Performance of SIMO FSO Links over Mixture Composite Irradiance Channels

Androutsos, Nikolaos A.; Nistazakis, Hector E.; Stassinakis, Argyris N.; Sandalidis, Harilaos G.; Tombras, George S.

doi:10.3390/app9102072

Cited by 15 publications

(26 citation statements)

References 12 publications

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“…The PDF of the MG distribution, as a function of the irradiance I a,h in the h-th hop, is given as [19,20,36]: where…”

Section: Scintillation Modelmentioning

confidence: 99%

“…Here, on the basis of [19,20,34], for the extraction of the parameters for MG distribution, we match the two PDFs, i.e., (3), (24); the resulting parameters which are obtained, in order to approximate the NE distribution, are as follows [36]:…”

Section: Scintillation Model Through the Mg Distributionmentioning

confidence: 99%

“…where σ x,h and σ y,h are the standard deviation, i.e., the different jitters of the horizontal and elevation displacement respectively, and µ x,h , µ y,h are the different boresight errors in each axis of the receiver plane s 2 h = µ 2 x,h + µ 2 y,h [33]. Thus, the PDF as function of I p,m for the NZB-PE effect is approximated as [12,33,36]: where…”

Section: Nzb-pe Modelmentioning

confidence: 99%

“…In order to combat the limitations associated with fading, relay-assisted FSO communication is an effective method to extend coverage and performance [15,35]. In [36], the MG model is adopted for the estimation of the performance of a SIMO FSO system with receivers' diversity, operating under the composite impact of nonzero boresight pointing errors and turbulence-induced scintillation fading. However, in this work, we investigate a totally different architecture and MG approximation is used for the study of another significant issue which concerns the way in which the effective radius of the FSO links can be extended.…”

Section: Introductionmentioning

confidence: 99%

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Serial DF Relayed FSO Links over Mixture Gamma Turbulence Channels and Nonzero Boresight Spatial Jitter

et al. 2019

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Over the past few years, terrestrial free space optical (FSO) communication systems have demonstrated increasing research and commercial interest. However, due the signal’s propagation path, the operation of FSO links depends strongly on atmospheric conditions and related phenomena. One such significant phenomenon is the scintillation caused by atmospheric turbulence effects; in order to address the significant performance degradation that this causes, several statistical models have been proposed. Here, turbulence-induced fading of the received optical signal is investigated through the recently presented mixture Gamma distribution, which accurately describes the irradiance fluctuations at the receiver’s input of the FSO link. Additionally, at the same time, it significantly reduces the mathematical complexity of the expressions used for the description of composite channels with turbulence along with nonzero boresight pointing error-induced fading. In order to counterbalance the performance mitigation due to these effects, serial decode-and-forward relays are employed, and the performance of the system is estimated through derived mathematical expressions.

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“…The PDF of the MG distribution, as a function of the irradiance I a,h in the h-th hop, is given as [19,20,36]: where…”

Section: Scintillation Modelmentioning

confidence: 99%

Section: Scintillation Model Through the Mg Distributionmentioning

confidence: 99%

Section: Nzb-pe Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Serial DF Relayed FSO Links over Mixture Gamma Turbulence Channels and Nonzero Boresight Spatial Jitter

et al. 2019

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“…F Ree space optical communication (FSO) supports high data rate applications with minimum electromagnetic interference [1]. FSO requires a point-to-point link between transmitter and receiver and is sensitive to atmospheric turbulences, such as fog, dust, and sand storms that result in serious degradation of FSO link capacity [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Ensemble Consensus-based Representation Deep Reinforcement Learning for Hybrid FSO/RF Communication Systems

Henna¹

2021

Preprint

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<div>Hybrid FSO/RF system requires an efficient FSO and RF link switching mechanism to improve the system capacity by realizing the complementary benefits of both the links. The dynamics of network conditions, such as fog, dust, and sand storms compound the link switching problem and control complexity. To address this problem, we initiate the study of deep reinforcement learning (DRL) for link switching of hybrid FSO/RF systems. Specifically, in this work, we focus on actor-critic called Actor/Critic-FSO/RF and Deep-Q network (DQN) called DQN-FSO/RF for FSO/RF link switching under atmospheric turbulences. To formulate the problem, we define the state, action, and reward function of a hybrid FSO/RF system. DQN-FSO/RF frequently updates the deployed policy that interacts with the environment in a hybrid FSO/RF system, resulting in high switching costs. To overcome this, we lift this problem to ensemble consensus-based representation learning for deep reinforcement called DQNEnsemble-FSO/RF. The proposed novel DQNEnsemble-FSO/RF DRL approach uses consensus learned features representations based on an ensemble of asynchronous threads to update the deployed policy. Experimental results corroborate that the proposed DQNEnsemble-FSO/RF’s consensus learned features switching achieves better performance than Actor/Critic-FSO/RF, DQN-FSO/RF, and MyOpic for FSO/RF link switching while keeping the switching cost significantly low.</div>

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Pointing errors influence at the performance of a multi-hop terrestrial FSO link emulated by a dual-hop scheme

Androutsos

Nistazakis

Gappmair

et al. 2020

Optics Communications

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Performance of SIMO FSO Links over Mixture Composite Irradiance Channels

Cited by 15 publications

References 12 publications

Serial DF Relayed FSO Links over Mixture Gamma Turbulence Channels and Nonzero Boresight Spatial Jitter

Serial DF Relayed FSO Links over Mixture Gamma Turbulence Channels and Nonzero Boresight Spatial Jitter

Ensemble Consensus-based Representation Deep Reinforcement Learning for Hybrid FSO/RF Communication Systems

Pointing errors influence at the performance of a multi-hop terrestrial FSO link emulated by a dual-hop scheme

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