Femtocell base station clustering and logistic smooth transition autoregressive‐based predicted signal‐to‐interference‐plus‐noise ratio for performance improvement of two‐tier macro/femtocell networks

Recently, to address the astonishing capacity requirement of 5G, researchers are investigating the possibility of combining different technologies with ultra-dense networks (UDNs). However, the ultradense deployment of small cells in the coverage area of conventional macrocells known as UDNs introduces new technical challenges such as severe interference, unfairness in radio resource sharing, unnecessary handover, a significant increase in energy consumption, and degraded quality-of-service (QoS). To overcome these challenges and achieve the performance requirements in 5G, there is a need to combine UDNs with other 5G enabling technologies and then, design intelligent management techniques for better performance of the overall networks. Hence, in this paper, we present a comprehensive survey on different generations of wireless networks, 5G new radio (NR) standards, 5G enabling technologies and the importance of combining UDNs with other 5G technologies. Also, we present an extensive overview of the recent advances and research challenges in intelligent management techniques and backhaul solutions in the last five years for the combination of UDNs and other enabling technologies that offers the visions of 5G. We summarise the mathematical tools widely exploited in solving these problems and the performance metrics used to evaluate the intelligent management algorithms. Moreover, we classify various intelligent management algorithms according to the adopted enabling technologies, benefits, challenges addressed, mathematical tools and performance metrics used. Finally, we summarise the open research challenges, provide design guidelines and potential research directions for the development of intelligent management techniques and backhaul solutions for the combination of UDNs and other 5G technologies. INDEX TERMS Macrocells, small cells, ultra-dense networks, QoS.

show abstract

“…Therefore, centralised approaches are only feasible for small-sized SCNs. An example of a centralised algorithm can be found in [228].…”

Section: ) Classification Of Rrm Algorithms According To Processing mentioning

confidence: 99%

Combination of Ultra-Dense Networks and Other 5G Enabling Technologies: A Survey

2020

View full text Add to dashboard Cite

show abstract

“…This solution converts the interference problem into a mixed integer nonlinear optimization model, and the simulation results found this algorithm to be less complex. According to the clustered small cells and predicted signal to interference plus noise ratio (SINR), the authors of [18] proposed a power control scheme applied to the downlink in the small cell network and found this method to lower the likelihood of an outage while improving throughput significantly compared to previous methods. However, these methods require considerable signaling interaction between small cells to complete the resource allocation.…”

Section: Introductionmentioning

confidence: 99%

Radio resource coordination and scheduling scheme in ultra-dense cloud-based small cell networks

Chen

Zou

Tang

et al. 2018

J Wireless Com Network

View full text Add to dashboard Cite

In a 5G ultra-dense network, dynamic network topology and traffic patterns lead to excessive system overhead and complex radio resource conflicts. The cloud radio access network and the fog computing have the advantages of high computation capabilities and low transmission delays. Therefore, by taking full advantage of these two characteristics, this study proposes a novel radio resource coordination and scheduling scheme in an ultra-dense cloud-based small cell network. Interference among small cells (or remote radio heads) can be avoided by implementing centralized cooperative processing in the base band unit pool in advance. Resource sharing in coordination and transfer depend on fog computing to relieve the overloaded cloud processing platform and reduce transmission delays, thereby maximizing resource utilization and minimizing system overhead when the network topology and number of users change dynamically. The simulation shows that the proposed scheme can increase the system throughput by 20% compared with the clustering-based algorithm; it can also increase system throughput by 33% compared with the graph coloring algorithm, decrease the signaling overhead by about 50%, and improve network's quality of service.

show abstract

Energy-spectral efficient resource allocation and power control in heterogeneous networks with D2D communication

et al. 2018

View full text Add to dashboard Cite

Femtocell base station clustering and logistic smooth transition autoregressive‐based predicted signal‐to‐interference‐plus‐noise ratio for performance improvement of two‐tier macro/femtocell networks

Cited by 13 publications

References 48 publications

Combination of Ultra-Dense Networks and Other 5G Enabling Technologies: A Survey

Combination of Ultra-Dense Networks and Other 5G Enabling Technologies: A Survey

Radio resource coordination and scheduling scheme in ultra-dense cloud-based small cell networks

Energy-spectral efficient resource allocation and power control in heterogeneous networks with D2D communication

Contact Info

Product

Resources

About