Free space optics (FSO) communication links are impaired by the fading due to turbulence and misalignment. In this paper, we theoretically analyze the pointing error effects on performance of FSO systems using multi-pulse pulse position modulation (MP-PPM) over the Gamma-Gamma turbulence channel. We consider the moderate and strong atmospheric turbulence regimes with the combined effect of the pointing errors (PEs), and study the link average symbol error rate (ASER) and the outage probability. The numerical results are presented to show the impact of the pointing error on the ASER and the system outage. However, to overcome the channel degradation resulting from the turbulence effects and the PE, the singleinput multiple-output (SIMO) system with maximal ratio combining (MRC) diversity is used. Exact close-form expressions for ASER and outage probability are derived and verified by using Monte Carlo simulation. We concluded that the optimal values of the system parameters are, the transmitted power is 20 dBm, jitter variance should be less than 0.5 m and laser beam width equals 0.2 cm. These values are significantly reduced the impacts of misalignment and fading whereas outage probability is less than at maximum jitter variance.
Adaptive spatial modulation (ASM) varies the modulation size across the transmit light-emitting diodes (LEDs) to improve the overall spectral efficiency of visible light communication (VLC) systems. This paper proposes a novel ASM scheme, referred to as flexible generalized spatial modulation (FGSM), for VLC systems. The proposed FGSM system changes the modulation sizes over the LEDs and the number of active LEDs, to improve the average symbol error rate (SER) and spectral efficiency compared to ASM with a fixed overall number of LEDs. The modulation sizes are selected in order to optimize the average SER under a predefined spectral efficiency value. A closed-form expression of approximate SER is derived along with decoding complexity calculations for the proposed system. Numerical results are provided to confirm the superiority of the proposed system and to support theoretical derivations.
This paper proposes a signal-to-noise ratio (SNR) estimator based on recurrent neural network (RNN) in optical fiber communication links. The proposed estimator jointly estimates the linear and nonlinear components of the SNR. The input features of the proposed estimator are carefully designed based on a combination of the lower quartile and entropy extracted from the received signal. The proposed input features do not require knowledge of the transmitted symbols. In the proposed SNR estimator, three different RNN models are investigated, namely simple RNN, gated recurrent units, and long shortterm memory. The overall computational complexity of the three models of the proposed estimator, including the feature extraction and RNN structures, are analyzed. Numerical results show that the three models of the proposed estimator provide a trade-off between the complexity of the RNN structure and estimation accuracy. Furthermore, the proposed estimator achieves a better SNR estimation accuracy and reduces the overall computational complexity compared to the literature.
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