A Low-Complexity Cyclostationary Spectrum Sensing for Interference Avoidance in Femtocell LTE-A-Based Networks

Tani, Andrea; Fantacci, Romano; Marabissi, Dania

doi:10.1109/tvt.2015.2419877

Cited by 26 publications

(41 citation statements)

References 17 publications

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“…New standards like LDACS aim to improve airtraffic management, offering new pathways for communicating between air and ground stations while ensuring coexistence with legacy L-band systems. While techniques like dynamic spectrum access can enable efficient use of the spectrum Low-complexity CFD [30] Single-cycle CFD [31] Autocorrelation based FD [32] Fig. 9: Comparison of detection accuracy of RL DC frames using different detection techniques.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, we also compare the proposed technique against cyclostationary feature detection (CFD) and autocorrelation based schemes from the literature. A low-complexity cyclostationary technique was proposed for sensing spectrum in a femtocell design for LTE networks [30], while the work in [31] explores a cooperative cyclostationary technique for spectrum sensing in low SNR conditions in generic OFDM systems (which we have adapted to a single-cycle CFD scheme for LDACS). The autocorrelation technique described in [32] relies on the detection of autocorrelation coefficient for spectrum sensing in generic OFDM systems.…”

Section: B Spectrum Sensing Effectivenessmentioning

confidence: 99%

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Efficient Spectrum Sensing for Aeronautical LDACS Using Low-Power Correlators

Shreejith

Mathew

Prasad

et al. 2018

IEEE Trans. VLSI Syst.

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Section: Discussionmentioning

confidence: 99%

Section: B Spectrum Sensing Effectivenessmentioning

confidence: 99%

Efficient Spectrum Sensing for Aeronautical LDACS Using Low-Power Correlators

Shreejith

Mathew

Prasad

et al. 2018

IEEE Trans. VLSI Syst.

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“…SCF is composed of the signal power for one or more cyclic frequencies α k , i.e. the cyclic autocorrelation function (CAF) at τ = 0, which is a variant of the ACF [53]:…”

Section: Cyclostationary Detectorsmentioning

confidence: 99%

“…This study, in addition, considers the effect of log-normal shadowing. As an alternative, to achieve lower computational complexity, instead of SCF, the CAF can be used for a standard signal cyclic frequency and time delay [53]:…”

Section: Cyclostationary Detectorsmentioning

confidence: 99%

Feature Extraction in Local SpectrumSensing for Next Generation CognitiveRadios � A Review

Ivanov

2020

JMM

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In the context of the currently developed networks for the realization of future communications, the concept of Cognitive Radio (CR) has a significant place. Its implementation in modern ultra-dense networks (UDN) requires the development of novel and improved adaptive solutions for the main functionalities of a CR system. This technology has a great potential for solving the significant spectrum underutilization issue which has been established as characteristic for the traditional communication networks and hence, the continual and substantive research efforts in the recent years. The principal challenge for CRs is the optimization of spectrum utilization without creating unwanted interference for the incumbent (primary) users. Thus, a significant portion of the research is directed towards the vital spectrum sensing functionality. This paper reviews the potential uses of CR in UDN as well as the main approaches for modeling of spectrum sensing with respect to signal detection. The review focuses on local spectrum sensing techniques and presents the strengths and weaknesses of their mathematical definition. Specific attention is given to the channel models which are considered in the literature and to what kinds of features are extracted from the received signal to achieve accurate detection.

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“…Indeed, a network controller uses average statistics to assign the BS to each device, and a spectrum manager maintains a database of available and leased open spectrum without the need for spectrum sensing operations. Differently [54] mainly focused on the capability of a secondary access point to detect the activity of the primary macrocell that operates following a carrier aggregation policy. Hence, the small cell performs suitable spectrum sensing based on low complexity cyclostationary detectors to understand to understand in an autonomic manner which frequency bands are available.…”

Section: Long-term Cognitive Approachesmentioning

confidence: 99%

Cognitive Spectrum Sharing: An Enabling Wireless Communication Technology for a Wide Use of Smart Systems

Fantacci

Marabissi

2016

Future Internet

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A smart city is an environment where a pervasive, multi-service network is employed to provide citizens improved living conditions as well as better public safety and security. Advanced communication technologies are essential to achieve this goal. In particular, an efficient and reliable communication network plays a crucial role in providing continue, ubiquitous, and reliable interconnections among users, smart devices, and applications. As a consequence, wireless networking appears as the principal enabling communication technology despite the necessity to face severe challenges to satisfy the needs arising from a smart environment, such as explosive data volume, heterogeneous data traffic, and support of quality of service constraints. An interesting approach for meeting the growing data demand due to smart city applications is to adopt suitable methodologies to improve the usage of all potential spectrum resources. Towards this goal, a very promising solution is represented by the Cognitive Radio technology that enables context-aware capability in order to pursue an efficient use of the available communication resources according to the surrounding environment conditions. In this paper we provide a review of the characteristics, challenges, and solutions of a smart city communication architecture, based on the Cognitive Radio technology, by focusing on two new network paradigms-namely, Heterogeneous Network and Machines-to-Machines communications-that are of special interest to efficiently support smart city applications and services.

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A Low-Complexity Cyclostationary Spectrum Sensing for Interference Avoidance in Femtocell LTE-A-Based Networks

Cited by 26 publications

References 17 publications

Efficient Spectrum Sensing for Aeronautical LDACS Using Low-Power Correlators

Efficient Spectrum Sensing for Aeronautical LDACS Using Low-Power Correlators

Feature Extraction in Local SpectrumSensing for Next Generation CognitiveRadios � A Review

Cognitive Spectrum Sharing: An Enabling Wireless Communication Technology for a Wide Use of Smart Systems

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