Li Huanyu, Li Hui, Zhou Youling
Department of Information and Communication Engineering, Hainan University, Haikou 570228, China.
Department of Electronic Information Engineering, Binjiang College of UNIST, Wuxi 214105, China.
Entropy (Basel). 2021 Nov 1;23(11):1454. doi: 10.3390/e23111454.
This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the , we first establish a Longley-Rice-based channel model. Then, the weighted achievable rate (WAR) is considered as the optimization objective to weigh the information rate and user fairness effectively. Our work introduces an improved joint power and user allocation scheme (RBPUA) based on a single resource block. Taking RBPUA as a basic module, we propose three joint multi-subchannel power and marine user allocation algorithms. The gradient descent algorithm (GRAD) is used as the reference standard for WAR optimization. The multi-choice knapsack algorithm combined with dynamic programming (MCKP-DP) obtains a WAR optimization result almost equal to that of GRAD. These two NOMA-based solutions are able to improve WAR performance by 7.47% compared with OMA. Due to the high computational complexity of the MCKP-DP, we further propose a DP-based fully polynomial-time approximation algorithm (DP-FPTA). The simulation results show that DP-FPTA can reduce the complexity by 84.3% while achieving an approximate optimized performance of 99.55%. This advantage of realizing the trade-off between performance optimization and complexity meets the requirements of practical low-latency systems.
本文研究基于非正交多址接入(NOMA)的海洋通信场景中的资源优化方案。根据海洋的近海环境,我们首先建立基于朗利 - 赖斯的信道模型。然后,将加权可达速率(WAR)作为优化目标,以有效权衡信息速率和用户公平性。我们的工作引入了一种基于单个资源块的改进型联合功率和用户分配方案(RBPUA)。以RBPUA为基本模块,我们提出了三种联合多子信道功率和海洋用户分配算法。梯度下降算法(GRAD)用作WAR优化的参考标准。结合动态规划的多选择背包算法(MCKP - DP)获得的WAR优化结果几乎与GRAD相同。与正交多址接入(OMA)相比,这两种基于NOMA的解决方案能够将WAR性能提高7.47%。由于MCKP - DP的计算复杂度较高,我们进一步提出了一种基于动态规划的全多项式时间近似算法(DP - FPTA)。仿真结果表明,DP - FPTA可以将复杂度降低84.3%,同时实现约99.55%的近似优化性能。这种在性能优化和复杂度之间实现权衡的优势满足了实际低延迟系统的要求。