面向移动蜂窝网络的智能地理负载均衡

L. Du, J. Bigham, L. Cuthbert
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引用次数: 48

摘要

我们研究了一种新的蜂窝网络地理负载均衡方案,该方案可以根据地理流量分布实时智能地改变蜂窝网络的覆盖范围。提出了一种用于蜂窝网络覆盖实时控制的协同协商方法。通过对通信热点周围的天线辐射方向图进行收缩和整形,并扩大相邻小区的覆盖范围以弥补覆盖损失,从而提高整个蜂窝网络的性能。利用基站与关联天线之间的实时协同协商,在整个蜂窝网络环境下达成近乎最优的局部覆盖协议。结果表明了该技术的优越性。使用约束实编码遗传算法(RCGA)进行全局优化提供了一个基准。首先研究了使用惩罚函数来管理约束的收敛性,但结果不佳。使用问题空间的转换来移除约束,并解释了成功转换所必需的标准。
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Towards intelligent geographic load balancing for mobile cellular networks
We investigate a novel geographic load-balancing scheme for cellular networks that intelligently changes cellular coverage according to the geographic traffic distribution in real time. A cooperative negotiation approach for the real-time control of cellular network coverage is described. The performance of the whole cellular network is improved by contracting and shaping the antenna radiation pattern around a traffic "hot spot" and expanding adjacent cells coverage to fill in the coverage loss. By the use of real time cooperative negotiations between base stations and associated antennas, a near optimal local coverage agreement is reached in the context of the whole cellular network. Results showing the advantage of this technique are presented. Global optimization using constrained real-coded genetic algorithms (RCGA) provides a benchmark. Convergence using penalty functions to manage the constraints was first investigated but gave poor results. A transformation of the problem space is used to remove the constraints, and a criterion that is necessary for successful transformations is explained.
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