Automated Placement of Individual Millimeter-Wave Wall-Mounted Base Stations for Line-of-Sight Coverage of Outdoor Urban Areas

Szyszkowicz, Sebastian S.; Lou, Andrés; Yanıkömeroğlu, Halim

doi:10.1109/lwc.2016.2552168

Cited by 30 publications

(27 citation statements)

References 17 publications

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“…The problem of identifying C can be approached by using tools from Computational Geometry. Similarly to [8], we introduce the notions of Simple Polygons (SPs) and Polygons With Holes (PWHs) in our system, describing the buildings and the roads, respectively.…”

Section: A Identifying Potential Rsu Locationsmentioning

confidence: 99%

“…Similarly, authors in [11], [12], only considered the distance or the propagation characteristics, but not the shape of the buildings and the roads. In our case, we will utilize tools from Computational Geometry (as in [8]), and consider all the above to find the desirable RSU locations. More specifically, we will investigate the performance of our algorithm under two urban environments, describing their unique characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Millimeter-Wave Infrastructure Placement for City-Scale ITS

Mavromatis

Tassi

Piechocki

et al. 2019

2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)

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Millimeter Waves (mmWaves) will play a pivotal role in the next-generation of Intelligent Transportation Systems (ITSs). However, in deep urban environments, sensitivity to blockages creates the need for more sophisticated network planning. In this paper, we present an agile strategy for deploying road-side nodes in a dense city scenario. In our system model, we consider strict Quality-of-Service (QoS) constraints (e.g. high throughput, low latency) that are typical of ITS applications. Our approach is scalable, insofar that takes into account the unique road and building shapes of each city, performing well for both regular and irregular city layouts. It allows us not only to achieve the required QoS constraints but it also provides up to 50% reduction in the number of nodes required, compared to existing deployment solutions.

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Section: A Identifying Potential Rsu Locationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Millimeter-Wave Infrastructure Placement for City-Scale ITS

Mavromatis

Tassi

Piechocki

et al. 2019

2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)

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show abstract

“…Recent works on mmW communications such as [1], [10], [12]- [18], and [19] have investigated the problems of access point deployment, beam steering, and coverage optimization. In [10], the authors investigate the effect of the number of antennas on the capacity and coverage probability in the mmWbased small cell, then they propose an antenna clustering scheme to utilize the antennas more efficiently.…”

Section: A Prior Workmentioning

confidence: 99%

“…Each design criterion is also formulated as a joint optimization problem in [10]. In [12], the authors develop an algorithm that uses computational geometry to place below-rooftop wall-mounted access points using a LoS propagation model for mmW carriers. The goal was to find a set of candidate AP locations whose LoS region, as viewed from each AP in a given set of disjoint geotropical blocks, has a locally maximum area.…”

Section: A Prior Workmentioning

confidence: 99%

Optimized Deployment of Millimeter Wave Networks for In-Venue Regions With Stochastic Users’ Orientation

Soorki

Saad

Bennis

2019

IEEE Trans. Wireless Commun.

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Millimeter wave (mmW) communication is a promising solution for providing high-capacity wireless network access. However, the benefits of mmW are limited by the fact that the channel between a mmW access point and the user equipment can stochastically change due to severe blockage of mmW links by obstacles such as the human body. Thus, one main challenge of mmW network coverage is to enable directional line-of-sight links between access points and mobile devices. In this paper, a novel framework is proposed for optimizing mmW network coverage within hotspots and in-venue regions, while being cognizant of the body blockage of the network's users. In the studied model, the locations of potential access points and users are assumed as predefined parameters while the orientation of the users is assumed to be stochastic. Hence, a joint stochastic access point placement and beam steering problem subjected to stochastic users' body blockage is formulated, under desired network coverage constraints. Then, a greedy algorithm is introduced to find an approximation solution for the joint deployment and assignment problem using a new "size constrained weighted set cover" approach. A closed-form expression for the ratio between the optimal solution and approximate one (resulting from the greedy algorithm) is analytically derived. The proposed algorithm is simulated for three in-venue regions: the meeting room in the Alumni Assembly Hall of Virginia Tech, an airport gate, and one side of a stadium football. Simulation results show that, in order to guarantee network coverage for different in-venue regions, the greedy algorithm uses at most three more access points (APs) compared to the optimal solution. The results also show that, due to the use of the additional APs, the greedy algorithm will yield a network coverage up to 11.7% better than the optimal, AP-minimizing solution.

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“…The authors utilized a meta-heuristic algorithm to obtain near-optimum solutions. Furthermore, in [22], a new approach was proposed for solving the mmWave cell planning problem by leveraging the polygon computational geometry concept. Note, however, that in this study the issue of backhauling was not addressed.…”

Section: A Related Workmentioning

confidence: 99%

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

Rezaabad

Beyranvand

Salehi

et al. 2018

IEEE Trans. Veh. Technol.

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In this paper, we study the cell planning problem for a two-tier cellular network containing two types of base stations (BSs)-i.e. with fiber backhaul, referred to as wired BSs (W-BSs), and BSs with wireless backhaul, referred to as unwired-BSs (U-BSs). In-band full-duplex wireless communications is used to connect U-BSs and W-BSs. We propose an algorithm to determine the minimum number of W-BSs and U-BSs to satisfy given cell and capacity coverage constraints. Furthermore, we apply our proposed non-dominated sorting genetic algorithm II (NSGA-II) to solve both cell planning and joint cell and backhaul planning problem to minimize the cost of planning, while maximizing the coverage simultaneously. Additionally, the considered cell planning program is developed into an optimization by including the problem of minimizing the cost of fiber backhaul deployment. In order to analyze the performance of the proposed algorithm, we study three different deployment scenarios based on different spatial distributions of users and coverage areas. The results show the superiority of our proposed NSGA-II algorithm for both cell planning and joint cell and backhaul planning to other well-known optimization algorithms. The results also reveal that there is a trade-off between cell deployment costs and SINR/rate coverage, and W-BSs are placed in congested areas to consume less resources for wireless backhauls. Similarly, a trade-off between cell and fiber deployment costs and SINR/rate coverage is observed in planning. We show that for realistic scenarios desirable solutions can be selected from the Pareto front of the introduced multi-objective problem based on given cellular operator policies.Index Terms-Cell planning, in-band full-duplex (IBFD), fiber-wireless (FiWi) networks, millimeter-wave networks, next-generation passive optical networks (NG-PONs), selfbackhauling.

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Automated Placement of Individual Millimeter-Wave Wall-Mounted Base Stations for Line-of-Sight Coverage of Outdoor Urban Areas

Cited by 30 publications

References 17 publications

Efficient Millimeter-Wave Infrastructure Placement for City-Scale ITS

Efficient Millimeter-Wave Infrastructure Placement for City-Scale ITS

Optimized Deployment of Millimeter Wave Networks for In-Venue Regions With Stochastic Users’ Orientation

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

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