Dynamic Spectrum Access Decisions. George F. Elmasry

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Название Dynamic Spectrum Access Decisions
Автор произведения George F. Elmasry
Жанр Отраслевые издания
Серия
Издательство Отраслевые издания
Год выпуска 0
isbn 9781119573791



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the different 5G services providers and the utilized technique can always be enhanced with time. The 5G service provider would have prerequisites such as removing the burden of spectrum sensing from the end user, and the goal of achieving spectrum utilization efficiency. The use of a hybrid spectrum sensing approach where the macrocell has a bird's eye view of spectrum use in this example and the ability to turn idle femtocells into SAs can always improve spectrum efficiency. The macrocell would use computationally complex spectrum arbitration techniques that can better optimize spectrum resources use dynamically from a global perspective and these techniques can be enhanced with time with new software releases.18

      6.4.1 The Macrocell as the Main Fusion Center

      1 The SA continually senses spectrum and collects spectrum sensing information (without any fusion). It consolidates spectrum sensing information for all frequency bands.

      2 The SA sends the consolidated spectrum sensing information to the macrocell.

      3 Picocells and femtocells also send their consolidated spectrum sensing information to the macrocell.

      4 The macrocell fusion center processes spectrum sensing information received from all SAs, all picocells, and all femtocells.

      5 The macrocell fusion center creates fusion results and sends them to each SA, femtocell, and picocell.

      6 An end user makes a spectrum service request from the SA.

      7 The SA uses the fusion results from the macrocell and replies to the end user with a recommendation of which spectrum band(s) to use.

Schematic illustration of the 5G use of the macrocell as the fusion center.

      This case can simply be described as a hybrid of distributed sensing and centralized fusion. Notice that this case can be morphed to the case where the SA, femtocells, and picocells perform a form of spectrum sensing information fusion and send the macrocell fusion center the results of its own local fusion. In either case, the macrocell fusion results are broadcasted to all lower hierarchy entities and the SA can't rely on its own local fusion results to respond to frequency band service requests from end users. Notice that even with the macrocell being the only place for fusion, the SAs, femtocells, and picocells perform a form of cooperative spectrum sensing.

      If some SAs have limited energy and must conserve energy, the macrocell can select a subset of the SAs to perform spectrum sensing and collect sensing information. The macrocell algorithm has to consider the hidden node challenge discussed earlier in this book and select SAs that are geographically distributed to optimize sensing impact.

      6.4.2 Spectrum Agents Operate Autonomously

      With this case, SAs can share spectrum sensing information in a distributed manner along with their geolocation information if they are not publically known to be static.19 In this case, each SA is a fusion center of spectrum sensing information and the spectrum sensing information shared is abstracted as a spectrum map after fusion.

Schematic illustration of the autonomous SAs in a distributed cooperative fashion and their control place.

      6.4.3 The End User as its Own Arbitrator

      One can conceptualize this case with very dense urban deployment where the end‐user device can obtain spectrum awareness information from multiple SAs and can use spectrum recommendations from multiple SAs to select the best spectrum band to operate on. Notice that if some QoS metrics are supplied to the end user as part of the recommendations, the end user can make the final decision on which band and which access point to select based on multiple factors, including least power consumption, highest data rate, and adhering to required QoS metrics thresholds.

Schematic illustration of the end use as the final arbitrator.

      It is important to note that this case with the end user making the final arbitration decision does not exclude designing a system that uses the macrocell as the fusion center or a system that makes SAs work autonomously. The arbitration here is in the context of arbitrating between different recommendations from different SA points and considering other metrics such as QoS and rate while making the end user reach the final decision on which recommendation to use.

      A service provider building a 5G infrastructure can build all the above capabilities in the deployed infrastructure and can enable or disable certain capabilities based on network management decisions or some cognitive algorithms that can morph the deployed infrastructure functionalities based on sensing information. One always needs to distinguish between capabilities or assets and how to use them dynamically. There are pros and cons for some capabilities that make them worth enabling only under certain conditions. For example, the case in Figure 6.14 has the disadvantage of requiring the end‐user device to perform an arbitration decision, which is an extra processing requirement on a device with limited battery. However, in very dense urban deployment with the close proximity of multiple cells, the device is already not consuming too much power in maintaining links, making it possible for the device to use some power for arbitration decisions. Also, in the case of autonomous SAs, we have the challenge of having a sparse deployment where an SA would have to rely on limited spectrum sensing information sources, which can lead to encountering a hidden node. However, one can see that in disaster areas, creating autonomous 5G access points is urgent enough to overcome the impact of higher probability of hidden node interference.

      5G standardization offers the service provider a lot of flexibility and different service providers will use different spectrum