Base Station Placement Research Articles

Beyond Empirical Models: Pattern Formation Driven Placement of UAV Base Stations

This paper considers the placement of unmanned aerial vehicle base stations (UAV-BSs) with criterion of minimum UAV-recall-frequency (UAV-RF), indicating the energy efficiency of mobile UAVs networks. Several different power consumptions, including signal transmit power, on-board circuit power and the power for UAVs mobility, and the ground user density are taken into account. Instead of conventional empirical stochastic models, this paper utilizes a pattern formation system to track the instable and non-ergodic time-varying nature of user density. We show that for a single time-slot, the optimal placement is achieved when the transmit power of UAV-BSs equals their on-board circuit power. Then, for multiple time-slot duration, we prove that the optimal placement updating problem is an integer nonlinear programming coupled with an inherent integer linear programming. Since the original problem is NP-hard and cannot be solved with conventional recursive methods, we propose a sequential-Markov-greedy-decision strategy to achieve near minimal UAV-RF in polynomial time. Furthermore, we prove that the increment of UAV-RF caused by inaccurate predicted user density is proportional to the generalization error of learned patterns. Here, in regions with large area, high-rise buildings, or low user density, large sample sets are required for effective pattern formation.

Optimal Base Station Deployment with Downlink Rate Coverage Probability Constraint

The uncertainty in user locations and channel conditions makes the deployment and performance analysis of wireless networks challenging. Stochastic geometry has emerged as a powerful tool for analyzing the performance of wireless networks, assuming certain stochastic models for the distribution of both users and base stations (BSs). In this letter, seeking further precision, we derive the downlink rate coverage probability of a wireless network with deterministically known BS locations . Then, we use this result to optimize the placement of BSs while keeping the downlink rate coverage probability above a certain threshold.

Trajectory Design for Completion Time Minimization in UAV-Enabled Multicasting

This paper studies an unmanned aerial vehicle (UAV)-enabled multicasting system, where a UAV is dispatched to disseminate a common file to a set of ground terminals (GTs). We aim to design the UAV trajectory to minimize its mission completion time, while ensuring that each GT successfully recovers the file with a desired high probability. The formulated problem is nonconvex and difficult to be solved in its original form. Therefore, we first derive an effective lower bound for the success file recovery probability of each GT. The problem is then reformulated in a more tractable form, where the UAV trajectory only needs to be designed to ensure the minimum connection time constraint with each GT, during which their distance is below a certain threshold. We show that without loss of optimality, the UAV trajectory consists of connected line segments only, which can be obtained by determining the optimal set of waypoints as well as the UAV speed along the path connecting the waypoints. We propose efficient schemes for the waypoint design based on a novel concept of virtual base station placement and by applying convex optimization. Furthermore, for fixed waypoints, the optimal UAV speed is efficiently obtained by solving a linear programming problem. Numerical results show that the proposed UAV-enabled multicasting with optimized trajectory design achieves significant performance gains over other benchmark schemes.

3-D Placement of an Unmanned Aerial Vehicle Base Station for Maximum Coverage of Users With Different QoS Requirements

The need for a rapid-to-deploy solution for providing wireless cellular services can be realized by unmanned aerial vehicle base stations (UAV-BSs). To the best of our knowledge, this letter is the first in literature that studies a novel 3D UAV-BS placement that maximizes the number of covered users with different Quality-of-Service requirements. We model the placement problem as a multiple circles placement problem and propose an optimal placement algorithm that utilizes an exhaustive search (ES) over a one-dimensional parameter in a closed region. We also propose a low-complexity algorithm, namely, maximal weighted area (MWA) algorithm to tackle the placement problem. Numerical simulations are presented showing that the MWA algorithm performs very close to the ES algorithm with a significant complexity reduction.

