Cognitive Resource Management: For All Wireless Access Layers

Marojevic, Vuk; Gomez, Ismael; Gelonch, A.

doi:10.1109/mvt.2012.2190190

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…Network providers can expand the existing infrastructure in support of UAS communications. We envision an integrated solution, where a wireless network provider leases infrastructure resources to, for example, terrestrial cellular service providers and UASs; similarly, an radio resource provider manages access to RF spectrum [16].…”

Section: Spectrum Management Discussionmentioning

confidence: 99%

Waveform and spectrum management for unmanned aerial systems beyond 2025

Kakar

Marojevic

2017

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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The application domains of civilian unmanned aerial systems (UASs) include agriculture, exploration, transportation, and entertainment. The expected growth of the UAS industry brings along new challenges: Unmanned aerial vehicle (UAV) flight control signaling requires low throughput, but extremely high reliability, whereas the data rate for payload data can be significant. This paper develops UAV number projections and concludes that small and micro UAVs will dominate the US airspace with accelerated growth between 2028 and 2032. We analyze the orthogonal frequency division multiplexing (OFDM) waveform because it can provide the much needed flexibility, spectral efficiency, and, potentially, reliability and derive suitable OFDM waveform parameters as a function of UAV flight characteristics. OFDM also lends itself to agile spectrum access. Based on our UAV growth predictions, we conclude that dynamic spectrum access is needed and discuss the applicability of spectrum sharing techniques for future UAS communications.

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Section: Spectrum Management Discussionmentioning

confidence: 99%

Waveform and spectrum management for unmanned aerial systems beyond 2025

Kakar

Marojevic

2017

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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“…We consider that the processing power of the BS is a shared and limited resource [12]. Different p Rx,max constraints are imposed on the flexible SNR strategy for this analysis: 14, 11.5 and 10.002 W. When each UL decoder needs only one iteration, the per‐user and total power for processing at the BS become 250 mW (Table 1) and 10 W ( p Rx,min ).…”

Section: Multi‐user Analysismentioning

confidence: 99%

Analysis of wireless transceiver power tradeoffs for green communications

2018

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The energy optimisation problem of wireless communications as a power consumption tradeoff between the transmitter and receiver is considered. The goal is finding the right balance between the transmission power and the amount of digital signal processing at the receiver. The problem then consists of deriving the optimal signal-to-noise ratio. Receiver cost functions from real implementations are defined and the constrained optimisation problem for single and multiuser links is solved. The numerical analysis shows that there is an optimal ratio between transmission power and signal processing which can lead to a 30% power reduction for noise limited systems.

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“…In our research we assume that wireless infrastructure customers, typically MVNOs, lease resources as needed or periodically from an IaaS provider to build their networks [5]. These virtualized wireless networks will be tailored to the services they provide by using virtual wireless network components as their building blocks, rather than dealing directly with the computing, spectrum, remote radio heads (RRHs), antennas, fronthaul/backhaul, and other physical resources.…”

Section: Introductionmentioning

confidence: 99%

“…The business model behind the Cloud radio access network (C-RAN) is based on the Infrastructure-as-a-Service (IaaS) model. A pool of physical resources, which include antenna sites, networking components and processors, is virtualized and offered to mobile virtual network operators (MVNOs) to build their networks as most suitable for the services they intend to offer [5]. As technology evolves, MVNOs will be able to load software images of wireless networks that can be dynamically customized and adapted to the changing operational conditions.…”

Section: Introductionmentioning

confidence: 99%

Open Orchestration Cloud Radio Access Network (OOCRAN) Testbed

Floriach-Pigem¹,

Xercavins-Torregrosa²,

Marojevic

et al. 2017

Companion Proceedings of The10th International Conference on Utility and Cloud Computing

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The 1 Cloud radio access network (C-RAN) offers a revolutionary approach to cellular network deployment, management and evolution. Advances in software-defined radio (SDR) and networking technology, moreover, enable delivering softwaredefined everything through the Cloud. Resources will be pooled and dynamically allocated leveraging abstraction, virtualization, and consolidation techniques; processes will be automated using common application programming interfaces; and network functions and services will be programmatically provided through an orchestrator. OOCRAN, oocran.dynu.com, is a software framework that is based on the NFV MANO architecture proposed by ETSI. It provides an orchestration layer for the entire wireless infrastructure, including hardware, software, spectrum, fronthaul and backhaul. OOCRAN extends existing NFV management frameworks by incorporating the radio communications layers and their management dependencies. The wireless infrastructure provider can then dynamically provision virtualized wireless networks to wireless service providers. The testbed's physical infrastructure is built around a computing cluster that executes open-source SDR libraries and connects to SDR-based remote radio heads. We demonstrate the operation of OOCRAN and discuss the temporal implications of dynamic LTE small cell network deployments.

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Cognitive Resource Management: For All Wireless Access Layers

Cited by 6 publications

References 10 publications

Waveform and spectrum management for unmanned aerial systems beyond 2025

Waveform and spectrum management for unmanned aerial systems beyond 2025

Analysis of wireless transceiver power tradeoffs for green communications

Open Orchestration Cloud Radio Access Network (OOCRAN) Testbed

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