## 1 Introduction  
The rapid development of the blue economy has created the challenge of constructing intelligent ports and terminals. At the same time, this has led to a significant increase in demand for maritime digital services from offshore users. Compared with traditional satellite communications, shore-based base stations (BS) can provide low-cost, high-speed mobile communications services. Recently, several references have applied fifth-generation (5G) and even sixth-generation (6G) emerging technologies, such as massive multiple-input multiple-output (MIMO) [1], internet of vehicles [2], and mobile edge computing [3] to maritime communications. Considering the limited geographic availability of coastal BS, this paper investigates resource allocation schemes based on non-orthogonal multiple access (NOMA) in 5G. Our contribution is to provide high data rate services for more maritime users (ships and islands) in offshore areas with limited-spectrum resources. According to previous research, the maritime communication environment is characterized by instability, sparseness, and the evaporation ducting effect [1]. These features make the marine channel model different from the terrestrial channel model. In particular, due to the scarcity of obstructions at sea, the shadow effect hardly affects signal transmission loss. Furthermore, we can neglect the evaporation ducting phenomenon, since offshore communication takes place within the line of sight (LoS) [4]. The fading of the offshore channel can be divided into large-scale fading and small-scale fading [5]. First, it is essential to establish an appropriate large-scale fading model. The radio communicationssector of the international telecommunication union (ITU-R) model fails to consider sea surface reflection and other complex marine environmental factors [6]. Previous studies [7] have modified the classic Okumura-Hata model by considering the sparse distribution of scattering in the context of vast ocean areas. The Longley-Rice model (also known as ITM) includes marine environment and climate factors and the deployment of antennas [8; 9]. Hence, ITM is able to achieve a more accurate simulation conclusion than the Okumura-Hata model [8]. In addition, it is also necessary for the maritime channel model to consider small-scale fading caused by sea surface fluctuations and atmospheric scattering [10; 11]. The research of [12] shows that the probability distribution function of small-scale fading is closer to a Rice distribution than a Nakagami distribution or Rayleigh distribution. In this paper, we establish a Longley-Rice-based offshore channel model that includes Rice small-scale fading. Joint power and subchannel allocation have always been the focus of resource optimization in NOMA. Some works also refer to subchannel allocation as the allocation scheme for multiplexed users on each resource block (RB). Motivated by recent research, our work takes the weighted achievable rate (WAR) as an objective function to weigh the WAR performance and user fairness [13]. We summarize NOMA-based resource optimization schemes into the following two cases according to the power constraints (user power constraint and system power constraint). Case 1: User power constraint is generally applied to the power control for each user in uplink communications [14; 15]. However, some papers still set user power constraints for downlink communication scenarios [16; 17]. The results of [17] prove that the WAR optimization problem with user constraints is strongly non-deterministic polynomial hard (NP-hard). Therefore, researchers developed a Lagrangian dual algorithm to achieve an approximate optimal result. However, the computational difficulty cannot be ignored in a low-latency actual system. Case 2: The total system power constraint represents the power budget provided by the base station to the communication system. The authors of [18] prove that the equal-weighted achievable rate optimization is solvable by polynomial time.