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Rate Adaptive Based Resource Allocation with Proportional Fairness Constraints in OFDMA Systems

机译:OFDMA系统中具有比例公平约束的基于速率自适应的资源分配

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摘要

Orthogonal frequency division multiple access (OFDMA), which is widely used in the wireless sensor networks, allows different users to obtain different subcarriers according to their subchannel gains. Therefore, how to assign subcarriers and power to different users to achieve a high system sum rate is an important research area in OFDMA systems. In this paper, the focus of study is on the rate adaptive (RA) based resource allocation with proportional fairness constraints. Since the resource allocation is a NP-hard and non-convex optimization problem, a new efficient resource allocation algorithm ACO-SPA is proposed, which combines ant colony optimization (ACO) and suboptimal power allocation (SPA). To reduce the computational complexity, the optimization problem of resource allocation in OFDMA systems is separated into two steps. For the first one, the ant colony optimization algorithm is performed to solve the subcarrier allocation. Then, the suboptimal power allocation algorithm is developed with strict proportional fairness, and the algorithm is based on the principle that the sums of power and the reciprocal of channel-to-noise ratio for each user in different subchannels are equal. To support it, plenty of simulation results are presented. In contrast with root-finding and linear methods, the proposed method provides better performance in solving the proportional resource allocation problem in OFDMA systems.
机译:在无线传感器网络中广泛使用的正交频分多址(OFDMA)允许不同的用户根据其子信道增益获得不同的子载波。因此,如何为不同的用户分配子载波和功率以达到较高的系统总速率是OFDMA系统的重要研究领域。本文的研究重点是基于比例自适应约束的基于速率自适应(RA)的资源分配。由于资源分配是一个NP难和非凸优化问题,因此提出了一种新的有效资源分配算法ACO-SPA,该算法结合了蚁群优化(ACO)和次优功率分配(SPA)。为了降低计算复杂度,将OFDMA系统中资源分配的优化问题分为两个步骤。对于第一个,执行蚁群优化算法以解决子载波分配。然后,开发了具有严格比例公平性的次优功率分配算法,该算法基于不同子信道中每个用户的功率之和与信噪比倒数相等的原理。为了支持它,给出了大量的仿真结果。与根查找和线性方法相比,该方法在解决OFDMA系统中的比例资源分配问题方面具有更好的性能。

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