OWC) systems under the effects of pointing errors (PEs) and atmospheric turbulences (ATs). The incorporation of UAVs as buffer-aided moving relays in the conventional FSO (CFSO) relay-assisted systems is proposed for enhancing the performance of PEs through AT. Using M-PSK (phase shift keying) and M-QAM (quadrature amplitude modulation), the impact of PEs on transmission quality is evaluated in this work. We evaluate and optimize the symbol error rate, outage probability (OP), and signal-to-noise ratio (SNR) for the UAV-to-ground station-based FSO communications systems. The spatial diversity-based relay-assisted CFSO systems can enhance the performance of the UAV-UAV FSO links. In this paper, a new FSO (NFSO) channel model for the hovering UAV-FSO OWC fluctuations under the PEs, AT effects, jitter, deviation, receiving an error, and wind resistance effects are established. To improve the performance of hovering UAV-based FSO relay OWC systems. We reduce the influence of UAV-FSO OWC fluctuations under PEs and AT effects. By receiving incoherent signals at various locations, the spatial diversity-based relay-assisted NFSO systems can significantly increase the system's redundancy and enhance connection stability. Numerical results show that to achieve a bit-error-rate (BER) of $$\le 10^{ - 5}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>≤</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>5</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> , the required SNR is ≥ 23 dB when the wind variance of the UAVs $$\sigma_{\alpha }^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mi>σ</mml:mi> <mml:mrow> <mml:mi>α</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msubsup> </mml:math> increases from 0 to 7 mrad with FSO link distance L = 2000 m. The required SNR is ≥ 25 dB when the wind variance $$\sigma_{\alpha }^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mi>σ</mml:mi> <mml:mrow> <mml:mi>α</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msubsup> </mml:math> is 1 mrad at an OP of $$10^{ - 6}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>6</mml:mn> </mml:mrow> </mml:msup> </mml:math> . To obtain an average BER of $$10^{ - 6}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>6</mml:mn> </mml:mrow> </mml:msup> </mml:math> , the SNR should be 16.23 dB, 17.64 dB, and 21.45 dB when $$\sigma_{\alpha }^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mi>σ</mml:mi> <mml:mrow> <mml:mi>α</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msubsup> </mml:math> is 0 mrad, 1 mrad, and 2 mrad, respectively. Using 8-PSK modulation without PEs requires 23.5 dB at BER of $$10^{ - 8}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>8</mml:mn> </mml:mrow> </mml:msup> </mml:math> while 16-QAM without PEs requires 26.5 dB to maintain the same BER of $$10^{ - 8}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>8</mml:mn> </mml:mrow> </mml:msup> </mml:math> . Compared with 16-QAM without PEs, the SNR gain of 8-PSK without PEs is 3 dB. The results show the relay-assisted UAV-FSO system with five stationary relays can achieve BER $$10^{ - 8}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>8</mml:mn> </mml:mrow> </mml:msup> </mml:math> at 25 dB SNR in the ideal case and $$10^{ - 5}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>5</mml:mn> </mml:mrow> </mml:msup> </mml:math> at 27 dB SNR with AT and PE at FSO length 1000 m. The results show the relay UAV-FSO system outperforms the CFSO at the BER and SNR performance. The effects of UAV’FSO s fluctuation increase when the UAV-FSO link length, $${\text{L}}_{{{\text{fso}}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mtext>L</mml:mtext> <mml:mtext>fso</mml:mtext> </mml:msub> </mml:math> increases. The results of the weak turbulence achieve better SER compared with MT and ST. The obtained results show that decreasing $${\text{L}}_{{{\text{fso}}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mtext>L</mml:mtext> <mml:mtext>fso</mml:mtext> </mml:msub> </mml:math> can compensate for the effects of UAV-FSO link fluctuation on the proposed system. Finally, we investigated the CFSO relay-assisted UAV-FSO system with aided NFSO-UAVs spatial diversity-based relay-based on NFSO OWC and revealed the benefits of the resulting hybrid architecture.