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Dynamic fair scheduling for inter-cell interference coordination in 4G cellular networks

机译:4G蜂窝网络中小区间干扰协调的动态公平调度

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Fairness is always an important issue for scheduling in communication systems. In 4G cellular networks, due to the fact that interference strengths from different user equipments (UEs) of neighbouring cells could be largely different, inter-cell interference coordination (ICIC) is quite difficult. In this paper, we model the ICIC problem in a scenario with two adjacent cells as a multi-decision 2-dimensional assignment problem, and we propose a dynamic fair scheduling scheme for it. The idea is to pair the strong interferers of adjacent cells with different UEs of the present cell alternatively, so that the damage of strong interferers can be dispersed by multiple UEs, which achieves high fairness. In details, we divide the time axis into periods for period-by-period decisions on assignment strategies. For each period, we combine the utilities of UEs in previous periods with the utility matrix for deciding the assignment strategy in the current period. Hungarian algorithm is used to obtain Max-Min fairness in each period, while the series of strategies form a greedy-like manner in which each assignment ameliorates the worst UEs up to this period. According to our simulations, the proposed scheme achieves extremely high fairness compared with random scheduling and traditional 1-shot Max-Min fair scheduling.
机译:对于通信系统中的调度,公平性始终是重要的问题。在4G蜂窝网络中,由于相邻小区的不同用户设备(UE)的干扰强度可能相差很大,因此小区间干扰协调(ICIC)非常困难。在本文中,我们将具有两个相邻像元的场景中的ICIC问题建模为多维二维分配问题,并为此提出了一种动态公平调度方案。该想法是将相邻小区的强干扰源与当前小区的不同UE交替配对,以使得强干扰源的损害可以被多个UE分散,这实现了高公平性。详细而言,我们将时间轴划分为多个周期,以期针对分配策略进行逐期决策。对于每个时期,我们将前一时期UE的效用与效用矩阵相结合,以确定当前时期的分配策略。匈牙利算法用于获得每个周期的最大-最小公平性,而这一系列策略形成了类似贪婪的方式,其中每个分配可以缓解该周期之前最差的UE。根据我们的仿真,与随机调度和传统的1次Max-Min公平调度相比,该方案实现了极高的公平性。

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