Ultra-Dense 5G Small Cell Deployment for Fiber and Wireless Backhaul-Aware Infrastructures

Rezaabad, Ali Lotfi; Beyranvand, Hamzeh; Salehi, Jawad A.; Maier, Martin

doi:10.1109/tvt.2018.2875114

Cited by 57 publications

(31 citation statements)

References 40 publications

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“…We also compare with the GA for cell planning presented in [27]; in general, PSO is similar to the GA in the logic that these two meta-heuristics algorithms are population-based search methods. In a single point iteration, PSO and GA move from one population to another with expected improvement.…”

Section: Results and Analysismentioning

confidence: 99%

“…In our simulation, we consider the same area dimension proposed in scenario II with mmWave BSs. In order to fulfill both constraints (data rates and coverage), and serve 3000 users, and the total number of iterations is set to 2000, and each user required 500 Mbps in contrast to 180 Mbps proposed in [27]. Forty-two UMa BSs are needed to cover the area, and four extra UMi BSs are deployed for GA to fulfill date rates constraints.…”

Section: Results and Analysismentioning

confidence: 99%

“…The investigation in [27] proposed an algorithm based on GA to determine the minimum number of BSs in the ultra-dense 5G network to satisfy cell capacity and coverage constraints; the authors used optical fiber and wireless backhaul to serve wired BSs and unwired BSs. However, few previous studies dealt with optimizing the placement of BSs for 5G networks in mmWave frequencies.…”

Section: Background and Related Workmentioning

confidence: 99%

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5G Base Station Deployment Perspectives in Millimeter Wave Frequencies Using Meta-Heuristic Algorithms

et al. 2019

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It can be predicted that the infrastructure of the existing wireless networks will not fill the requirement of the fifth generation (5G) wireless network due to the high data rates and a large number of expected traffic. Thus, a novel deployment method is crucial to satisfy 5G features. Meta-heuristic is expected to be a promising method for the complex deployment optimization problem of the 5G network. This work presents an implementation of a meta-heuristic algorithm based on swarm intelligence, to minimize the number of base stations (BSs) and optimize their placements in millimeter wave (mmWave) frequencies (e.g., 28 GHz and 38 GHz) in the context of the 5G network while satisfying user data rates requirement. Then, an iterative method is applied to remove redundant BSs. We formulate an optimization problem that takes into account multiple 5G network deployment scenarios. Further, a comparative study is conducted with the well-known simulated annealing (SA) using Monte Carlo simulations to assess the performance of the developed model. In our simulation results, we divide the region of interest into two subareas with different user distributions for different network scenarios while considering the intercell interference. The results demonstrate that the proposed approach has better network coverage with low percentage users in outage. In addition, the developed approach has less computational times to reach the desired target network quality of service (QoS). base station (BS) and user for urban micro-cells (UMi) street canyon and urban macro-cells (UMa) scenarios. For BS antenna height of 10 m and 25 m for UMi and Uma, respectively, the distance is 10 m and 35 m for UMi and Uma, respectively [4]. Thus, these very short distances allow better frequency reuse within a dense network coverage area. The usage of high frequencies is expected to be one of the key 5G technology enabling very high data rates and significant increases in capacity. The spectrum at 28 GHz and 38 GHz are still unexploited and have negligible atmospheric gases attenuation as compared to others high-frequency ranges according to International Telecommunication Union (ITU) L-series recommendations. 5G new radio deployments will require ultra-dense network topologies with the usage of high frequencies, which required many new cells, resulting in additional potential deployment challenges. Consequently, where and when to deploy cells while satisfying user data rates requirement will be challenging. To help assess this deployment challenge, the new approach of network planning is needed to meet the demand of 5G networks and beyond. Network planning is vital in order to deploy 5G networks efficiently, it is considered to be a promising solution to satisfy the user data rates requirement in 5G network [5], it depends on various parameters such as geographical area, cells configuration parameters, estimated number of users, estimated number of cells, path loss and propagation models, and frequency reuse patterns [6]. In the proposed model, UMa a...

