Small Cell Deployment Challenges in Ultradense Networks: Architecture and Resource Management

Nidhi, -; Mihovska, Albena

doi:10.1109/csndsp49049.2020.9249560

Cited by 7 publications

(3 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Considerable research has been carried out both domestically and internationally on the technology of spectrum resource allocation in Ultra Dense Networks (UDN). For instance, [4] elucidates on the suitable scenarios for resource allocation in ultra-dense networking, and [5] expounds on the problems that can be resolved by spectrum resource allocation in UDN.…”

Section: Figure 1 Udn Communication Modelmentioning

confidence: 99%

Resource allocation trends for ultra dense networks in 5G: a comprehensive survey

jiangliang,

donghui,

siyi

2023

Third International Conference on Digital Signal and Computer Communications (DSCC 2023)

View full text Add to dashboard Cite

With the widespread application of the fifth-generation mobile communication system, mobile data traffic has seen rapid growth, bringing new challenges to traditional cellular networks. Ultra-dense networks (UDN) are one of the key technologies used in 5G communication to address user capacity and high-speed transmission. How to effectively solve the problems of inter-site interference, spectrum resource scarcity, and high energy consumption in UDN has become a major research topic, and resource allocation technology is essential in this regard. This article summarizes the spectrum resource allocation methods and applications in UDN through literature review. Firstly, the applicable scenarios, models, and various indicators of resource allocation in UDN are summarized and analyzed. Secondly, this paper systematically sorts and classifies recent research on resource allocation methods for UDNs, analyzing their applicability, advantages, and disadvantages. Additionally, the paper discusses the future development of spectrum resource allocation methods for UDNs.

show abstract

Section: Figure 1 Udn Communication Modelmentioning

confidence: 99%

Resource allocation trends for ultra dense networks in 5G: a comprehensive survey

jiangliang,

donghui,

siyi

2023

Third International Conference on Digital Signal and Computer Communications (DSCC 2023)

View full text Add to dashboard Cite

show abstract

“…There have been several studies on different aspects of IAB networks in 5G ultra-dense scenarios. For instance, the IAB node (or small cell) placement problem [50] [51] [52] [53], interference management [54] [55] [56] [57] [58] [59], resource allocation [60] [61], the IAB donor (or gateway) placement problem [62] [63] [64] [65] [66], and mobility management [67] [68] [69] have been studied in the context of 5G ultra-dense networks. The focus in this paper is on the gateway location problem in 5G ultra-dense networks.…”

Section: B Related Workmentioning

confidence: 99%

A Fast Heuristic for Gateway Location in Wireless Backhaul of 5G Ultra-Dense Networks

et al. 2021

View full text Add to dashboard Cite

In 5G Ultra-Dense Networks, a distributed wireless backhaul is an attractive solution for forwarding traffic to the core. The macro-cell coverage area is divided into many small cells. A few of these cells are designated as gateways and are linked to the core by high-capacity fiber optic links. Each small cell is associated with one gateway and all small cells forward their traffic to their respective gateway through multi-hop mesh networks. We investigate the gateway location problem and show that finding near-optimal gateway locations improves the backhaul network capacity. An exact p-median integer linear program is formulated for comparison with our novel K-GA heuristic that combines a Genetic Algorithm (GA) with K-means clustering to find near-optimal gateway locations. We compare the performance of K-GA with six other approaches in terms of average number of hops and backhaul network capacity at different node densities through extensive Monte Carlo simulations. All approaches are tested in various user distribution scenarios, including uniform distribution, bivariate Gaussian distribution, and cluster distribution. In all cases, K-GA provides near-optimal results, achieving average number of hops and backhaul network capacity within 2% of optimal while saving an average of 95% of the execution time. INDEX TERMS 5G, backhaul network capacity, gateway location problem, heuristic, machine learning, small cells, ultra-dense networks.

show abstract

“…Nowadays, wireless cellular networks are denser and many issues must be addressed [9]. In the coming years, the prediction is that the number of deployed small cells will increase exponentially [10], [11]. An ultra-dense network (UDN) is defined by A. Gotsis et alin [12] as a network where the number of small cells is greater than the number of active user equipments (UEs) [13].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Cell Selection Scheme for 5G Heterogeneous Ultra-Dense Networks

Alablani

Arafah

2021

IEEE Access

View full text Add to dashboard Cite

Fifth-generation (5G) cellular networks are a promising technology to meet the rapid growth in wireless traffic. Small cells are critical in fulfilling the requirements of 5G networks. A heterogeneous ultra-dense network (HUDN) is an enabling technology consisting of several types of small cells to enhance the performance of 5G networks effectively. A critical issue of HUDN is the cell selection method because the traditional technique for cell selection is inapplicable in such a network. This study proposes a novel adaptive cell selection (ADA-CS) scheme. It adapts to various characteristics of HUDNs and vehicle movements. It performs six phases to select the best base station with which to be associated. Simulation results show that, with low-and medium-speed vehicles, the ADA-CS scheme outperforms the traditional protocol in terms of the average number of handovers by 42.39%. In addition, it is superior to some relevant recent schemes by up to 36.53%. The adaptation feature of the proposed protocol provides additional improvements regarding the average number of handovers with high-speed vehicles. Therefore, it achieves superiority in terms of the average number of handover failures and unnecessary handovers. In addition, the ADA-CS scheme enhances the average achievable downlink data rates and spectral efficiency per vehicle by 3.98% and 2.79% compared with the traditional and the relevant recent schemes.

show abstract

Small Cell Deployment Challenges in Ultradense Networks: Architecture and Resource Management

Cited by 7 publications

References 19 publications

Resource allocation trends for ultra dense networks in 5G: a comprehensive survey

Resource allocation trends for ultra dense networks in 5G: a comprehensive survey

A Fast Heuristic for Gateway Location in Wireless Backhaul of 5G Ultra-Dense Networks

An Adaptive Cell Selection Scheme for 5G Heterogeneous Ultra-Dense Networks

Contact Info

Product

Resources

About