Max-throughput interference avoidance mechanism for indoor self-organizing small cell networks

Lin, Kuang-Hsun; Tsai, Cho-Hsin; Chang, Jen‐Wei; Chen, Yu-Chieh; Wei, Hung‐Yu; Yeh, Fu-Ming

doi:10.1016/j.icte.2017.04.005

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…Instead of outdoor deployments, indoor small cells may employ lower power levels and provide higher data rates compared to outdoor base stations. This scheme reduces energy consumption, improves quality of service (QoS) and experience (QoE), employs the spectrum efficiently, facilitate using licensed bands for home networking, lowers the level of electromagnetic radiations, minimizes the costs for the mobile operator and provides true ubiquity and coverage for subscribers [22]. However, operators lose their control on base station deployment.…”

Section: Opportunities In Dynamic Networkmentioning

confidence: 99%

Density-aware Dynamic Mobile Networks: Opportunities and Challenges

Onur,

Mollahasani,

Eroğlu

et al. 2017

Preprint

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We experience a major paradigm change in mobile networks. The infrastructure of cellular networks becomes mobile as it is densified by using mobile and nomadic small cells to increase coverage and capacity. Furthermore, the innovative approaches such as green operation through sleep scheduling, user-controlled small cells, and end-to-end slicing will make the network highly dynamic. Mobile cells, while bringing many benefits, introduce many unconventional challenges that we present in this paper. We have to introduce novel techniques for adapting network functions, communication protocols and their parameters to network density. Especially when cells on wheels or wings are considered, static and man-made configurations will waste valuable resources such as spectrum or energy if density is not considered as an optimization parameter. In this paper, we present the existing density estimators. We analyze the impact of density on coverage, interference, mobility management, scalability, capacity, caching, routing protocols and energy consumption. We evaluate nomadic cells in dynamic networks in a comprehensive way and illustrate the potential objectives we can achieve by adapting mobile networks to base station density. The main challenges we may face by employing dynamic networks and how we can tackle these problems are discussed in detail.

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Section: Opportunities In Dynamic Networkmentioning

confidence: 99%

Density-aware Dynamic Mobile Networks: Opportunities and Challenges

Onur,

Mollahasani,

Eroğlu

et al. 2017

Preprint

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“…U LTRA-DENSE small cells (UDSC) are the key to providing high capacity for the fifth generation (5G) mobile systems [1]. Unlike macrocells can be deployed by the help of cell planning tools, small cells are usually installed in an ad hoc manner, thereby making real-time interference management in UDSC challenging [2]. Because customers' traffic loads change in both time domain and spatial domain, underutilized small cells lead to the issue of spectrum and energy inefficieny.…”

Section: ç 1 Introductionmentioning

confidence: 99%

Data-Driven Resource Management for Ultra-Dense Small Cells: An Affinity Propagation Clustering Approach

Wang

Cheng

2019

IEEE Trans. Netw. Sci. Eng.

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Deploying dense small cells is the key to providing high capacity, but raise the serious issue of energy consumption and inter-cell interference. To understand the behaviors of ultra-dense small cells (UDSC) with dynamic interference and traffic patterns, this paper presents a data-driven resource management (DDRM) framework to implement power control and channel rearrangement in UDSC. We find that the inter-cell interference can be used to describe the affinity of cells. Thus, we propose an unsupervised learning algorithm for UDSC, called affinity propagation power control (APPC) mechanism. In principle, APPC first groups small cells into different clusters and identifies cluster centers. Next, the transmission power of a cluster center is decreased to reduce the interference to the neighboring cells' users in this cluster. Since lowering transmission power of a cluster center cell may cause the performance degradation to the users at the cell edge, a victim-aware channel rearrangement (VACR) mechanism is further designed to adjust the channel usage bandwidth of the neighboring cells in order to guarantee the quality of service of these victimized users. Our simulation results show that the DDRM framework can significantly improve energy efficiency and throughput in UDSC compared to the existing approaches.

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