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Quantified Dynamic Spectrum Access Paradigm

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Spectrum Access and Management for Cognitive Radio Networks

Part of the book series: Signals and Communication Technology ((SCT))

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Abstract

Quantified Dynamic Spectrum Access (QDSA) paradigm is a generic approach to spectrum sharing between multiple, spatially overlapping, heterogeneous RF systems. QDSA paradigm enables us to address the regulatory, technical, operational, and business impediments to the adoption of dynamic spectrum sharing. As spectrum-access rights are defined and enforced for an individual transceiver in quantified manner, dynamic spectrum-access can be regulated. The QDSA paradigm implies spectrum can be treated as a commodity. It brings in simplicity, precision, and efficiency in terms of spectrum management, operations, and commerce. With spectrum as a quantified resource perspective, the spectrum trade conversation could be on the following lines: I have x units of spectrum right now, I have given y units of spectrum to somebody and have z units of spare spectrum which I can share.

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Notes

  1. 1.

    Without allowing spatial-overlap of wireless services, spectrum sharing may lead to spatial fragmentation of coverage for a wireless service. Furthermore, as discussed in the previous section, imposing a spatial boundary on spectrum sharing leads to suboptimal spectrum sharing.

  2. 2.

    This is to include the use of spectrum by the receive-only systems; for example, radio astronomy telescopes.

  3. 3.

    The threshold, \(\beta \), represents the quality of a receiver and incorporates receiver-noise and other receiver technology imperfections. Thus, \(\beta \) models the receiver-performance under the MUSE methodology.

  4. 4.

    The path-loss exponent can be a function of n and m in order to capture fine-grained spatial variations in the path-loss.

  5. 5.

    The choice of propagation model would typically determine the path-loss.

  6. 6.

    That is, the aggregate RF-power received at \(\rho \) from all the interference sources for the receiver \(r_{n,m}\).

  7. 7.

    In fact, this relationship follows from the definition of unit-spectrum-space reliability.

  8. 8.

    The management of spectrum may vary across different spectrum sharing models. Market based approach to spectrum sharing presumes a spectrum pool while overlay approach requires recovering the underutilized spectrum.

  9. 9.

    Here, we distinguish these spectrum-access constraints that imply the spectrum available for sharing from the spectrum-access constraints on an individual RF-entity while exercising a spectrum-access. We call the former one as spectrum-sharing policy and the later one as spectrum-access policy.

  10. 10.

    As described here, the problem of spectrum-estimation use involves several sub-problems. In the interest of illustrating how these sub-components come together to accomplish real-time characterization of the use of spectrum, we do not discuss the individual sub-problems in detail. In [24], we presented cochannel interference-tolerant algorithms for the purpose of signal detection, received power estimation, and TDOA estimation and provided illustrations of these algorithms.

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  1. Computer Science and Engineering, University at Buffalo, Suny, USA

    Nilesh Khambekar

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  1. Nilesh Khambekar
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Correspondence to Nilesh Khambekar .

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  1. Electrical & Electronic Engg, Universiti Teknologi Brunei , Bandar Seri Begawan, Brunei Darussalam

    Mohammad A Matin

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Khambekar, N. (2017). Quantified Dynamic Spectrum Access Paradigm. In: Matin, M. (eds) Spectrum Access and Management for Cognitive Radio Networks. Signals and Communication Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-2254-8_4

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  • DOI: https://doi.org/10.1007/978-981-10-2254-8_4

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  • Online ISBN: 978-981-10-2254-8

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