Dynamic optimized resource allocation in cellular & wireless networks with software interface

Abstract

In the past years, there has been a huge advance in the structure and design of wireless networks, and we have seen significant variation form the physical layer algorithm development to the layer protocol design to the system level optimization. Numerous wireless standards have been agreed on to keep up with demand of multiple applications. Over the years researchers came together and realized that for wireless networks, and because of user mobility, fading channel and power resources, and other factors we cannot simply optimize the wireless communication like we used to optimize the wired networks, where they usually concentrate on one layer without paying any attention on the effects it has on other layers. But for wireless networks, interconnection between layers and cross layer optimization is the basic issue to insure high quality performance. One of the most important issues in the cross layer optimization is resource allocation. In Wireless communication there are frequency, time and space diversity as well. If we took advantages of those diversities we can tremendously improve the quality of communication. All those variables contribute to the need of resource allocations. We have seen the advance of resource allocation in the past years with huge progress. As anyone can imagine, because the number of degrees freedom, and multiple parameters, dynamic resource allocation is a broad topic that deals with variety of problems. So the optimization tools and techniques may vary a lot. Aside from the commonly used method which is convex optimization there are non-linear and non-convex methods. When we speak about channel allocation and resource scheduling. Sometimes the problem tends to get more and more complicated. If we took into account the time caring conditions, the problem will evolve to be a dynamic optimization. The cooperation with the distributed and autonomous devices is considered, different mathematical models can be used to find the best strategy and optimal solution. It is only fair to say that there is no single perfect optimization available to solve all the dynamic resource allocation problems.