基于移动卫星星座系统的海洋通信关键技术研究

Nowadays, due to be possessed with significant strategic values, mobile satellite constellation system based marine communications have become one of the core information technologies, which are racing to be developed by all nations in the world. But there are still several problems as follows. First of all, there are difficulties of large range and quick variation parameters, such as noise and interference and so on, in the physical layer. Then, the problems of the decentralized data traffic control, load equalization and so on in the data link layer are also very hard. In addition, the challenges of the optimized route selection in the network layer are formidable too. Confronted with these difficult problems, this project will investigate key technologies of the sparse probability graph signal processing framework based distributed cross-layer coordinated relay transmission in marine-space data links. The research contents are as follows. It mainly investigates the performance prediction and efficient construction of the distributed relay forwarding low-density parity-check (LDPC) codes, the sparse cognitive identification of the space complex fading parameters and the iterative channel estimation, mutual information accumulation based generalized coordination signal detection in the multiple relays, the soft probability message propagation by the buffer aided relays and the cross-layer load equalization and some other related fundamental theories and the related software and hardware experimental verification technologies. The innovations of this project are listed as follows. The concatenations of the distributed and fragmented code words are randomly predicted and optimally constructed by sparse graphs. By means of soft probability metric propagation, the coordinated decoding and signal detection can be use to eliminate the mutual information loss, which mainly occurs in traditional communication and information systems without joint processing. Also the efficient mutual information accumulations based coordination message transmission via multiple relays is applied to accomplish fast cognitive detection of the iterative messages with low complexity, high efficiency and good reliability. The joint cross-layer store-and-forward, the load equalization and optimization in the multiple relays are also employed to improve the transmission efficiency. Finally, the anticipated research fruits of this project will help promote the perfection and development of the space-ocean data link strategic infrastructure in our country.

当前，因基于移动卫星星座系统的海洋通信具备重大战略价值，已成为世界各国竞相发展的核心信息技术之一。但其仍面临物理层噪声干扰等参数范围大及变化快等困难，链路层非中心化流量控制与负载均衡不易等问题，及网络层最优路由选择困难等挑战。面对这些难题，本项目拟开展基于稀疏概率图信号处理框架的海空数据链分布式跨层协同中继传输关键技术研究：分布式中继转发低密度奇偶校验码性能预测与高效构造；空间复杂衰落参数的稀疏认知识别与迭代信道估计；互信息累积广义多中继协同信号检测；软概率消息中继存储传递与跨层负载均衡等基础理论及其软硬件实验验证技术。其创新为：分布式码片级联的稀疏图随机预测及码字构造；软概率消息协作传递，消除非联合通信模块的外信息处理损失；多中继协同互信息累积传递，实现低复杂高效可靠迭代消息的快速认知检测；联合跨层多中继存储转发及负载均衡与优化。预期成果有助于促进我国空海数据链战略基础设施的完善和发展。

当前，因基于移动卫星星座系统的海洋通信具备重大战略价值，已成为世界各国竞相发展的核心信息技术之一。但其仍面临物理层噪声干扰等参数范围大及变化快等困难，链路层非中心化流量控制与负载均衡不易等问题，及网络层最优路由选择困难等挑战。面对这些难题，本项目拟开展基于稀疏概率图信号处理框架的海空数据链分布式跨层协同中继传输关键技术研究。理论成果主要如下：(1)编码协作转发：短码长高码率QC-LDPC原模图码优化构造；伪误码率迭代门限判决极化选择译码转发；协作判决门限polar编码选择译码转发及优化功率分配；高阶极化加权增量选择译码协作转发；(2)稀疏识别与估计：Doolittle分解和PCA-SVM分类的协作盲频谱检测；协方差Cholesky分解和RBF-SVM判决分类的改进盲频谱感知；认知无人机网SPRT协作频谱感知；LDPC译码软信息最陡下降迭代定时恢复；期望传播的频域Turbo均衡；IRS-SWIPT系统能效优先波束成形；协方差矩阵混合核SVM频谱感知；(3)广义互信息累积检测：LSTM活跃用户数估计和预测；MIL和RCG增强干扰对齐策略IRS辅助多用户MIMO；判决门限辅助的快速Z转发协作；选择软消息转发协作物理层网络编码；(4)安全网络存储与负载均衡：选择转发协作优化天线选择和自适应功率分配；面向事件驱动物联网IoT应用的流量模式区分节能；交织协作认知系统安全协作频谱感知；SWIPT使能中继网基于信任度的安全中继选择；分布式智能无线传输及资源共享。在应用研究方面，重点研究了上述海空一体通信系统核心算法软件和高速光无线传输等FPGA软硬件模块，研制了海空一体自主无线电软硬件仿真验证平台。项目共发表了38篇论文(14篇SCI)、授权了25项发明专利、出版了1部专著、获得了6项奖励(2项省部级)，并获得了较好经济及社会效益。成果有助于促进我国空海一体数据链战略基础设施的完善和发展。

内容获取失败，请点击重试