Using MIMO Techniques to Enhance Communication Among Static and Mobile Nodes in Wireless Sensor Networks

Marinho, Marco A. M.; Freitas, Edison Pignaton de; Costa, João Paulo; Almeida, André L. F. de; Sousa, Rafael T. de

doi:10.1109/aina.2013.107

Cited by 6 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although wireless power transfer (WPT), energy harvesting (EH), and energy‐efficient communication techniques have been employed to address this issue, IoT services are still looking for fully autonomous things without power constraints. The green IoT can be obtained using UAVs infrastructure and a new concept called the IoMIMO, which is still in its infancy stages, as IoT connectivity has constraints and requirements that are totally different from broadband connections (Cetinkaya et al, 2020; Huang et al, 2021; Marinho et al, 2013a; Taştan & İlhan, 2021; Yilmaz & Denizer, 2020).…”

Section: Future Research Directions For Fanetsmentioning

confidence: 99%

“…In other words, aerial object detection is almost impossible due to the very small size of the objects, variation in surrounding illumination, occlusion and the shadowing of objects by trees and high buildings. (Cetinkaya et al, 2020;Huang et al, 2021;Marinho et al, 2013a;Taştan & İlhan, 2021;Yilmaz & Denizer, 2020).…”

Section: Future Research Directions For Fanetsmentioning

confidence: 99%

See 1 more Smart Citation

A systematic literature review of flying ad hoc networks: State‐of‐the‐art, challenges, and perspectives

Pasandideh

Costa

Kunst

et al. 2023

Journal of Field Robotics

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs), also known as drones, communicate, collaborate, and form flying ad hoc networks (FANETs) to perform many different missions, ranging from delivery tasks to agriculture applications. Recently, FANETs have been integrated with different technologies, such as artificial intelligence (AI), virtual reality, and Internet of Things. Such new avenues for the use of UAVs directly impact the research on FANETs and cause some major challenges, such as security and physical layer issues, resource management, and UAV positioning issues that need to be addressed. Several researchers have been working for the last few years to propose AI and machine learning (ML)‐based solutions for different use cases in UAV‐based networks. They present the limitations of the existing research work and highlight some possible future works on FANETs. However, exhibiting the trends in the UAV research papers in a quantitative manner is still required to motivate researchers to rethink the research on FANETs. Therefore, this study covers more than 170 scientific publications extracted from five trusted academic databases published from 2013 to 2021 to provide a thorough overview of the main research and development statistics in the area of FANETs, the open challenges existing in this area and the ML‐based solutions to solve these challenges. In addition, the investigation of emerging technologies integrated with FANETs, as well as the simulation tools employed for evaluating FANETs' performance are discussed. Moreover, the future research directions in the area of FANETs are considered within a prospective vision discussion.

show abstract

Section: Future Research Directions For Fanetsmentioning

confidence: 99%

Section: Future Research Directions For Fanetsmentioning

confidence: 99%

A systematic literature review of flying ad hoc networks: State‐of‐the‐art, challenges, and perspectives

Pasandideh

Costa

Kunst

et al. 2023

Journal of Field Robotics

View full text Add to dashboard Cite

show abstract

“…Results obtained in this work showed that cooperative MIMO is only advantageous when long distances are involved. Nevertheless, the advantages of cooperative MIMO are not restricted to energy efficiency, the faster data rates achievable with MIMO system allow the interaction between fast moving mobile as well as traditional static nodes [10] [11], also, antenna array techniques such as beam forming or direction of arrival estimation can be employed.…”

Section: Introductionmentioning

confidence: 99%

Applying Cooperative MIMO Technique in an Adaptive Routing Mechanism for Wireless Sensor Networks

Marinho

Freitas

Costa

et al. 2013

2013 IEEE Conference on Wireless Sensor (ICWISE)

View full text Add to dashboard Cite

Energy consumption in Wireless Sensor Networks (WSNs) is a limiting factor that hinders the application of such networks into solving a broader set of problems. Various ways of saving energy have been proposed, from energy efficient processing to power aware cluster organization. With communication between nodes being responsible for a large part of the energetic demand, energy efficient methods of communication have been proposed, with multi-hop communication being a wide used technique, capable of minimizing energy consumption and spreading it amongst the network. However, multi-hop is not always more efficient and is prone to a high delay, due to the decode and forward mechanism usually employed. In this paper a cooperative MIMO technique is studied, its energy consumption analyzed, and a mechanism for integrating it in existing WSNs and allowing its coexistence with multi-hop communication is suggested. Energy efficiency, packet delivery delay and packet loss ratios are analyzed and the results compared to standard WSNs.

show abstract

“…Massive multiple-input multiple-output (MIMO) is a key technology that dramatically improves the spectral efficiency of 5G wireless systems, by leveraging a large number of GBS antennas to serve a small number of users. Due to its enormous beamforming and full spatial multiplexing gains, massive MIMO has been applied recently to support UAVs for resolving the aforementioned aerial-ground interference and 3D coverage issues [2]- [4]. As compared to traditional two-dimensional (2D) beamforming towards the ground only, massive MIMO with 3D beamforming provides finer-grained angle resolutions in both azimuth and elevation dimensions.…”

Section: Introductionmentioning

confidence: 99%

Massive MIMO for Cellular-Connected UAV: Challenges and Promising Solutions

Huang

Lü

et al. 2020

Preprint

View full text Add to dashboard Cite

Massive multiple-input multiple-output (MIMO) is a promising technology for enabling cellular-connected unmanned aerial vehicle (UAV) communications in the future. Equipped with full-dimensional large arrays, ground base stations (GBSs) can apply adaptive fine-grained three-dimensional (3D) beamforming to mitigate the strong interference between high-altitude UAVs and low-altitude terrestrial users, thus significantly enhancing the network spectral efficiency. However, the performance gain of massive MIMO critically depends on the accurate channel state information (CSI) of both UAVs and terrestrial users at the GBSs, which is practically difficult to achieve due to UAVinduced pilot contamination and UAV's high mobility in 3D. Moreover, the increasingly popular applications relying on a large group of coordinated UAVs or UAV swarm as well as the practical hybrid GBS beamforming architecture for massive MIMO further complicate the pilot contamination and channel/beam tracking problems. In this article, we provide an overview of the above challenging issues, propose new solutions to cope with them, and discuss about promising directions for future research. Preliminary simulation results are also provided to validate the effectiveness of proposed solutions.

show abstract

Using MIMO Techniques to Enhance Communication Among Static and Mobile Nodes in Wireless Sensor Networks

Cited by 6 publications

References 7 publications

A systematic literature review of flying ad hoc networks: State‐of‐the‐art, challenges, and perspectives

A systematic literature review of flying ad hoc networks: State‐of‐the‐art, challenges, and perspectives

Applying Cooperative MIMO Technique in an Adaptive Routing Mechanism for Wireless Sensor Networks

Massive MIMO for Cellular-Connected UAV: Challenges and Promising Solutions

Contact Info

Product

Resources

About