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Capacity Driven Small Cell Deployment in Heterogeneous Cellular Networks: Outage Probability and Rate Coverage Analysis

Authors:
Arif Ullah Khan at Chosun University
Arif Ullah Khan
Ziaul Haq Abbas at Universitetet i Agder
Ziaul Haq Abbas
Fazal Muhammad at University of Engineering and Technology, Mardan
Fazal Muhammad
  • University of Engineering and Technology, Mardan
Ghulam Abbas at Ghulam Ishaq Khan Institute of Engineering Sciences and Technology
Ghulam Abbas
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Abstract and Figures

Heterogeneous Cellular Networks (HCNets) are one of the key enabling technologies to improve the performance gain of future cellular networks. Stochastic geometry is considered a promising tool to model and analyze HCNets. Users and base stations are generally distributed uniformly using a Homogeneous Poisson Point Process (HPPP). The assumption of uniformly distributed users is not suitable in HCNets because of the existence of clustered users in hotspots. In order to consider the correlation between the users and base stations, deployment of small base stations in these areas are of great concern to increase the performance of HCNets. In this paper, we assume the notion of mixed user distribution, wherein the network users are the superposition of clustered and uniform users, modeled through HPPP and Poisson Cluster Process (PCP), respectively. We evaluate outage probability and rate coverage of the proposed HCNet model. We compare the network performance of the proposed mixed user distribution model with the conventional uniformly distributed user model. The analytical results are validated using Monte-Carlo simulations. Our results show that the proposed HCNet model of mixed user distribution outperforms the uniformly distributed user model in terms of outage probability and rate coverage.
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Received: 28 March 2019 Revised: 14 September 2019 Accepted: 5 December 2019
DOI: 10.1002/ett.3876
RESEARCH ARTICLE
Capacity driven small cell deployment in heterogeneous
cellular networks: Outage probability and rate
coverage analysis
Arif Ullah1Ziaul Haq Abbas2Fazal Muhammad3Ghulam Abbas4Lei Jiao5
1Telecommunication and Networking
(TeleCoN) Research Lab, Ghulam Ishaq
Khan Institute of Engineering Sciences
and Technology, Topi, Pakistan
2Faculty of Electrical Engineering,
Ghulam Ishaq Khan Institute of
Engineering Sciences and Technology,
Topi, Pakistan
3Department of Electrical Engineering,
City University of Science and Information
Technology, Peshawar, Pakistan
4Faculty of Computer Science and
Engineering, Ghulam Ishaq Khan
Institute of Engineering Sciences and
Technology, Topi, Pakistan
5Department of Information and
Communication Technology, University
of Agder, Grimstad, Norway
Correspondence
Arif Ullah, Telecommunication and
Networking (TeleCoN) Research Lab,
Ghulam Ishaq Khan Institute of
Engineering Sciences and Technology,
Topi, Pakistan.
Email:arifullah@giki.edu.pk
Abstract
Heterogeneous cellular networks (HCNets) are one of the key enabling tech-
nologies to improve performance gain of future cellular networks. Stochastic
geometry is considered a promising tool to model and analyze HCNets. Users
and base stations (BSs) are generally distributed uniformly using a homoge-
neous Poisson point process (HPPP). The assumption of uniformly distributed
users is not suitable in HCNets because of the existence of clustered users
in hotspots. To consider the correlation between the users and BSs, deploy-
ment of small base stations in these areas are of great concern to increase
the performance of HCNets. In this article, we assume the notion of mixed
user distribution, wherein the network users are the superposition of clus-
tered and uniform users, modeled through HPPP and Poisson cluster process,
respectively. We evaluate outage probability and rate coverage of the proposed
HCNet model. We compare the network performance of the proposed mixed
user distribution model with the conventional uniformly distributed user model.
The analytical results are validated using Monte-Carlo simulations. Our results
show that the proposed HCNet model of mixed user distribution outperforms
the uniformly distributed user model in terms of outage probability and rate
coverage.
