Figure 4.9 The use of a centralized DSA arbitrator can further optimize spectrum resource allocation between a large‐scale set of heterogeneous networks.
One important advantage of using a centralized DSA arbitrator is the stability of spectrum assignments. The centralized arbitrator can assign each network a set of frequency bands as life lines and this set can be relatively small, as shown on the right of Figure 4.9. The centralized arbitrator can add more frequency band to a network based on traffic demand. The life‐line frequency band assignment can be stable and only changes if mobility requires the redistribution of these life‐line bands. This will create a form of stability in spectrum assignment that will result in creating more stable routes by the distributed cognitive routing engines. One of the challenges facing dynamic resource allocation techniques is rippling, as explained in the previous chapters. Rippling occurs when resources are assigned then quickly taken away to be reassigned.17 This can lead to the establishment and teardown of link before routes are established. The use of a centralized DSA arbitrator offers the designer of these heterogeneous networks the means to reduce rippling.
The use of a centralized arbitrator can also help address energy‐constrained nodes limitations. In heterogeneous MANET, some networks can be sensor networks with limited battery size, with only gateway nodes having enough energy to process high‐volume traffic. The assignment of life‐line frequency bands to energy‐constrained nodes while assigning gateway nodes more frequency bands can result in links between gateway nodes having lower routing cost than that of the links that rely on energy‐constrained nodes, which will decrease the likelihood that an energy‐constrained node is considered for routing higher bandwidth traffic while still maintaining stable network connectivity.
The design of a hybrid DSA system with a centralized arbitrator has to take into consideration the following:
1 There is a place for local DSA decisions, distributed cooperative DSA decisions, and centralized DSA decisions.
2 The speed of these decisions has to be considered in the design where local DSA decisions are fast. Distributed cooperative DSA decisions should take considerably longer than local decisions because they require some knowledge‐based fusion and propagation of fused information between the nodes. Centralized DSA decisions are meant to create stability, including life‐line spectrum allocation, and react to traffic demand increase in more optimum ways than using distributed cooperative decisions for demand‐based resource allocation.
3 Distributed cooperative DSA decisions within a net will still use the spectrum resource pool assigned to the net by the centralized arbitrator dynamically to address temporary surges in traffic demand before attempting to request more spectrum resources from the centralized arbitrator.
The centralized DSA arbitrator can make predictive analysis based on node mobility, the spectrum map, and how it changes to create a new spectrum plan. This spectrum plan will have spectrum assignments with changes to most networks in the deployment. These new spectrum plans are meant to stabilize spectrum assignment for longer periods and result in topology and route stability. In other words, the design of a hybrid DSA system with a centralized arbitrator can consider different places for DSA decision making and different types of DSA decisions where some decisions are meant as quick reaction while other decisions are meant to create radical changes that result in more spectrum resources assignment stability and global route stability. In addition to creating stable topology and stable routes, DSA decision stability also reduces the volume of DSA control traffic as information exchange can be just “maintenance” information exchange during stable periods.
Another critical advantage of the use of the centralized DSA arbitrator is the creation of global route tables that avoid routing over the compromised areas where jammers or eavesdroppers are known to be present and avoid routing over energy‐constrained nodes.
4.6 Concluding Remarks
With DSA design, there is no single design approach that can be used for all systems. Systems come with limitations, requirements, and vast differences in intended use. Regardless of whether the system under consideration is a civilian or a military system, local, distributed, and centralized DSA approaches have to be weighed in and the place of DSA cognitive engines has to be considered with other cognitive engines the system is using. This chapter is meant to help the reader analyze system limitations, requirements, especially the most critical requirements (e.g., avoid jamming, create low spectrum footprint map, avoid decision rippling, avoid routing over power constrained nodes, and adhere to the maximum bandwidth allocated for control traffic18), and create a design approach that makes the best of all DSA decision places in a hierarchical DSA system.
While this chapter considered mainly DSA systems for heterogeneous hierarchical MANETs, Chapter 6 addresses dynamic spectrum management in commercial 5G systems to draw parallels and contrasts between DSA design for military communications systems and DSA design for commercial systems eluding to the breadth of dynamic spectrum management needs and challenges. Chapter 7 presents some concepts for the use of 5G in military applications based on DSA concepts. It will be left to the reader to decide if 5G systems can be used for both civilian and military communications infrastructure with no modifications, or if some aspects of 5G can be borrowed for use in military communication systems. Can military networks, which are heterogeneous by definition, have a mix of military waveforms and 5G technologies such as mm‐wave based links and networks?19
Exercises
1 Consider Figure 4.5, where we have the master DSA engine being able to establish flows with a TDMA based network through the TDMA waveform agent. Let us assume that the flow unit is defined as F bps, as shown in the figure below. The x axis is the time defined in unit T and the y axis is the flow defined in unit F. The curve defines the traffic demand between two peer nodes over the formed TDMA network. Let us assume the TDMA waveform DSA agent applies the following rules when creating flows (adding or subtracting flows):A flow can be added or subtracted every 0.5T time. The protocols necessitate that flows cannot be added or subtracted in a rate faster than 0.5T.If a fraction of F is needed, the entire flow F is added.If a flow is not needed, its resources are freed. Freeing resources cannot happen at a faster rate than 0.5T.Use the curve to draw the allocated flows versus time over the duration of this traffic demand.Can you find time periods when the allocated bps are less than the traffic demand and time periods when the allocated pbs are more than the traffic demand?State the reasons for encountering gaps between traffic demand and resources allocations.Would you design such a system with TOS bit marking of traffic flows? Why?
2 Consider a MANET with N + 1 nodes. One of these nodes is transmitting a DSA control traffic packet of size L bytes to all the other N nodes. The node under consideration can reach half of the network nodes through one over‐the‐air hop and the rest of the nodes through two over‐the‐air hops. Assume that we need spectrum allocation of 2 Hz per each transmitted bit.If we assume 100% reliability,