IEEE 5G Spectrum Sharing Challenge: A Practical Evaluation of Learning and Feedback

Rajendran, Sreeraj; Bergh, Bertold Van den; Vermeulen, Tom; Pollin, Sofie

doi:10.1109/mcom.2016.1600209rp

Cited by 14 publications

(8 citation statements)

References 8 publications

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“…With the fast development of 4/5‐Generation (4/5G) wireless‐communications and digital‐television‐ broadcasting (DTV) applications, dual/multi‐band circuits, and systems with strict requirements in terms of compact size, low‐cost, and high immunity to the environmental noise and electromagnetic interference are becoming more and more important . In particular, they may be very desired for commercially‐exploited bands, such as the Global System for Mobile Communications (GSM) bands at 0.9/1.8 GHz, as well as the global positioning system (GPS) and wireless local area network (WLAN) bands at 1.57/2.45 GHz.…”

Section: Introductionmentioning

confidence: 99%

Compact dual‐band single‐ended‐to‐balanced power dividers with open/short‐ended stubs

Feng

Wang

Shi

et al. 2019

Int J RF Microw Comput Aided Eng

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In this article, two novel topologies of compact-size dual-band single-ended-tobalanced power dividers that are loaded with open-and short-ended stubs are presented.Quarter-wavelength open-ended stubs and half-wavelength short-ended stubs are respectively exploited in the proposed dual-band power-divider configurations to incorporate the dual-band functionality into them for flexibly-adjustable dual-frequency-ratio specifications. Each engineered five-port power-divider circuit features high in-band input/output power-matching levels, high in-band powerisolation levels between the two differential-mode outputs, and high commonmode-rejection levels in a broad spectral range. Two microstrip prototypes designed at 0.9/1.8 GHz (GSM bands) and 1.57/2.45 GHz (GPS and WLAN bands) are constructed and characterized for experimental-demonstration purposes.

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Section: Introductionmentioning

confidence: 99%

Compact dual‐band single‐ended‐to‐balanced power dividers with open/short‐ended stubs

Feng

Wang

Shi

et al. 2019

Int J RF Microw Comput Aided Eng

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“…In CRNs, CR users / SUs can opportunistically access the spectrum without affecting the transmission of legitimate users / PUs [5]. CR is believed to be a key technology to address spectrum demands in NGNs [4,21]. The key of CR lies in self-organizing networks and awareness of the environment.…”

Section: Cognitive Radio Overviewmentioning

confidence: 99%

“…NGNs place a focus on learning and feedback information about the environment in cognitive IoT systems by bringing up cooperation of secondary IoT-nodes as an essential part of the distributed learning process [4]. Various learning schemes can be used in the distributed CSS process like incremental [51], consensus [52], diffusionbased [53], etc.…”

Section: Cooperation and Learningmentioning

confidence: 99%

“…Keeping pace with spectrum demands will require new technologies that can offer acceptable intercommunication between IoT nodes. In order to address the spectrum scarcity issue, cognitive radio (CR) has drawn drastic attention as a potential technology for future IoT systems [3,4]. The principle of CR networks (CRNs) lies in identifying additional frequency beings on the same frequency spectrum band with the main spectrum users without disturbing their communication [5].…”

Section: Introductionmentioning

confidence: 99%

“…The nature of IoT systems is distributed [3]. In addition to this, IoT networks place focus on learning and feedback information about the environment [4]. Therefore, distributed approach tends to be more favorable in the IoT scenario.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Learning-Based Cooperative Spectrum Sensing for Cognitive Internet of Things Systems

