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require increasing or decreasing power level while keeping all established links and routes unchanged. It will be left to the cognitive engines to decide if this change can be maintained or new links need to be established. Another similar change is directionality. The ability to keep the same topology with minimal changes to the beam direction should be explored and used before making changes that will affect route stability.

      12 11 Many military communications waveforms use adaptive FEC. Some waveforms use concatenating codes where both the inner and outer codes are adaptive. The inner code can be turbo code while the outer codes can be RS code with erasure.

      13 12 The reader should keep in mind the different control loop time periods. Routing within the network, which can be waveform dependent, can have its own techniques that create and tear down reactive routes separate from global routes. Global routes need to be more stable than routes local to a network.

      14 13 It is important to see that with this architecture there could be two distinct types of cooperative distributed DSA. One type is distributed cooperative DSA between nodes within a single network. The other type is the global distributed cooperative DSA between the gateways.

      15 14 This proxy can go both ways. With a large‐scale deployment of heterogeneous MANETs, some MANET gateways may not be able to reach the centralized arbitrator due to factors such as terrain. The gateways can proxy the centralized arbitrator decisions through the cooperative distributed approach described in the previous section.

      16 15 The distributed cooperative protocol from the previous section is now partially implemented to reduce control traffic volume because it is only a fallback solution. Messages from a gateway node to the centralized arbitrator can use an unreliable multicast protocol. Dissemination of all these messages to all gateways is not needed. The fallback distributed cooperative solution can fuse the subset of information that reaches the gateway through multicast messages.

      17 16 Gaming theory based approaches can be used in the absence of a centralized arbitrator and some networks master DSA engines negotiating spectrum resources allocation with peer master DSA engines can be “greedy” in negotiation (overestimating date rate) causing the gaming theory based technique to tend to evenly distribute spectrum resources between the networks.

      18 17 As explained earlier, making global routes stable is more important than making routes local to one network stable.

      19 18 The system's requirements can define the maximum bandwidth that can be allocated to DSA control traffic.

      20 19 The DARPA 100G program and the DARPA mobile hotspot program explored the adaptation of some 5G technologies for military communications use from two different aspects.

Part II Case Studies

      The National Institute of Standards and Technology (NIST) defines cloud computing as “a model for enabling ubiquitous, convenient, on‐demand network access to a shared pool of configurable computing resources – e.g., networks, servers, storage, applications, and services – that can be rapidly provisioned and released with minimal management effort or service provider interaction”. The goal of this chapter is to present a case for DSA to be designed as a collection of cloud services that are ubiquitous, convenient, and on‐demand for a shared pool of spectrum resources or frequency bands. Spectrum resources can be provisioned and released at different speeds depending on the hierarchy of heterogeneous networks with minimal management effort from a human in the loop. In addition to offering DSA services from provisioned spectrum resources, DSA cloud services can tap into opportunistic spectrum resources as well.

      When interference is detected3 by any entity, a service request for a new frequency band to operate on can be triggered. The client for DSA cloud services here is not an actual person. The client is a network entity that is suffering from interference. The service is to re‐provision spectrum resources to accommodate all networks and nodes needed for seamless wireless communications.

      NIST provides different service models for cloud computing that include infrastructure as a service (IaaS). DSA services can follow the IaaS model.

Schematic illustration of the construct of DSA as a set of cloud services in network hierarchy.

      This generic architecture construct has a goal: DSA services should be available as a set of cloud services for any entity that needs it regardless of the control planes' conditions. A system that offers DSA as a set of cloud services that optimize the use of spectrum resources will follow a hybrid approach that is a mix of local, distributed cooperative, and centralized DSA services. Notice that local DSA services can happen at any entity in this hierarchy. Distributed cooperative DSA can be between the peer nodes in the network or between the peer gateways. Each of these distributed cooperative techniques has a place in a hybrid design. Centralized services can happen at the central arbitrator or at the network gateway acting as a proxy of the central arbitrator's services. As Chapter 8 explains, co‐site interference considerations can be another type of DSA cloud services that can be added to the collection of DSA services as a subset of services. The system's specifications and requirements can guide the designer on how to mix and match these DSA services in the system.

      As the reader goes through the next chapter, the concept of 5G cellular dynamic spectrum management being a derivative of this generic construct should become clearer. The lowest hierarchical entity in 5G cellular that can seek DSA services is the end user device or user equipment (UE). The UE has access to different hierarchical cells (equivalent to gateways) and the higher tier DSA decision (e.g., from a macro‐cell) can override the lower tier DSA decision (e.g., from a femtocell).

      DSA decisions are often needed when wireless networks are suffering from interference and reduced connectivity.

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