1INTRODUCTION
The heterogeneity of cellular networks leads to increase in capacity due to spectrum reuse and densification via deploy-
ment of low power small base stations (SBSs) in a macro base station (MBS) coverage region.1-3 Leveraging SBS
deployment, it is assumed that heterogeneous cellular networks (HCNets) contribute 56×gain to the 1000×traffic
demand in the enhancement of fifth-generation cellular networks.4Keeping in view the network performance, cost, and
energy consumption, SBSs need to be optimally deployed in the hotspots (area of interest, for example, shopping malls,
cafeteria, airports, and so on), where the user density is high. For the deployment of SBSs and distribution of users,
researchers consider stochastic models to analyze the network performance gain tractably and accurately.5,6 Homoge-
neous Poisson point process (HPPP), a tool from stochastic geometry, is used to deploy different tiers of base stations
(BSs) as well as users randomly throughout the network.7,8 However, user deployment according to HPPP may not reflect
the real scenario of user distribution in HCNet because all users are not uniformly distributed as a high fraction of
Trans Emerging Tel Tech. 2020;31:e3876. wileyonlinelibrary.com/journal/ett © 2020 John Wiley & Sons, Ltd. 1of21
https://doi.org/10.1002/ett.3876
... To cope with the rapid growth of traffic demands for support wireless services, and the need for high quality, and secure coverage, cellular networks are trending towards small cell networks (SCN) [1][2][3][4]. On the other hand, non-orthogonal multiple access (NOMA) is an enabling technology to improve energy and spectrum efficiency [5,6]. ...
... Let denote the SIC decoding order. The users are decoded in the order of 1 ...
... On the other hand, a linear programming is solved via the interior-point algorithm at each iteration of Algorithm 1, and its computational complexity is O(K 0.5 ). Also, the master problem at each iteration of Algorithm 1 is solved by performing an Euclidean projection, which gives the computational complexity of O (1). Therefore, the computational complexity of Algorithm 1 is O(K 0.5 ). ...
Performance comparison of successive interference cancellation decoding order for base station association and power control in small cell networks incorporating handoff optimization
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View
... The explosive growth of mobile devices and the popularity of immersive interactive services (e.g., augmented reality/virtual reality) have led to a continuous increase in teletraffic. To alleviate this problem, network densification greatly improves the capacity of the network by deploying a large number of transmission points (TPs) [1][2][3] to form the ultra-dense network (UDN). UDN can be applied to various hot spots, such as stadiums, shopping malls, schools, and offices, which aims to provide high rates, low latency, and seamless coverage in 5G and even B5G networks. ...
... UDN can be applied to various hot spots, such as stadiums, shopping malls, schools, and offices, which aims to provide high rates, low latency, and seamless coverage in 5G and even B5G networks. [1][2][3] Future cellular networks have been featured with the dense deployment of small TPs that exploit spatial frequency reuse to enrich spectrum resources. 4 However, if relying on the traditional hexagonal cellular architecture and base station-centric design, network densification may bring inevitable challenges to user access, such as frequent handovers, 5 strong neighbor interference, 6 and so on. ...
... which is also the probability of finding n − 1 UEs in the area A (A denote the 2D area with the center at the origin and radius less than v). Then, the distance distribution of the nth closest UE is given by [theorem 1,22] ...
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... multi-user transmission to enhance the overall system throughput and ensure higher spectral efficiency compared to singleinput-single-output (SISO) systems [1], [2]. However, multiple data stream transmissions through multiple antennas ensure spatial multiplexing gain but it results in inter-stream interference at the receiver. ...
... where q nj is the nth row and jth column of Q matrix, h nj is the channel gain defined in (2). ...
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... Many existing studies assume that the macro cell base station and the small cell base station communicate with the same frequency band. For example, the following previous studies [8]- [11] are pioneering studies in which stochastic geometry is used to clarify the outage and association probabilities when using DUDe in single-channel multi-tier heterogeneous networks. In contrast to [8]- [11], we propose a method for dynamic channel and connection assignment in a heterogeneous network using multiple channels; this approach is then evaluated through simulation. ...
... For example, the following previous studies [8]- [11] are pioneering studies in which stochastic geometry is used to clarify the outage and association probabilities when using DUDe in single-channel multi-tier heterogeneous networks. In contrast to [8]- [11], we propose a method for dynamic channel and connection assignment in a heterogeneous network using multiple channels; this approach is then evaluated through simulation. In this study, each base station is assumed to use one of several shared channels (resource blocks). ...
