写作系列之: Introduction, related works, contribution

背景: 问题很重要

这一段的大意:
UAV优势很多，得到了广泛的应用，对 data rate (你要优化什么就是什么) 提出了很高的要求, 所以你研究的问题很重要
   Unmanned aerial vehicle (UAV) is an emerging facility which has been effectively applied in military, public, and civil applications [2]. According to BI Intelligence’s report, more than 29 million UAVs are expected to be put into use in 2021 [3]. Among these applications, the use of UAV to perform sensing has been of particular interest owing to its significant advantages, such as the ability of on-demand flexible deployment, larger service coverage compared with the conventional fixed sensor nodes, and additional design degrees of freedom by exploiting its high UAV mobility [4], [5]. Recently, UAVs with cameras or sensors have entered the daily lives to execute various sensing tasks, e.g. air quality index monitoring [6], autonomous target detection [7], precision agriculture [8], and water stress quantification [9]. The sensory data needs to be transmitted to the server for further processing, thereby posing high uplink rate requirement on the UAV communication network.

文献综述部分

这一段可以说哪一些内容:
一是，可以引用一些和你采用的技术((比如 NOMA)或研究的场景(UAV communication networks…)相关的文献，格式是: In …, the authors proposed…

二是你为什么研究这个问题, 也就是你的motivation

第1段: 对场景做一个简单的交代
因为提出了 single cell cellular network, 因为处于cell edge 的用户 SNR 较低, 因此提出了 UAV relay
   Driven by such real-time requirements, the upcoming network is committed to support UAV communication, where the collected data can be effectively transmitted [10]. Unlike the conventional ad hoc sensor network, the sensory data can be transmitted to the networks directly in a centralized way [11], which can greatly improve the quality of UAV communications [12]. In this paper, we study a single cell cellular network with a number of cellular users (CUs) and UAVs, where each UAV moves along a pre-determined trajectory to collect data, and then uploads these data to the base station (BS). However, some UAVs may locate at the cell edge, and the signal to noise ration (SNR) of their communication links to the BS are low. To provide a satisfactory data rate, we enable these UAVs to transmit the sensory data to the UAVs with high SNR for the communication link to the BS as relay. The relaying UAVs save the received data in their caches and upload the data to the BS in the following time slots as described in [13]. Specifically, the UAV transmissions can be supported by two basic modes, namely UAV-to-network (U2N) and UAV-to-UAV (U2U) transmissions. The overlay U2N transmission offers direct link from UAVs with high SNR to the BS, and thus provides a high data rate [14], [15]. In U2U transmission, a UAV with low SNR for the U2N link can set up direct communication links to the high U2N SNR UAVs bypassing the network infrastructure and share the spectrum with the U2N and CU transmissions, which provides a spectrum efficient method to support the data relaying process [16].

第2段: 你为什么研究这个问题，也就是你研究这个问题的 motivation 是什么:
比如因为信道重叠, 所以存在干扰, 因此研究频谱分配(spectrum allocation)很重要.
   Due to the high mobility and long transmission distance of the sensing UAVs, it is not trivial to address the following issues. Firstly, since the U2U transmissions underlay the spectrum resources of the U2N and CU transmissions, the U2N and CU transmissions may be interfered by the U2U transmissions when sharing the same subchannel. Correspondingly, the U2U transmissions are also interfered by the U2N, CU, and U2U links on the same subchannel. Moreover, different channel models are utilized for the U2N, U2U, and CU transmissions due to the different characteristics of air-to-ground, air-to-air, and ground-to-ground communications. Therefore, an efficient spectrum allocation algorithm is required to manage the mutual interference. Secondly, to complete the data collection of the sensing tasks given time requirements, the UAV speed optimization is necessary. Thirdly, to avoid the data loss and provide a relatively high data rate for the UAVs with low SNR for the link to the BS, an efficient communication method is essential. In summary, the resource allocation schemes, UAV speed, and UAV transmission protocol should be properly designed to support the UAV to-X communications.

第3段: 引用一些和你采用的方法或研究的问题相关的文献

  In the literature, some works on the UAV communication network have been studied, in which UAVs work as relays or BSs. In [17], the authors studied a 3-D UAV-BS placement to maximize the number of covered users with different quality-of-service requirements. In [18], the deployment of a UAV as a flying BS used to provide the fly wireless communications was analyzed. In [19], the UAV was proposed to work as a mobile BS which collected data from fixed sensor nodes on the ground. A trajectory design and power control algorithm was introduced for a UAV relay network in [20] to improve the reliability of transmissions. The work [21] investigated the scenario where UAVs served as flying BSs to provide wireless service to ground users, and optimized the downlink data rate and UAV hover duration. In [22],the authors proposed a hybrid network architecture with the use of UAV as a BS, which flies cyclically along the cell edge to serve the cell-edge users. Unlike most of the previous works which typically treat UAVs as relays or BSs, in our work the UAVs that relay the data from other UAVs also have their own sensing tasks, i.e. we consider the UAVs as flying mobile terminals in the UAV sensing network.

主要贡献

关于贡献部分我单独写了一个博客，请见 写作系列之:贡献
  The main contributions of this paper can be summarized below.
(1) We construct a UAV-to-X communication network, where the UAVs can either upload the collected data via U2N communications directly or send to other UAVs by U2U communications. A cooperative UAV sense-and-send protocol is proposed to enable these communications.
(2) We formulate a joint subchannel allocation and UAV speed optimization problem to maximize the uplink sum-rate of the network. We then prove that the problem is NP-hard, and decompose it into three sub-problems: U2N and CU subchannel allocation, U2U subchannel allocation, and UAV speed optimization. An efficient iterative subchannel allocation and speed optimization algorithm (ISASOA) is proposed to solve the sub-problems iteratively.
(3) We compare the proposed algorithm with a greedy algorithm in simulations. The results show that the proposed ISASOA outperforms the greedy algorithm by about 10% in terms of the uplink sum-rate.
The rest of this paper is organized as follows. In Section II, we present the system model of the UAV sensing network.
A cooperative UAV sense-and-send protocol is proposed in Section III for the data collection and UAV-to-X communications. In Section IV, we formulate the uplink sum-rate maximization problem by optimizing the subchannel allocation and UAV speed jointly. The ISASOA is proposed in Section V, followed by the corresponding analysis. Simulation results are presented in Section VI, and finally we conclude the paper in Section VII.

节选自 Cellular UAV-to-X Communications: Design and Optimization for Multi-UAV Networks
Zhang S , Zhang H , Di B , et al. Cellular UAV-to-X Communications: Design and Optimization for Multi-UAV Networks[J]. IEEE Transactions on Wireless Communications, 2018, PP(99).