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Section: Results and Analysismentioning

confidence: 99%

Section: Results and Analysismentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

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5G Base Station Deployment Perspectives in Millimeter Wave Frequencies Using Meta-Heuristic Algorithms

et al. 2019

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“…Even though the work highlights the scalability of their deployment strategy, the authors do not take into account the possibility of using wireless devices in the transport network and there is no mention of minimum requirements for the bitrate experienced by the mobile network users. The work in [25] proposes a genetic algorithm to minimize the planning cost of a mobile network while maximizing the network coverage. The authors consider the deployment of BSs employing wireless or wired backhaul in a greenfield scenario.…”

Section: Background and Related Workmentioning

confidence: 99%

Cost-Optimal Deployment of a C-RAN With Hybrid Fiber/FSO Fronthaul

Tonini

Raffaelli

Wosinska

et al. 2019

J. Opt. Commun. Netw.

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Centralized radio access network (C-RAN) has been considered as an architectural solution able to reduce capital and operational expenditure in dense 5G cellular networks, while allowing better network performance. The C-RAN approach decouples baseband units from antenna sites and places them in selected locations, connected by the so called fronthaul links. These links require expensive high capacity connections, thus calling for cost-efficient deployment. This paper presents a hybrid fronthaul solution for C-RAN based on both optical fibers and free space optics (FSO) to enhance fronthaul flexibility and minimize deployment costs. Two design strategies based on integer linear programming are proposed for both greenfield and brownfield deployments. The first strategy is referred to as joint planning (JP) and is based on the joint minimization of the number of deployed remote radio heads (RRHs) and cost of the hybrid fiber/FSO fronthaul. The second strategy is based on a two-step disjoint planning (DP) which first identifies a cost-optimal RRH placement and then finds the corresponding minimum cost deployment for the fronthaul links. Results obtained with JP and DP are compared in dense urban area scenarios (i.e., with characteristics similar to festivals or concerts) highlighting the advantage of the JP approach with respect to DP, both in terms of costs and an enhanced flexibility during the network design process.

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“…High cost of deployment and scalability are the major issues associated with fibre optics based backhaul solution. In order to address these issues, there has been evolution of passive optical network (PON) technology to improve the performance of fibre based solutions [15,16].…”

Section: Introductionmentioning

confidence: 99%

GPON and V-band mmWave in green backhaul solution for 5G ultra-dense network

Ajani¹,

Oduol

Adeyemo

2021

IJECE

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Ultra-dense network (UDN) is characterized by massive deployment of small cells which resulted into complex backhauling of the cells. This implies that for 5G UDN to be energy efficient, appropriate backhauling solutions must be provided. In this paper, we have evaluated the performance of giga passive optical network (GPON) and V-band millimetre wave (mmWave) in serving as green backhaul solution for 5G UDN. The approach was to first reproduce existing backhaul solutions in Very Dense Network (VDN) scenario which served as benchmark for the performance evaluation for the UDN scenario. The best two solutions, GPON and V-band solutions from the VDN were then deployed in 5G UDN scenario. The research was done by simulation in MATLAB. The performance metrics used were power consumption and energy efficiency against the normalized hourly traffic profile. The result revealed that GPON and V-band mmWave outperformed other solutions in VDN scenario. However, this performance significantly dropped in the UDN scenariodue to higher data traffic requirement of UDN compared to VDN. Thus, it can be concluded that GPON and V-band mmWave are not best suited to serve as green backhaul solution for 5G UDN necessitating further investigation of other available backhaul technologies.

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Ultra-Dense 5G Small Cell Deployment for Fiber and Wireless Backhaul-Aware Infrastructures

Cited by 57 publications

References 40 publications

5G Base Station Deployment Perspectives in Millimeter Wave Frequencies Using Meta-Heuristic Algorithms

5G Base Station Deployment Perspectives in Millimeter Wave Frequencies Using Meta-Heuristic Algorithms

Cost-Optimal Deployment of a C-RAN With Hybrid Fiber/FSO Fronthaul

GPON and V-band mmWave in green backhaul solution for 5G ultra-dense network

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