• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.661-663
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• 2021

Network performance is degraded when the UE is disconnected because the outage occurs at the base station in a mobile communication system. Therefore it is important to detect and recover the outage. In this paper, detecting the outage base station by using the KPI and the network scanning in the neighbor base station, and increasing the transmit power and changing the frequency band to recovery the outage scheme is proposed. The proposed scheme uses not only the KPI of the base station but also the network scanning of the neighbor base stations to detect the outage base station, so that it is possible to detect the outage base station more accurately. In addition, when the outage occurred, the neighbor base station changes the transmit power and frequency band to recover the outage with less signal interference.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.30-42
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• 2020

Unlike in previous generations of mobile technology, machine learning (ML)-based self-healing research trend are currently attracting attention to provide high-quality, effective, and low-cost 5G services that need to operate in the HetNets scenario where various wireless transmission technologies are added. Self-healing plays a vital role in detecting and mitigating the faults, and confirming that there is still room for improvement. We analyzed the research trend in self-healing framework and ML-based fault detection, fault diagnosis, and fault compensation. We propose that to ensure that self-healing is a proactive instead of being reactive, we have to design an ML-based self-healing framework and select a suitable ML algorithm for fault detection, diagnosis, and outage compensation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.1049-1068
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• 2011

In this paper a simple and effective call admission control (CAC) scheme is proposed for the emerging interleave-division multiple-access (IDMA) systems, supporting a variety of traffic types and offering different quality of service (QoS) requirements and priority levels. The proposed scheme is signal-to-interference-plus-noise ratio (SINR) evolution based CAC (SE-CAC). The key idea behind the scheme is to take advantage of the SINR evolution technique in the process of making admission decisions, which is developed from the effective chip-by-chip (CBC) multi-user detection (MUD) process in IDMA systems. By virtue of this semi-analytical technique, the MUD efficiency can be estimated accurately. Additionally, the computational complexity can be considerably reduced. These features make the scheme highly suitable for IDMA systems, which can combat intra-cell interference efficiently with simple CBC MUD. Analysis and simulation results show that compared to the traditional CAC scheme considering MUD efficiency as a constant, the proposed SE-CAC scheme can guarantee high power efficiency and throughput for multimedia traffic even in heavy load conditions, illustrating the high efficiency of CBC MUD. Furthermore, based on the SINR evolution, the SE-CAC can make accurate estimation of available resource considering the effect of MUD, leading to low outage probability as well as low blocking and dropping probability.