Dynamic Spectrum Access Decisions. George F. Elmasry
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and means the same for all waveforms.
5.4 Concluding Remarks
DSA can be designed to be a set of cloud services that are IaaS type. The design of DSA as a set of cloud services have some commonality with standard IaaS services and have some unique aspects that must be considered. This chapter offered a generic model in how to design DSA as a set of cloud services and some design concepts that can be followed. This chapter also covered some aspects of the metrology of DSA as a set of cloud services. As the reader goes through the next chapter, it will be seen how 5G cellular dynamic spectrum management is a special case of the generic model presented in this chapter. In 5G opportunistic and nonopportunistic spectrum bands are managed dynamically and spectrum resources are offered to users as services based on a service agreement between the user and the 5G service provider.
Exercises
1 Following the examples of DSA cognitive engine threads in Section 5.2, draft some DSA cognitive engine threads that can be added to the threads explained in Section 5.2.
2 Following the examples of DSA cloud metrics in Section 5.3, draft the details of the DSA metric of control traffic volume divided into two sub‐metrics, one for upward control traffic and one for downward.
Bibliography
1 CSCC, Practical Guide to Service Level Agreements Version 1.0, April 2015. Available at: https://www.omg.org/cloud/deliverables/CSCC-Practical-Guide-to-Cloud-Service-Agreements.pdf.
2 Cloud Computing Service Metric Description, US Department of Commerce, Publication 500‐307, NIST, April 2018.
3 Evaluation of Cloud Computing Services Based on NIST SP 800‐145, US Department of Commerce, Publication 500‐322, NIST, February 2018.
4 ISO/IEC 20926:2009, Software and systems engineering – Software measurement. IFPUG functional size measurement method, 2009.
5 Kushagra, K. and Dhingra, S., Modeling the Ranking of Evaluation Criteria for Cloud Services. International Journal of Electronic Government Research, vol. 14, pp. 64, 2018.
6 Polash, F., Abuhussein, A., and Shive, S., A survey of cloud computing taxonomies: Rationale and overview. 9th International Conference for Internet Technology and Secured Transactions 2014, pp. 459–465, 2014.
7 Ramachandran, M. and Mahmood, Z., Requirements Engineering for Service and Cloud Computing. Springer, 2017. ISBN 978‐3‐319‐51309‐6.
8 Siegel, J. and Perdue, J., Cloud Services Measures for Global Use: The Service Measurement Index (SMI). Service Research & Innovation Institute (SRII) Global Conference, IEEE, San Jose, CA, July 24–27, 2012.
9 The NIST Definition of Cloud Computing, US Department of Commerce, Special Publication 800‐145, NIST, September 2011.
Notes
1 1 An entity is a network node, a gateway or the central arbitrator, as explained later in this chapter.
2 2 Most of the spectrum access systems (SASs) developed for the citizens broadband radio service (CBRS) in the USA, which operate around the 3.5 GHz band, offer DSA as a set of cloud services. CBRS allows enterprises to build their own LTE networks and share the band with the LTE cellular infrastructure.
3 3 Interference detection can be an outcome of decision fusion. As explained earlier, hypothesizing interference by a sensor at any time instant does not necessarily lead to interference detection. Fusion of many hypotheses that may come from different sensing sources is what produces a decision that interference is above a certain threshold, which requires new frequency assignment.
4 4 In military communications, all lower echelon networks are wireless MANETs. These wireless networks can be lower tier waveforms with small spectrum footprint and upper tier networks with large spectrum footprint.
5 5 The correct term to use here is frequency band not frequency. A frequency band is defined by a central frequency and bandwidth. The term frequency is used throughout this book loosely to mean a frequency band a network is operated with in order to differentiate an operational frequency band used by a network from the known defined frequency bands such as the HF band, the VHF band, and the UHF band.
6 6 Many decision fusion techniques use heuristic algorithms because reaching an optimum solution for a large number of networks and a large number of nodes within each network can be too computationally extensive to produce timely DSA services. Reducing the order of computational complexity is beyond the scope of this book.
7 7 Notice that considering control traffic volume impact is not simple or straightforward. A DSA design approach can add more control traffic but in the meantime makes the use of spectrum resources much more efficient. Such design is better than lowering the control traffic volume at the expense of reducing the efficiency of spectrum resources use. Although one can use a metric to measure control traffic, this metric's impact comes secondary to the metrics that measure throughput efficiency.
8 8 Chapter 8 explains how co‐site interference avoidance can be another DSA cloud service.
Chapter 6 Dynamic Spectrum Management for Cellular 5G Systems
Part 1 of this book presented the foundations of creating a hybrid DSA design while relying on examples of heterogeneous hierarchical MANETs that demonstrate the most critical aspects of DSA design needs. Chapter 5 showed how to design DSA as a set of cloud services with metrics to measure spectrum use optimization objectively. This chapter covers the use of DSA1 with 5G cellular networks. There are commonalities and differences between hybrid DSA design for military cognitive MANET systems and DSA design for commercial cellular systems. With military MANET systems, all nodes in the network may be peers and all nodes may be mobile; there can be fast moving nodes such as fighter jets and slow‐moving nodes such as tanks and much slower nodes such as dismounted soldiers. A deployment of heterogeneous networks can be provisioned spectrum blocks for use in a nonopportunistic way. Waveforms forming networks may switch to opportunistic spectrum use in some cases but for the majority of the cases, networks use provisioned spectrum dynamically. These networks may share the provisioned spectrum blocks for an entire deployment dynamically before attempting to resort to the use of unlicensed bands. The problem domains in 5G cellular systems and military MANET systems are different, but they share many of the basic DSA concepts such as relying on spatial and time based sensing, collecting a knowledge repository, fusing the knowledge repository to produce decisions, performing interference mitigation techniques, and utilizing metrics to quantify the performance of dynamic spectrum use. As Chapter 5 showed, DSA can be developed as a set of cloud services in a hierarchical manner regardless of the system under consideration.
There are differences in the way DSA concepts are applied in military communications and in commercial use. With commercial cellular 5G, there are standardization bodies, research and development findings from industry and academia, and a mix of licensed and unlicensed spectrum use. There is a wide range of spectrum bands considered for use with 5G, including:
long‐term evolution (LTE) enhancements to utilize the spectrum below 6 GHz; this band increases capacity to about 2.5 times of that of LTE
segments of the 6–24 GHz band
the millimeter wave (mm‐wave) band between 24 and 86 GHz, which may bring the 20 Gbps theoretical speed to reality2
bands