Gharib¹

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The emerge of Internet of Things (IoT) brings up revolutionary changes to the field of wireless communications. Providing connection to billions of IoT devices together with challenging IoT environments lead to the need of new technologies in order to fulfill IoT spectrum demands. Cognitive radio (CR) technology can be seen as one of the prominent solutions to the spectrum scarcity issue in IoT, where multiband cooperative spectrum sensing (CSS) is the key. In this thesis, we consider heterogeneous distributed learning-based CR networks (CRNs). Focus is given to learning approaches named as incremental, consensus, and diffusion. We perform a comparative study to investigate which one of them best fits cognitive IoT demands. Simulation results are performed illustrating potentials of diffusion and consensus algorithms and disadvantages of incremental for cognitive IoT systems. Lack of centralized control, increase in number of devices, and dynamic environments place a room for lots of challenges in the CSS process. Conventional CSS techniques have to be improved in order to fulfill sophisticated IoT requirements. One of the main challenges is cooperative secondary users' (SUs') scheduling to sense a subset of channels. To overcome the aforementioned challenge, in this thesis, we propose a novel multi-band CSS scheme, named as heterogeneous multi-band multiuser CSS (HM2CSS). The proposed scheme allows heterogeneous SUs to sense multiple channels and works by selecting cooperative SUs in two stages. Only SUs owning different information about channels are chosen to be cooperative. This is done by selecting leaders for each channel in the first stage and corresponding cooperative SUs in the second stage. Careful choice of leaders reflects the selection of cooperative SUs and hence, improves system performance. Then, diffusion learning algorithm is used to exchange locally sensed information among cooperative SUs for all channels. Further, the decision on the availability of channels is made. Extensive simulation results illustrate that the proposed HM2CSS scheme satisfies the IEEE 802.22 detection performance standard. Detection performance and CRN To my beloved family v Table of Contents vii List of Tables x List of Figures xi Nomenclature xiv List of Tables 4.1 Comparison of incremental, consensus, and diffusion-based learning approaches' characteristics. .

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Asymptotic Analysis for Spectrum-Sharing Systems With TAS/MRC Using Extreme Value Theory: An Overlooked Aspect

et al. 2019

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We investigate the asymptotic behavior for an overlooked aspect of spectrum-sharing systems when the number of transmit antennas n t at the secondary transmitter (ST) grows to infinity. Considering imperfect channel state information (CSI), we apply the transmit antenna selection and the maximal-ratio combining techniques at the ST and the secondary receiver (SR), respectively. First, we obtain the signalto-noise ratio (SNR) distributions received by the SR under perfect and imperfect CSI conditions. Then we show that the SNR distributions are tail-equivalent in the sense that the right tails of the two distributions decay in the same rate as the number of transmit antennas n t grows to infinity. Based on the extreme value theory, when the transmit power of the ST is solely limited by the interference constraint, we show that the limiting SNR at the SR is Fréchet-distributed and the limiting rate scales as log(n t ). When the transmit power of ST is determined by both the maximal transmit power and the interference power constraints, the limiting SNR is Gumbel-distributed and the limiting rate scales as log(log(n t )). We further show that the average rate can be estimated by the corresponding easier-to-obtain outage rate. Numerical results indicate that the derived asymptotic rate expressions represent accurate approximations even when n t is ''not-solarge''. Finally, we study the robustness of the secondary transmissions by analyzing the corresponding average symbol error rates (SER) under general modulation and coding schemes. The findings indicate that the SER is Weibull distributed, when the maximal transmit power and interference power constraints are comparable.INDEX TERMS Spectrum sharing, extreme value theory, rate scaling law, symbol error rate.

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IEEE 5G Spectrum Sharing Challenge: A Practical Evaluation of Learning and Feedback

Cited by 14 publications

References 8 publications

Compact dual‐band single‐ended‐to‐balanced power dividers with open/short‐ended stubs

Compact dual‐band single‐ended‐to‐balanced power dividers with open/short‐ended stubs

Distributed Learning-Based Cooperative Spectrum Sensing for Cognitive Internet of Things Systems

Asymptotic Analysis for Spectrum-Sharing Systems With TAS/MRC Using Extreme Value Theory: An Overlooked Aspect

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