## 4 Enabling Technologies for FSO Communication
### Adaptive Detection Thresholds
#### 4.10.1 Background  
In the absence of scintillation, the BER of an FSO system can be improved significantly through the use of an optimal detection threshold based on the maximum likelihood princi  
Figure 14: Categorization of PAT mechanisms in FSO communications based on their dimensionality. ple, assuming the bit level means and variances are known. However, in an atmospheric channel, turbulence-induced scintillation causes considerable fluctuations in the bit means and variances, which in turn affects the optimal threshold. To address this, a new thresholding method has been developed that replaces the constant threshold with an adaptive one. This method utilizes a Kalman filter algorithm to continuously track and adjust the bit means and variances. In this context, conventional fixed detection thresholds (FDTs) are insufficient for the dynamic environments of FSO systems, as they fail to consider real-time fluctuations in signal quality. Conversely, ADTs improve system performance by dynamically adjusting threshold levels based on the existing channel conditions, thereby optimizing the detection process [413]. Typically, the standard approach for adaptive detection assumes perfect knowledge of the instantaneous CSI, utilizing the instantaneous SNR to detect each data symbol [414; 415; 416; 417]. To ensure reliable communication, adaptive detection techniques can be used to dynamically adjust the Rx sensitivity in response to these fluctuations [418; 419; 420; 421; 422]. Consequently, ADT methods have garnered significant interest as effective strategies for alleviating the impacts of AT in FSO. ADT enables systems to attain improved average BER with low complexity [418]. For instance, it is well known that an OOK IM/DD system with a fixed decision techniques leads to an irreducible error floor and is power inefficient. Optimal OOK demodulation necessitates time-varying ADTs based on perfect CSI for detecting each data symbol [415; 416; 421; 194]. However, this approach presents clear practical challenges for OOK IM/DD operation with nanosecond data symbol durations (i.e., Gb/s rates) and millisecond turbulence coherence times. Specifically, it necessitates rapid adjustments to the detection threshold on the millisecond timescale of turbulence coherence times [415; 416; 423]. In this context, practical FSO systems will not be able to accurately track changes in the means and variances at the bit level. Therefore, optimizing the threshold to a constant value based on slowly varying statistical quantities, such as average signal power and turbulence strength, can also be adopted as a suboptimal method [413; 422]. Although the performance of the Rx heavily relies on the chosen threshold level [420], determining the appropriate ADT remains a challenge [418]. Previous studies often assume detection with instantaneous CSI [293; 10]. To address these practical issues, an electrical-SNR-optimized detection system has been proposed [211; 424]. This system requires changing the detection thresholds only over extended timescales, such as seconds or minutes, during which a stationary turbulence channel assumption is valid [425]. However, this method necessitates knowledge of the turbulence channel's PDF, thereby increasing computational complexity [414]. For instance, research has indicated that estimating the fading intensity requires using redundant overhead, such as pilot symbols or training sequences [426]. In [424], pilot-symbol assisted modulation (PSAM) and the maximum likelihood method are introduced as methods to reduce the effects of turbulence and improve system performance. However, PSAM can cause delays at the Rx because the entire frame must be stored before decoding. In practice, to simplify commercial implementation and ensure infrastructure transparency, detection without CSI and the PDF of the turbulence channel is the favored approach [194; 424].