Applications of Multi-Objective Optimization Techniques in Radio Resource Scheduling of Cellular Communication Systems
Applications of Multi-Objective Optimization Techniques in Radio Resource Scheduling of Cellular Communication Systems
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DOI：
10.1109/twc.2008.060533
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发表时间：
2008
影响因子：
10.4
通讯作者：
M. Elmusrati;H. El-Sallabi;H. Koivo
中科院分区：
文献类型：
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作者：
M. Elmusrati;H. El-Sallabi;H. Koivo
低中断、高容量和高吞吐量等新目标是移动通信系统无线电资源管理的主要挑战。更具体地说，在无线电资源调度（RRS）中，其目的是如何优化可用资源，如传输功率和数据速率，以达到一定的目标。传统的RRS算法基于优化一个目标，同时保留其他目标作为约束。提出了一种基于解析多目标优化的分布式RRS算法。该算法放宽约束条件，对所有目标进行联合优化。得到无穷多最优解集，称为帕累托最优解。集合中的每个解在特定意义上都是最优的。决策者选择满足网络需求和条件的解决方案。一些传统的RRS算法是我们的多目标算法的特殊情况。对该算法进行了详细的数学分析。仿真结果表明了该算法的性能以及与传统算法相比的优越性。
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.