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Fast Algorithms for Resource Allocation in Wireless Cellular Networks

机译:无线蜂窝网络中资源分配的快速算法

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We consider a scheduled orthogonal frequency division multiplexed (OFDM) wireless cellular network where the channels from the base-station to the $n$ mobile users undergo flat fading. Spectral resources are to be divided among the users in order to maximize total user utility. We show that this problem can be cast as a nonlinear convex optimization problem, and describe an $O(n)$ algorithm to solve it. Computational experiments show that the algorithm typically converges in around 25 iterations, where each iteration has a cost that is $O(n)$, with a modest constant. When the algorithm starts from an initial resource allocation that is close to optimal, convergence typically takes even fewer iterations. Thus, the algorithm can efficiently track the optimal resource allocation as the channel conditions change due to fading. We also show how our techniques can be extended to solve resource allocation problems that arise in wideband networks with frequency selective fading and when the utility of a user is also a function of the resource allocations in the past.
机译:我们考虑一个调度的正交频分复用(OFDM)无线蜂窝网络,其中从基站到$ n $移动用户的信道经历平坦衰落。频谱资源将在用户之间分配,以最大程度地提高用户的总体实用性。我们证明了该问题可以被转换为非线性凸优化问题,并描述了一种O(n)$算法来解决。计算实验表明,该算法通常在约25个迭代中收敛,其中每个迭代的成本为$ O(n)$,且具有适度的常数。当算法从接近最佳的初始资源分配开始时,收敛通常需要更少的迭代。因此,当信道条件由于衰落而改变时,该算法可以有效地跟踪最佳资源分配。我们还展示了如何扩展我们的技术来解决在频率选择性衰落的宽带网络中出现的资源分配问题,以及过去用户的效用也是资源分配的函数。

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