Dynamic Channel Assignment for Downlink and Uplink Decoupling in Wireless Networks
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The demand for wireless communication capacity continues to increase with the extensive usage of smartphones, tablets, and devices that are related to the Internet of Things (IoT). However, devices and base stations are diversified, and base stations of various sizes are mixed. In existing cellular networks, the transmission powers of the base stations are different. If the downlink received power from the base station that belongs to the device is maximum, the uplink received power from the device at the base station is not always the maximum. This study maximizes the power that is received from the device through downlink-uplink decoupling (DUDe). DUDe can improve the spectral efficiency by selecting the downlink base station and the uplink base station independently in a network with base stations with different transmission powers. This study focuses on two technologies, DUDe and the dynamic channel assignment (DCA). It proposes an association algorithm to solve the dynamic combinational optimization problem for uplink and downlink cellular networks separately using DUDe. When a user device arrives, it first connects to the base station that has the maximum capacity at that time. Subsequently, by using the base station assignment at that time as an individual, the proposed method performs a more optimal base station assignment with DCA by using a genetic algorithm. The computer simulations demonstrate that the proposed method can achieve up to a 140 % higher spectral efficiency than the existing DUDe in the fixed channel assignment (FCA).
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... To meet the unprecedented demand for data-intensive wireless network services, the small cell networking topology has been considered a promising systematic solution for the next generation of cellular networks. [1][2][3] Such a networking topology can be interpreted as an extended macrocell network (MCN), that consists of macrocell base stations (MBSs), in which a large number of low-cost and low-power consuming small cell base stations (SBSs) with low service areas are densely deployed. [4][5][6] On the other side, the non-orthogonal multiple access (NOMA) that utilizes successive interference cancellation (SIC) is a prominent technique that allows a transmitter simultaneously to support multiple users' information within one frequency-time resource in the power domain. ...
... ln (2) where ln is the SIC ordering of MU k in the SIC ordering permutation n . Also, I (t) inter−cell is the out-of-cell interference from users not associated with BS n and can be expressed as ...
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View
... The conclusions are in line with previous research in this area concerning small cells [19]- [21] and the impact of mobile phone usage on person's exposure [22]. The layer with smaller cells (micro, pico, femto) is added to the macro layer to increase capacity or to improve coverage in smaller zones [23]. New services requiring high throughput, low latency and high availability lead to usage of smaller (and smaller) cells, and this architectural change may also yield lower EMF exposure. ...
... Small exposure reduction over the macro area was expected considering the small fraction of users in the micro area (Table 2). Micro layer is generally being added for coverage and/or capacity reasons [23]. High reduction in the micro area was due to the fact that users in the micro area had lower average transmitted power than they would have had without the micro base station turned on. ...
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... To cope with the explosive growth of demand for support new services, high-quality, and secure coverage, cellular networks are trending toward small-cell networks (SCN). [1][2][3][4] Small cells are low-cost, low-powered radio access points with low service areas that are deployed to enhance the mobile network coverage and capacity. [5][6][7] On the other side, nonorthogonal multiple access (NOMA) is an enabling technology to improve energy and spectrum efficiency for nextgeneration wireless communications. ...
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View
... The short wavelengths of mmWave signals also enable the deployment of small-cell wireless networks that provide high-speed connectivity in densely populated urban areas. The mmWave band consists of frequencies between 30 and 300 GHz, experiencing significant attenuation due to oxygen absorption [42,43]. However, 35, 94, 140, and 220 GHz frequencies have less attenuation and can be used for long-distance communication [42,44]. ...
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Article
  • Jul 2018
The dense deployment of low-power small cells base stations (SBSs) can complement existing macro base stations (MBSs) to address the 1000x mobile data challenge. Considering the low power rating of SBSs, it may be possible to supply them with renewable energy, providing an appealing alternative for hyper-dense deployment of small cells. Since renewable energy is weak and intermittent, off-grid SBSs may not be always active that raises the concern if they can be a real solution. To assess the performance of heterogeneous network (HetNet) with two tiers, including the traditional MBSs supplied by grid power and off-grid SBSs supplied by renewable energy, this work develops an analytical framework based on the celebrated stochastic geometry. The proposed framework is versatile with numerous features included: non-uniform BS deployment, biased user association, flexible operation of off-grid SBSs, and resource allocation with minimum rate guarantee. We obtain important distance distributions, association probabilities, and coverage probabilities. Extensive numerical results validate the accuracy of theoretical analysis and show the impact of key system parameters to the performance of HetNet with off-grid SBSs.
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