Complex Field Network Coding for Multi-Source Multi-Relay Single-Destination UAV Cooperative Surveillance Networks

Xue, Rui; Han, Lu; Chai, Huisi

doi:10.3390/s20061542

Cited by 10 publications

(14 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In such cases, the application that has asked for UAV deployment comes with very specific constraints and requirements and calls for specific optimization models. Reference [ 11 , 12 ] gives two such examples dedicated respectively for three-dimensional measurements and surveillance.…”

Section: Application-driven Uav Based Measurementsmentioning

confidence: 99%

“…Reference [ 12 ] focuses on UAV cooperative surveillance networks and introduces the use of complex field network coding (CFNC) for this application. According to whether there is a direct communication link between any source drone and the destination, the information transfer mechanism at the downlink is set to one of two modes, either mixed or relay transmission, and two corresponding irregular topology structures for CFNC-based networks are proposed.…”

Section: Application-driven Uav Based Measurementsmentioning

confidence: 99%

See 1 more Smart Citation

Optimization and Communication in UAV Networks

Caillouet

Mitton

2020

Sensors

View full text Add to dashboard Cite

Nowadays, Unmanned Aerial Vehicles (UAVs) have received growing popularity in the Internet-of-Things (IoT) which often deploys many sensors in a relatively wide region. Current trends focus on deployment of a single UAV or a swarm of it to generally map an area, perform surveillance, monitoring or rescue operations, collect data from ground sensors or various communicating devices, provide additional computing services close to data producers, etc. Applications are very diverse and call for different features or requirements. But UAV remain low-power battery powered devices that in addition to their mission, must fly and communicate. Thanks to wireless communications, they participate to mobile dynamic networks composed of UAV and ground sensors and thus many challenges have to be addressed to make UAV very efficient. And behind any UAV application, hides an optimization problem. There is still a criterion or multiple ones to optimize such as flying time, energy consumption, number of UAV, quantity of data to send/receive, etc

show abstract

Section: Application-driven Uav Based Measurementsmentioning

confidence: 99%

Section: Application-driven Uav Based Measurementsmentioning

confidence: 99%

Optimization and Communication in UAV Networks

Caillouet

Mitton

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Compared to conventional terrestrial infrastructures, the advantages of UAVs include high flexibility, low cost and ease of deployment [7] [8], which makes them preferable when setting up wireless communications for monitoring missions. UAV swarms are thought to be a prospective application for wireless links due to their multiple application scenes such as forest fire prevention, traffic surveillance, precision agriculture, inspection for protective construction [3], and the delivery of commodities. Investigation and surveillance are important applications for UAVs.…”

Section: Introductionmentioning

confidence: 99%

“…CFNC obtains throughput as high as 1/2 symbol per source per channel use (sym/S/CU) [16], which is higher than other network coding schemes, such as physical-layer network coding (PNC), random linear network coding (RLNC) and Galois field network coding (GFNC). CFNC has been adopted in many scenarios for wireless communications for high throughput, such as UAVs [3], wireless backhaul [14], wireless sensor networks [15]. However, the reliability performance of CFNC is poor while achieving high throughput.…”

Section: Introductionmentioning

confidence: 99%

Precoding-based Complex Field Network Coding Strategy for Multi-Source UAV Cooperative System

Zhao

Xue

Jiang

2022

Preprint

View full text Add to dashboard Cite

Employing multiple UAVs as a swarm for investigation and surveillance can complete more complex missions. Since novel sensors equipped, vast amounts of data are continually generated as the increasing number of UAVs. Therefore, the process of multi-source data and the valuable information from the multi-source data is of significant importance. These data formats vary from traditional data to dynamic data with the characteristic of multi-source. Considering that vast amounts of multi-source data from UAV swarm require higher throughput performance of transmission schemes, complex field network coding (CFNC) is selected for UAV cooperative system. However, adverse effects like inter-user interference of fading channels will limit the reliability performance of UAV cooperative system. To improve the reliability performance and recover more accurate valuable information, we propose a precoding-based CFNC strategy for multi-source UAV cooperative system. The proposed transmission scheme processes data through precoding matrix, which is obtained by the transformation of channel state matrix. Compared to conventional CFNC schemes, precoding-based CFNC scheme improves the accuracy of detections. Through theoretical analysis and experimental results, the precoding-based CFNC transmission scheme not only maintains high throughput, but also recover more valuable information and achieves better reliability performance.

show abstract

“…Due to their ease of deployment, low cost, high mobility and ability to hover [5], [6] compared to conventional terrestrial infrastructure, UAVs are better equipped to set up wireless links with favorable channel conditions. They are considered a promising vector of support for wireless communications for a great number of practical applications, such as security and surveillance, the real-time monitoring of road traffic, provision of wireless coverage, sensor data collection, relays for ad hoc net-works [3], search and rescue operations, the delivery of goods, data rate enhancement [4], precision agriculture, and civil infrastructure inspection [7], as shown in Figure 1. However, it is difficult to complete complex surveillance missions in remote areas because of the intricate and uncertain circumstances that restrict the ability of UAV to work over larger areas.…”

Section: Introductionmentioning

confidence: 99%

Information Transmission Schemes Based on Adaptive Coded Modulation for UAV Surveillance Systems With Satellite Relays

Xue

Zhao

Tang³

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

To expand their search range, unmanned aerial vehicles (UAVs) used for surveillance employ satellites as relays to forward monitoring data to the UAV's command and control centers. With updated sensors, the amount of UAV detection data increases sharply, and the demand for bandwidth and transmission rates increase continuously. In this paper, the Ka-band is introduced to the satellite system as a solution instead of the Ku, C and other bands. Highly robust constant coded modulations (CCMs), such as the binary low-density parity-check (LDPC) and the coded quadrature phase shift keying (QPSK) are adopted to handle poor channel conditions caused by rain attenuation, which lead to a waste of spectral efficiency, especially in poor weather conditions; Adaptive Coded Modulation (ACM) can relieve the problems detailed above. Aiming at the problem mentioned above, we have proposed two different transmission schemes for two typical scenarios, including high quality of service (QoS) and high throughput service. The first is the so called automatic repeat request (ARQ)+ACM (target bit error rate (BER) algorithm) for high QoS, which means ARQ and ACM are employed by UAV-satellite links and satellite-center links, respectively. The second, denoted as coded cooperation (CC)+ACM (the maximum throughput algorithm) for high throughput services, designates that CC is employed for UAV-satellite links and ACM is employed for satellite-center links. Simulation results show that the ARQ+ACM scheme achieves higher spectral efficiency than CCM in cases that keep the BER below 5 10 − , and the CC+ACM scheme attains 3 to 7.5 times the spectral efficiency of CCM.

show abstract

Complex Field Network Coding for Multi-Source Multi-Relay Single-Destination UAV Cooperative Surveillance Networks

Cited by 10 publications

References 32 publications

Optimization and Communication in UAV Networks

Optimization and Communication in UAV Networks

Precoding-based Complex Field Network Coding Strategy for Multi-Source UAV Cooperative System

Information Transmission Schemes Based on Adaptive Coded Modulation for UAV Surveillance Systems With Satellite Relays

Contact Info

Product

Resources

About