Increasing demand for higher-speed and large-capacity data communications has driven the development of constellation shaping technology. This paper proposes a hybrid constellation shaping scheme for 64-quadrature amplitude modulation (64QAM) based on hexagonal lattice of a constellation subset. The proposed scheme aims to enhance the nonlinear tolerance of higher-order modulated signals and further improve the constellation shaping gain. The initial quantitative characterization of the constellation is firstly performed based on the hexagonal lattice structure. Then, the objective function of maximizing constellation figure of merits (CFM) is utilized to determine the position distribution of constellation points, resulting in the generation of the geometric shaping-64QAM (GS-64QAM) signal. Finally, according to concentric hexagonal layers, all constellation points are divided into multiple subsets where points within the same subset are assigned the same probability, and the hybrid shaping-64QAM (HS-64QAM) signal is generated. To validate the effectiveness of the proposed scheme, the experimental verification was demonstrated in a 120 Gbit/s multi-span coherent optical communication system. Experimental results indicate that, at the soft-decision forward error correction threshold, HS-64QAM achieves an optical signal-to-noise ratio (OSNR) gain of 1.9 dB and 4.1 dB over uniform GS-64QAM in back-to-back and 375 km transmission scenarios, respectively. Furthermore, HS-64QAM achieves an OSNR gain of 2.7 dB and 7.6 dB over uniform Square-64QAM in back-to-back and 375 km transmission scenarios, respectively.

With the increase in global wireless traffic, the use of large-scale satellite networking to provide ubiquitous access is one of the essential trends of future 6G network development. Elastic optical satellite networks (EOSNs) are widely considered a flexible solution for future satellite communication. However, with the continuous proliferation of network devices and users, the growing disparity between user demands and the limited bandwidth and capacity of the network is becoming increasingly noticeable. This has led to issues such as constrained network resource utilization and resource fragmentation. Therefore, EOSNs must efficiently address the challenge of allocating scarce bandwidth resources. Effective traffic grooming methods will be applied to EOSNs to solve the problem of bandwidth shortage. This paper proposed a dynamic traffic grooming algorithm based on virtualization-plane-aided optimization (DTG-VPO) to facilitate the bandwidth allocation for EOSNs. Firstly, the nodes of the alternative paths were graded, and the weights of the subsequent hop links were modified. Then, the path was evaluated using link weights, alternative paths were selected in the virtual and physical topologies, respectively, and a path set was constructed. Finally, a resource block evaluation parameter was designed to quantify the quality of candidate resource blocks and rank them. A series of simulations have evaluated the traffic-blocking probability and wavelength utilization under different traffic loads. The link resource was more fully utilized compared with other traffic grooming algorithms. The blocking probability can be reduced by 75%, while wavelength utilization can be improved by 8.1%.

Orthogonal time–frequency space (OTFS) modulation combined with massive multiple-input multiple-output (MIMO) can simultaneously address the problems caused by multipath delay, the Doppler effect, and channel fading. To mitigate inter-subcarrier and inter-symbol interference in satellite–terrestrial MIMO-OTFS systems, an iterative maximum ratio combining detection algorithm based on hard-decision interference cancelation (ICH-IMRC) is proposed. The signal detection is iterated by performing MRC on the interference-canceled received symbols. To mitigate the error spread in the interference cancelation process, iterative maximum ratio combining detection based on soft symbol interference cancelation (S-IMRC) is proposed, which is improved based on ICH-IMRC. The interference cancelation is updated by the expectation of other symbols, and the expectation and variance of symbols are updated by soft judgment with the posterior probability of symbols. To improve the detection convergence speed, optimal relaxation parameters are obtained based on the Sparrow Search Algorithm (SSA). Simulation results show that the proposed S-IMRC has superior error rate performance compared to the conventional algorithms for satellite–terrestrial MIMO-OTFS systems. Furthermore, the proposed algorithm is applicable to various satellite channel models and achieves excellent BER for different orders of orthogonal amplitude-modulated signals and different antenna array sizes.