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arXiv 2408.09182cs.NI
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蜂窝网络中实现速率保障的带慢时间尺度索引偏置的效用最优调度

Utility Optimal Scheduling with a Slow Time-Scale Index-Bias for Achieving Rate Guarantees in Cellular Networks

Anurag Kumar, Rajesh Sundaresan

AI总结:

针对5G网络切片中带速率保障的RAN调度需求,提出一种三时间尺度最大和效用调度算法,通过慢时间尺度索引偏置调整保障速率用户的调度优先级,仿真验证其性能优于现有两时间尺度算法。

摘要:

5G网络中网络切片的需求之一是具备速率保障的RAN(无线接入网)调度。我们研究了一种用于最大和效用调度、带最小时延约束的三时间尺度算法。与常规方法一致,调度器在每个时隙为每个UE(用户设备)计算一个索引,并调度索引最大的UE,这对应最快的、信道衰落的自然时间尺度。下一个时间尺度是指数加权移动平均(EWMA)速率更新的时间尺度。我们算法中最慢的时间尺度是通过随机近似算法进行的“索引偏置”更新,其步长小于EWMA的步长。索引偏置与拉格朗日乘子相关,会对有速率保障的UE的时隙索引施加偏置,推动它们被更频繁地调度。我们得到了一对耦合的常微分方程(o.d.e.),这两个常微分方程的唯一稳定点就是带约束效用优化问题的原解和对偶解。对于两个较慢时间尺度迭代的小步长而言,UE速率和索引偏置的迭代过程会跟踪该常微分方程系统的渐近行为。仿真结果表明,通过以比EWMA迭代更慢的时间尺度运行索引偏置迭代,并在索引偏置更新中直接使用EWMA吞吐量,UE速率会稳定在速率区域边界上接近最优工作点的位置,且索引偏置在最优拉格朗日乘子附近仅有小幅波动。我们将所得结果与已有的两时间尺度算法进行了对比,证明所提方法性能更优。

英文摘要:

One of the requirements of network slicing in 5G networks is RAN (radio access network) scheduling with rate guarantees. We study a three-time-scale algorithm for maximum sum utility scheduling, with minimum rate constraints. As usual, the scheduler computes an index for each UE in each slot, and schedules the UE with the maximum index. This is at the fastest, natural time-scale of channel fading. The next time-scale is of the exponentially weighted moving average (EWMA) rate update. The slowest time scale in our algorithm is an "index-bias" update by a stochastic approximation algorithm, with a step-size smaller than the EWMA. The index-biases are related to Lagrange multipliers, and bias the slot indices of the UEs with rate guarantees, promoting their more frequent scheduling. We obtain a pair of coupled ordinary differential equations (o.d.e.) such that the unique stable points of the two o.d.e.s are the primal and dual solutions of the constrained utility optimization problem. The UE rate and index-bias iterations track the asymptotic behaviour of the o.d.e. system for small step-sizes of the two slower time-scale iterations. Simulations show that, by running the index-bias iteration at a slower time-scale than the EWMA iteration and using the EWMA throughput itself in the index-bias update, the UE rates stabilize close to the optimum operating point on the rate region boundary, and the index-biases have small fluctuations around the optimum Lagrange multipliers. We compare our results with a prior two-time-scale algorithm and show improved performance.

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