Enhanced multi-parameter cognitive architecture for future wireless communications

Gao, Feifei; Zhang, Kaiqing

doi:10.1109/mcom.2015.7158270

Cited by 17 publications

(16 citation statements)

References 15 publications

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“…In essence, there are L(L − 1) possibilities of errors that are intertwined to exacerbate the complexity in threshold calculation. In [7], closed-form thresholds were determined by assuming the same cost for all the errors. Note that a number of parameters (power mode) are required a priori, including the number of power levels, the value of powers, the noise power, and the prior probability of hypotheses.…”

Section: A Rf Landscape Perceptionmentioning

confidence: 99%

“…Note that a number of parameters (power mode) are required a priori, including the number of power levels, the value of powers, the noise power, and the prior probability of hypotheses. In theory, this problem can be solved by labelling the collected samples from different PU power levels [7]. However, this is not very practical in reality.…”

Section: A Rf Landscape Perceptionmentioning

confidence: 99%

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Spectrum Intelligent Radio: Technology, Development, and Future Trends

et al. 2020

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The advent of Industry 4.0 with massive connectivity places significant strains on the current spectrum resources, and challenges the industry and regulators to respond promptly with new disruptive spectrum management strategies. The current radio development, with certain elements of intelligence, is nowhere near showing an agile response to the complex radio environments. Following the line of intelligence, we propose to classify spectrum intelligent radio into three streams: classical signal processing, machine learning (ML), and contextual adaptation. We focus on the ML approach, and propose a new intelligent radio architecture with three hierarchical forms: perception, understanding, and reasoning. The proposed perception method achieves fully blind multi-level spectrum sensing. The understanding method accurately predicts the primary users' coverage across a large area, and the reasoning method performs a near-optimal idle channel selection. Opportunities, challenges, and future visions are also discussed for the realization of a fully intelligent radio.

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Section: A Rf Landscape Perceptionmentioning

confidence: 99%

Section: A Rf Landscape Perceptionmentioning

confidence: 99%

Spectrum Intelligent Radio: Technology, Development, and Future Trends

et al. 2020

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“…The fifth generation of cellular networks are not only envisioned to enhance the mobile broadband services, but also to support massive number of connections within the Internetof-Things (IoT) paradigm as well as to provide ultra-reliable low-latency communications for some services [1], [2]. Such new requirements impose unprecedented challenges that cannot be fulfilled via the conventional orthogonal multiple-access (OMA) with centralized base station controlled communications.…”

Section: A Motivation and Literature Reviewmentioning

confidence: 99%

Cooperative HARQ-Assisted NOMA Scheme in Large-Scale D2D Networks

Shi

ElSawy

et al. 2018

IEEE Trans. Commun.

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This paper develops an interference aware design for cooperative hybrid automatic repeat request (HARQ) assisted non-orthogonal multiple access (NOMA) scheme for large-scale device-to-device (D2D) networks. Specifically, interference aware rate selection and power allocation are considered to maximize long term average throughput (LTAT) and area spectral efficiency (ASE). The design framework is based on stochastic geometry that jointly accounts for the spatial interference correlation at the NOMA receivers as well as the temporal interference correlation across HARQ transmissions. It is found that ignoring the effect of the aggregate interference, or overlooking the spatial and temporal correlation in interference, highly overestimates the NOMA performance and produces misleading design insights. An interference oblivious selection for the power and/or transmission rates leads to violating the network outage constraints. To this end, the results demonstrate the effectiveness of NOMA transmission and manifest the importance of the cooperative HARQ to combat the negative effect of the network aggregate interference. For instance, comparing to the non-cooperative HARQ assisted NOMA, the proposed scheme can yield an outage probability reduction by 32%. Furthermore, an interference aware optimal design that maximizes the LTAT given outage constraints leads to 47% throughput improvement over HARQ-assisted orthogonal multiple access (OMA) scheme.

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“…An architecture for managing multi-parameter based cognition is proposed in [5]. The key idea is to structure the various parameters at different protocol layers in order to reduce the actual number of parameters that need to be tuned during and by the cognitive operation.…”

Section: Related Workmentioning

confidence: 99%

Network management issues in military Cognitive Radio Networks

Bräysy

Tuukkanen

Couturier

et al. 2017

2017 International Conference on Military Communications and Information Systems (ICMCIS)

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Abstract-Cognitive Radio (CR) was designed to support flexible spectrum usage by adding spectrum sensing facilities and decision making logic to the radio devices. Cognitive Radio Network (CRN) is an extension of the CR concept to enable holistic end-to-end optimization of the network operation and services. We discuss CRN management issues in the context of military and tactical operation environments, where the key feature is the temporal nature of the network installations. Our special interest is in the wireless ad hoc network solutions. The network lifetime may extend from just hours to several days. The limited lifetime of the networks makes it both possible and necessary to define the management functionalities with respect to different mission phases. Traditional FCAPS (Fault, Configuration, Administration, Performance, and Security) functions and their required actions are therefore detailed to some level at each operational phase (before, during and after mission). We will emerge the idea that, as the cognitive and autonomous technologies will be developed to operate communication networks and become trustworthy enough to be applied also in tactical context, they will most likely first be applied in the during mission phase. Of course, this phase is also the most critical in the sense that it is here that lives are at stake. To answer this critical issue, the policy management must be seen as an equally critical functionality. It is necessary to develop the interconnection between mission goals and defined policies so that the Cognitive Network Engine (CNE) determining the operational parameters of the network, in all situations provides a reliable and failsafe communication solution to be utilized. 1

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Enhanced multi-parameter cognitive architecture for future wireless communications

Cited by 17 publications

References 15 publications

Spectrum Intelligent Radio: Technology, Development, and Future Trends

Spectrum Intelligent Radio: Technology, Development, and Future Trends

Cooperative HARQ-Assisted NOMA Scheme in Large-Scale D2D Networks

Network management issues in military Cognitive Radio Networks

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