Non-Machine Learning Cell Outage Compensation for a Three Tier Heterogeneous Network

Aicha Jahangeer, V. Bassoo
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引用次数: 1

Abstract

A cell outage compensation algorithm based on Received Signal Strength Indicator (RSSI) for a three-tier hetrogeneous network (HetNet) is proposed in this paper. The algorithm is non-machine learning based to reduce the complexity of the compensation scheme, and to eliminate the need for training. Simulation results show that cell outage compensation is successfully achieved, provided that base stations (BSs) of sufficient capacity are deployed near users in outage. The RSSI values after compensation are also higher than those during the outage. Additionally, the proposed algorithm outperforms a k-means clustering scheme when allocating users in outage to neighbouring BSs.
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三层异构网络的非机器学习单元中断补偿
针对三层异构网络(HetNet),提出了一种基于接收信号强度指示器(RSSI)的小区中断补偿算法。该算法基于非机器学习,以降低补偿方案的复杂性,并消除对训练的需求。仿真结果表明,在断网用户附近部署有足够容量的基站时,可以成功实现小区断网补偿。补偿后的RSSI值也高于停运时的RSSI值。此外,该算法在将停机用户分配到邻近的BSs时优于k-means聚类方案。
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