UAV-Assisted Underwater Sensor Networks Using RF and Optical Wireless Links

电信线路 实时计算 计算机科学 自由空间光通信 水下 电子工程 计算机网络 频道(广播) 传输(电信) 误码率 数据传输 光通信 工程类 电信 海洋学 地质学
作者
Pouya Agheli,Hamzeh Beyranvand,Mohammad Javad Emadi
出处
期刊:Journal of Lightwave Technology [Institute of Electrical and Electronics Engineers]
卷期号:39 (22): 7070-7082 被引量:26
标识
DOI:10.1109/jlt.2021.3114163
摘要

Underwater sensor networks (UWSNs) are of interest to gather data from underwater sensor nodes (SNs) and deliver information to a terrestrial access point (AP) in the uplink transmission, and transfer data from the AP to the SNs in the downlink transmission. In this paper, we investigate a triple-hop UWSN in which autonomous underwater vehicle (AUV) and unmanned aerial vehicle (UAV) relays enable end-to-end communications between the SNs and the AP. It is assumed that the SN–AUV, AUV–UAV, and UAV–AP links are deployed by underwater optical communication (UWOC), free-space optic (FSO), and radio frequency (RF) technologies, respectively. Two scenarios are proposed for the FSO uplink and downlink transmissions between the AUV and the UAV, subject to water-to-air and air-to-water interface impacts; direct transmission scenario (DTS) and retro-reflection scenario (RRS). After providing the channel models and their statistics, the UWSN's outage probability and average bit error rate (BER) are computed. Besides, a tracking procedure is proposed to set up reliable and stable AUV– UAV FSO communications. Through numerical results, it is concluded that the RSS scheme outperforms the DTS one with about 200% (32%) and 80% (17%) better outage probability (average BER) in the uplink and downlink, respectively. It is also shown that the tracking procedure provides on average 480% and 170% improvements in the network's outage probability and average BER, respectively, compared to poorly aligned FSO conditions. The results are verified by applying Monte-Carlo simulations.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
liuliu完成签到,获得积分10
刚刚
小小发布了新的文献求助10
1秒前
xxxgggppp发布了新的文献求助10
1秒前
1秒前
1秒前
清新的寻菡完成签到,获得积分10
2秒前
2秒前
dengty发布了新的文献求助50
2秒前
2秒前
2秒前
3秒前
3秒前
3秒前
小海豚发布了新的文献求助10
3秒前
充电宝应助Sharon采纳,获得10
3秒前
4秒前
小二郎应助鱼哲哲采纳,获得10
4秒前
852应助zy采纳,获得10
4秒前
lx84317261给wangzhen005822的求助进行了留言
4秒前
5秒前
研友_VZG7GZ应助Z170采纳,获得10
5秒前
牛肉面发布了新的文献求助10
6秒前
6秒前
科研通AI6.2应助酷炫柔采纳,获得10
6秒前
可可完成签到,获得积分10
6秒前
大个应助rf采纳,获得10
6秒前
6秒前
Corn完成签到,获得积分10
6秒前
搜集达人应助星河采纳,获得10
6秒前
7秒前
7秒前
7秒前
8秒前
牟牟发布了新的文献求助10
8秒前
靓丽行天发布了新的文献求助10
8秒前
8秒前
8秒前
peng发布了新的文献求助10
8秒前
志灰灰完成签到,获得积分10
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Kinesiophobia : a new view of chronic pain behavior 2000
Research for Social Workers 1000
Psychology and Work Today 800
Mastering New Drug Applications: A Step-by-Step Guide (Mastering the FDA Approval Process Book 1) 800
Kinesiophobia : a new view of chronic pain behavior 600
Signals, Systems, and Signal Processing 510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5896718
求助须知:如何正确求助?哪些是违规求助? 6712271
关于积分的说明 15735218
捐赠科研通 5019244
什么是DOI,文献DOI怎么找? 2702929
邀请新用户注册赠送积分活动 1649710
关于科研通互助平台的介绍 1598738