Applications of multi-objective optimization techniques in radio resource scheduling of cellular communication systems

Novel objectives such as very low outage, high capacity, and high throughput are major challenging problems in radio resource management of mobile communication systems. More specifically, in radio resource scheduling (RRS), the aim is how to optimize available resources such as transmission power and data rate to achieve certain targeted objectives. Conventional RRS algorithms are based on optimizing one objective while keeping others as constraints. This paper proposes a novel distributed RRS algorithm based on analytic multi-objective optimization. The proposed algorithm relaxes the constraints and jointly optimizes all the required objectives. Infinity set of optimal solutions, called Pareto optimal, is obtained. Each solution in the set is optimal in a specific sense. The decision maker selects the required solution that fulfills the network requirements and conditions. Some of the conventional RRS algorithms are special cases of our multi-objective based algorithm. Detailed mathematical analysis of the proposed algorithm is given. Simulation results show the behavior of the proposed algorithm as well as its advantages over conventional algorithms.