Mitigation of turbulence-induced scintillation and ASE noise using aperture averaging based on hybrid DPPM and OOK modulation of FSO systems

The performance evaluation of free-space optical (FSO) communication using a digital pulse position modulation (DPPM) is investigated in this paper. The impact of atmospheric turbulence, scintillation and amplified spontaneous emission (ASE) noise has been taken into account. To reduce the turbulence-induced scintillation and optical power penalty, the use aperture averaging (AA) has been proposed in this paper. To evaluate the bit-error rate (BER) performance in the presence the atmospheric turbulence and amplified spontaneous emission (ASE), the use of the moment generation function (MGF) techniques are explained with the modified Chernoff bound (MCB) that is more accurate and an appropriate from Chernoff bound (CB). Such a system, which could provide a power efficient, a low cost, excessive flexibility and reliable or considered a massive solution in the bandwidth provision for future access networks, and together for higher data rate. The BER, are given for an optically preamplified DPPM FSO communication system impaired by pointing error (PE) and atmospheric turbulence combined, in addition to the ASE noise arising from the optical amplification. The gamma–gamma (GG) distribution model is used to characterize the whole range of turbulence conditions. The results reveal the superiority of DPPM with improved receiver sensitivity (at a binary data rate 2.5 Gbps and at typical FSO BER of 10 ^-9) of about 10 dB –11 dB for coding level (M) of 5 and optical link length (for turbulent interaction) of 2000 m more than an equivalent optically preamplified on-off keying non-return-to-zero (OOK-NRZ) approach, depending on the level of turbulence.

Improved bit error rate evaluation of M-ary DPPM modulation using an aperture averaging for FSO systems impaired by interchannel crosstalk and ASE noise

The performance evaluation of free-space optical (FSO) communication system using the digital pulse position modulation (DPPM) and on-off keying non-return-to-zero (OOK-NRZ) approach are investigated in this paper. The impact of atmospheric turbulence, scintillation and amplified spontaneous emission (ASE) noise has been taken into account. To reduce the turbulence-induced scintillation and optical power penalty, the use aperture averaging has been proposed in this paper. To evaluate the bit-error rate (BER) performance in the presence the atmospheric turbulence and amplified spontaneous emission (ASE), the use of the moment generation function techniques are explained with the modified Chernoff bound that is more accurate and an appropriate from Chernoff bound. Such a system, which could provide a power efficient, a low cost, excessive flexibility and reliable or considered a massive solution in the bandwidth provision for future access networks, and together for higher data rate. The BER, are given for an optically preamplified DPPM FSO communication system impaired by pointing error and atmospheric turbulence combined, in addition to the ASE noise arising from the optical amplification. The gamma–gamma distribution model is used to characterize the whole range of turbulence conditions. The results reveal the superiority of DPPM with improved receiver sensitivity (at a binary data rate 2.5 Gbps and at typical FSO BER of 10-9) of about 10 dB – 11 dB for coding level (M) of 5 and optical link length (for turbulent interaction) of 2000 m more than an equivalent optically preamplified OOK-NRZ approach, depending on the leve of turbulence.

Performance Evaluation and Enhancement of M-Ary DPPM Modulation for WDM-PON/FSO Systems Impaired by Atmospheric Turbulence, Interchannel Crosstalk, and ASE Noise

This paper analyzes and enhances the performance of moment generating function techniques, notably the Chernoff bound (CB) and modified Chernoff bound (MCB), is used to improve the bit-error-rate (BER) performance of an optically pre-amplified for the wavelength division multiplexing (WDM) based on the passive optical network (PON) free-space optical (FSO) communications in the presence of both atmospheric turbulence (AT), amplified spontaneous emission (ASE) noise, and interchannel crosstalk. In the absence of AT and ASE at a data rate of 2.5 Gbps on the 1550 nm wavelength, digital pulse-position modulation (DPPM) systems with coding level (M) of 2 provide about 2.9 dB improvement in average power over at a BER of (depending on the turbulence level) compared with an equivalent on-off keying (OOK) non-return-to-zero (NRZ) in the WDM-PON/FSO system while maintaining minimum bandwidth expansion to leverage the extended reach and enhanced user capacity and considered as a good solution to the bandwidth requirement for future access networks, with potential for higher data rate, improved data security. The receiver sensitivities of M-ary DPPM about 51.4 dBm (~21.9 photons/bit) (CB), and 51.5 dBm (21.4 photons/bit, MCB) can be achieved, which implies an improvement when compared with an OOK-NRZ system (~38 photons/bit) in the non-turbulent atmospheric condition. M-ary DPPM retains its sensitivity improvement over OOK even in the existence of crosstalk while predicting a lower power penalty of about 0.2–3.0 dB for weak turbulence at low coding level (M) 2 in WDM systems.

Distance variable improvement of time-series big data stream evaluation

Real-time information mining of a big dataset consisting of time series data is a very challenging task. For this purpose, we propose using the mean distance and the standard deviation to enhance the accuracy of the existing fast incremental model tree with the drift detection (FIMT-DD) algorithm. The standard FIMT-DD algorithm uses the Hoeffding bound as its splitting criterion. We propose the further use of the mean distance and standard deviation, which are used to split a tree more accurately than the standard method. We verify our proposed method using the large Traffic Demand Dataset, which consists of 4,000,000 instances; Tennet’s big wind power plant dataset, which consists of 435,268 instances; and a road weather dataset, which consists of 30,000,000 instances. The results show that our proposed FIMT-DD algorithm improves the accuracy compared to the standard method and Chernoff bound approach. The measured errors demonstrate that our approach results in a lower Mean Absolute Percentage Error (MAPE) in every stage of learning by approximately 2.49% compared with the Chernoff Bound method and 19.65% compared with the standard method.

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

We prove equidistribution at shrinking scales for the monochromatic ensemble on a compact Riemannian manifold of any dimension. This ensemble on an arbitrary manifold takes a slowly growing spectral window in order to synthesize a random function. With high probability, equidistribution takes place close to the optimal wave scale and simultaneously over the whole manifold. The proof uses Weyl’s law to approximate the two-point correlation function of the ensemble, and a Chernoff bound to deduce concentration.

Concentration Bounds for High Sensitivity Functions Through Differential Privacy

A new line of work demonstrates how differential privacy can be used as a mathematical tool for guaranteeing generalization in adaptive data analysis. Specifically, if a differentially private analysis is applied on a sample S of i.i.d. examples to select a low-sensitivity function f, then w.h.p. f(S) is close to its expectation, even though f is being chosen adaptively, i.e., based on the data. Very recently, Steinke and Ullman observed that these generalization guarantees can be used for proving concentration bounds in the non-adaptive setting, where the low-sensitivity function is fixed beforehand. In particular, they obtain alternative proofs for classical concentration bounds for low-sensitivity functions, such as the Chernoff bound and McDiarmid's Inequality. In this work, we extend this connection between differential privacy and concentration bounds, and show that differential privacy can be used to prove concentration of high-sensitivity functions.