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RIS-Assisted Hybrid THz/FSO Backhaul System Employing Spatial Modulation Switching

Year: 2026
Type: article
Abstract: The growing demand for ultra-reliable and high capacity backhaul networks poses significant challenges for sixth generation (6G) systems, particularly in dynamic environmental conditions. To address the limitations of conventional switching mechanisms, including data rate bottlenecks and frequent switching overhead, this paper introduces a novel hybrid terahertz (THz)/free-space optical (FSO) communication system. The proposed system adopts spatial modulation (SM) as the core mechanism for efficient link selection, which enhances spectral efficiency while eliminating explicit channel state information requirements at the transmitter (CSIT). To further enhance link reliability, reconfigurable intelligent surfaces (RIS) are integrated into the system architecture. The THz link is characterized by severe non-linear fading modeled by the α − μ distribution with pointing errors and molecular absorption, while the FSO link incorporates Gamma-Gamma turbulence, atmospheric attenuation, and pointing errors. By utilizing the multivariate Fox-H function, we derive exact closed-form expressions of the probability density function (PDF), cumulative distribution function (CDF), and moment-generating function (MGF) for the instantaneous SNR of the RIS-assisted THz links. Based on these statistical characterizations, we analytically evaluate the average bit error rate (ABER) of the proposed hybrid system. Monte Carlo simulations validate our analysis and demonstrate significant performance improvements compared to conventional architectures. To achieve a target ABER of 10−3, the proposed hybrid RIS-SM scheme achieves SNR gains of approximately 11 dB and 18 dB compared to the RIS-assisted FSO system and the hybrid SM system without RIS, respectively. The proposed framework establishes a new foundation for designing intelligent and spectrally efficient backhaul architectures in emerging hybrid networks.
Language: English
Open Access status: gold
Estimated APC paid: $2,075
OpenAlex ID: W7154631351
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