Dynamic Spectrum Access Decisions - George F. Elmasry

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north as a reference to how the different angles in this estimation are related. Figure 4.5 shows how “north” is used as a reference and how the angles are related.

Schematic illustration of the pointing directions between two nodes.

      In Figure 4.5, notice the following:

       γ is the antenna pointing direction, relative to north

       β is the bearing of the other node, relative to north

       δ is the angle between the pointing direction and the targeted node.

      One can see the extensive distributed information that would need to be communicated between the different DSA engines in order for the DSA engine to be able to support a cognitive routing engine. In addition, the DSA engine is expected to perform extensive computations continually so that the routing engine has accurate estimations of the interference level of all potential frequency slots to use and all nodes in the neighborhood.7

      While the disadvantages of using these two distributed cognitive engines include the increase of over‐the‐air resources use for DSA control traffic and the need for local computational power to perform comprehensive local decision fusion tasks, the advantages of such design include the following:

      1 Efficient use of spectrum resources, which can lead to higher throughput.

      2 The ability to reuse the same frequency slot relying on directionality and power control, which also can lead to higher throughput of the system.

      3 The ability to route around jammers.

      4 Making the transmitting nodes spectrum emission less prone to eavesdropping by reducing the spectrum footprint of the formed MANET in comparison to using omnidirectional antennas.

      5 The ability to dynamically adapt spectrum resources use to the specifics of the area of deployment (e.g. terrain) and achieve connectivity in the presence of external benign and/or malicious interferences.

      These advantages can be critical in the use of DSA in military cognitive MANETs. One can see that the trade space in Figure 4.1 is overly simplified and it can include other dimensions:

       The low probability of detection (LPD) trade space, which can be measured with a metric that calculates the ratio of the combined spectrum footprint of all directional links to the entire theater area of operation.

       The low probability of intercept (LPI) trade space, which can be measured with a metrics that calculates the probability of an eavesdropping node, randomly positioned in the theater's area of operation, to intercept a directional link.

       The probability of avoiding jammed areas trade space, which can be measured with a metric that counts the number of successes and failures to establish routes around jammed areas where jammed areas are randomly positioned in the theater's area of operation.

      In the previous section, we saw how a distributed DSA engine can interact with a distributed routing engine in order to create a low spectrum footprint MANET with antijamming, LPI/LPD, and dynamic spectrum reuse capabilities. In this section, we will show how this distributed cooperative routing engine concept, which is local to a single network, can be adapted to global heterogeneous routing, which is between the different types of hierarchical MANETs.8 The goal here is to explore how far a system that is designed as a hybrid between local and distributed cooperative DSA decisions can go before we move to cases where a centralized DSA arbitrator is needed.

      Making distributed DSA work in a global manner with heterogeneous hierarchical networks can be based on the following principals:

       The creation of multitiered DSA engine architecture where a platform that is a node of more than one network (gateway node) has a distributed DSA engine for each network and a parent DSA engine (for global arbitration of DSA decisions).

       The creation of two distinct types of cognitive routing engines where one type is for routing local to the network and the other type is for gateway nodes that can create global routes.

 Schematic illustration of the local and gateway nodes cognitive engines.

      Notice that there are different approaches used to create dynamic heterogeneous global routing. One known approach creates an interface control definition (ICD) between each waveform type and the networking layer above the waveform. This interface is sometimes referred to as the router‐to‐radios (R2R) interface. In Figure 4.6, this interface may be replaced with the interface between the waveform routing engine and the master routing engine. The approach covered here relies on the master routing engine making routing decisions by choosing between the different available paths based on the condition of each wireless network in the path. This interface can override R2R protocols such as the point‐to‐point protocol over Ethernet (PPPOE), which have been shown to be insufficient in dynamic MANETs. The approach covered here leaves certain dynamic spectrum management local to each network through the waveform DSA engine and uses the master DSA engine for other DSA decisions. Here, we have a more comprehensive approach than that of Section 4.3 where the gateway node is part of the spectrum allocation negotiation between the different MANETs.