An Optimization Design of Ultra Dense Networks Balancing Mobility and Densification

Zhu, Jinkang; Zhao, Ming; Zhou, Shengli

doi:10.1109/access.2018.2845690

Cited by 22 publications

(19 citation statements)

References 23 publications

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“…The SON has been standardized and applied as a fundamental feature in Fourth Generation (4G) and Fifth Generation (5G) mobile technologies [7, [35][36][37][38]. This feature was introduced by the 3GPP initially in LTE (Release 9 (Rel.9)).…”

Section: Research Overview and Motivationmentioning

confidence: 99%

Individualistic Dynamic Handover Parameter Self-Optimization Algorithm for 5G Networks Based on Automatic Weight Function

et al. 2020

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Section: Research Overview and Motivationmentioning

confidence: 99%

Individualistic Dynamic Handover Parameter Self-Optimization Algorithm for 5G Networks Based on Automatic Weight Function

et al. 2020

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“…The results showed that the proposed optimization algorithms can effectively improve network performance in terms of throughput and signal-to-interference-plus-noise ratio (SINR). A novel optimization design for UDNs that involves dividing massive numbers of users into groups based on moving speed and selecting suitable subnets was proposed Wireless Communications and Mobile Computing 3 in [17]. Optimization is then performed to coordinate suitable UDN subnets for each group to meet huge service demands with the minimum quantity of resources.…”

Section: Related Workmentioning

confidence: 99%

“…(i) Instead of optimizing either the network capacity or deployment cost, this work is aimed at balancing the trade-off between both parameters for dense small cells (ii) The optimal solutions, i.e., optimal ISDs within the constraint of different user capacity demands, provide insights to determine the ideal extent of network densification (iii) A novel method involving multiattribute user types is utilized in the proposed system model. Instead of grouping a large number of users based on single user attributes, like user mobility in [17], this method is designed to cover all possible propagation conditions for users including LOS or NLOS, outdoor or indoor, and UE heights. Other works [15][16][17]19] consider only individual or limited combinations of these possible propagation conditions in real urban environments.…”

Section: Related Workmentioning

confidence: 99%

“…Instead of grouping a large number of users based on single user attributes, like user mobility in [17], this method is designed to cover all possible propagation conditions for users including LOS or NLOS, outdoor or indoor, and UE heights. Other works [15][16][17]19] consider only individual or limited combinations of these possible propagation conditions in real urban environments. This method is described in more detail in Section 3 (iv) An innovative infinitesimal dividing modeling method termed the ring method is proposed in this work for network capacity dimensioning and optimization.…”

Section: Related Workmentioning

confidence: 99%

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Optimization of Cell Size in Ultra‐Dense Networks with Multiattribute User Types and Different Frequency Bands

Wei

Hwang

2018

Wireless Communications and Mobile Computing

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Ultra-dense cellular networks (UDNs) represent the trend for 5G networks in dense urban environments. With the aim of exploring the optimal extent of network densification under different performance requirements and the trade-off between the network capacity and deployment cost in UDNs, a multiple-objective optimization model is proposed. This novel optimization design consists of a multiattribute user type in which users are grouped based on their propagation conditions and an infinitesimal dividing modeling method termed the ring method for network capacity dimensioning. The optimal cell size is estimated to maximize the total network capacity and minimize the deployment cost under different levels of user capacity demand. Additionally, the corresponding total network capacity and the required number of base stations are presented. Furthermore, two conventional frequency bands, 800 MHz and 1.8 GHz, and two new bands, 3.5 GHz and mmWave 28 GHz, are considered to investigate their feasibility and the potential of higher frequency bands in the 5G network.

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“…Ultra dense cellular networks (UDCNs) have been proposed for 5G networks which include macrocells, picocells and femtocells [10], [12]. In addition to cellular traffic, 5G networks support D2D and internet of things (IoT) communications [11].…”

Section: Introductionmentioning

confidence: 99%

Prioritized Cell Association and Power Control in Uplink Heterogeneous Networks

Gulliver

2020

IEEE Access

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A heterogeneous network (HetNet) is a mix of macrocell base stations (MBSs) underlaid by a diverse set of small cell base stations (SBSs) such as microcells, picocells and femtocells. These networks are employed to enhance network capacity, improve network coverage, and reduce power consumption. However, HetNet performance can be limited by the disparity of power levels in the different tiers. Further, conventional cell association approaches cause MBS overloading, SBS underutilization, excessive user interference and wasted resources. Power control and cell association (CAPC) should be determined based on user priority, channel condition and BS traffic load. However, ensuring priority user (PU) requirements while satisfying as many normal users (NUs) as possible is not considered in existing power control algorithms. In this paper, prioritized CAPC is proposed to solve the load balancing problem between MBSs and SBSs and meet the needs of all PUs. Performance results in Additive white Gaussian noise (AWGN) and Rayleigh fading channels are presented which show that the proposed scheme is a fair and efficient solution which reduces power consumption and has faster convergence than other CAPC schemes.

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An Optimization Design of Ultra Dense Networks Balancing Mobility and Densification

Cited by 22 publications

References 23 publications

Individualistic Dynamic Handover Parameter Self-Optimization Algorithm for 5G Networks Based on Automatic Weight Function

Individualistic Dynamic Handover Parameter Self-Optimization Algorithm for 5G Networks Based on Automatic Weight Function

Optimization of Cell Size in Ultra‐Dense Networks with Multiattribute User Types and Different Frequency Bands

Prioritized Cell Association and Power Control in Uplink Heterogeneous Networks

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