LOCATION AWARE ALGORITHM FOR ENERGY EFFICIENT HETEROGENEOUS NETWORK

The placement of small base stations (BSs) in heterogeneous network (HetNet) has recently attracted increasing interest to optimize the network energy efficiency (EE). In this paper, we propose a new energy efficient algorithm for small BSs placement in HetNet with a constrained spatial model that is aimed at supporting the decisions in the planning process where to locate new small BSs. The investigation analysis involves both uniform and non-uniform traffic load distribution across the coverage area. For uniform user distribution, our simulation results have shown that the EE of HetNet improved as the small BSs placed towards macrocell edges. However, this prediction is true for the uniform distribution and outcomes could change for a non-uniform distribution. In addition, the improper position of small BSs, i.e., at the cell edge of macrocell instead of the center of the hotspots, result in degrading the EE of HetNet as the number of users being close to the small BSs decreases compared to the uniform case. Finally, our findings tend to agree with suggestions to use a few micro BS (MieNBs) rather than to use a large number of pico BS (PeNBs) to perform energy saving in case of network with spatially spread users.

Optimal base station location in LTE heterogeneous network using non-dominated sorting genetic algorithm II

The main objective of the radio network planning is to provide a cost-effective solution for the radio network in terms of coverage, capacity and quality of service. The network planning process and design criteria vary from region to region depending on the dominant factor, which could be capacity or coverage. However, base stations deployment optimisation is an important and crucial process in cellular network planning. It represents a major challenge for mobiles operators and considered as NP-hard problem. In this work, we study the placement of base station and configuration with an optimisation approach. In addition, a mathematical model based on set covering problem is suggested to solve the BS positioning. The main objective of the model is to maximise the coverage and minimising the financial cost. Non-Dominate Sorting Genetic Algorithm (NSGA II) is applied to find a suitable solution. Simulation results and discussions on the performance of suggested algorithm are provided.

Multi-agent target searching with time constraints using game-theoretic approaches

PurposeThe purpose of this paper is to propose a model for a target searching problem in a two-dimensional region with time constraints. The proposed model facilitates the search operation by minimizing the mission time and fuel usage, and the search operation is performed by a set of agents divided into a number of groups.Design/methodology/approachThe authors have applied optimization techniques, Cartesian product, inclusion–exclusion principle, cooperative strategy, Shapley value, fuzzy Shapley function and Choquet integral to model the problem.FindingsThe proposed technique optimizes the placement of base stations that minimizes the sortie length of the agents. The results show that the cooperative strategy outperforms the non-cooperative strategy. The Shapley values quantify the rewards of each group based on their contributions to the search operation, whereas the fuzzy Shapley values determine the rewards of each group based on their contributions and level of cooperation in the search operation.Practical implicationsThe proposed model can be applied to model many real-time problems such as patrolling in international borders, urban areas, forests and managing rescue operations after natural calamities, etc. Therefore, defence organizations, police departments and other operation management sectors will be benefitted by applying the proposed approach.Originality/valueTo the best of the authors’ knowledge, determining the optimal locations of base stations in a region is not explored in the existing works on target searching problems with fuel constraints. The proposed approach to cooperatively search the targets in a region is new. Introducing the Shapley function and fuzzy Shapley function is a novel idea to quantify the rewards of each group based on their contributions and level of cooperation in the search operation. This paper addresses these unexplored areas.

3-D Placement of an Unmanned Aerial Vehicle Base Station (UAV-BS) for Energy-Efficient Maximal Coverage

Unmanned aerial vehicle mounted base stations (UAV-BSs) can provide wireless services in a variety of scenarios. In this letter, we propose an optimal placement algorithm for UAV-BSs that maximizes the number of covered users using the minimum transmit power. We decouple the UAV-BS deployment problem in the vertical and horizontal dimensions without any loss of optimality. Furthermore, we model the UAV-BS deployment in the horizontal dimension as a circle placement problem and a smallest enclosing circle problem. Simulations are conducted to evaluate the performance of the proposed method for different spatial distributions of the users.

Modulation aware cluster size optimisation in wireless sensor networks

ABSTRACTWireless sensor networks (WSNs) play a great role because of their numerous advantages to the mankind. The main challenge with WSNs is the energy efficiency. In this paper, we have focused on the energy minimisation with the help of cluster size optimisation along with consideration of modulation effect when the nodes are not able to communicate using baseband communication technique. Cluster size optimisations is important technique to improve the performance of WSNs. It provides improvement in energy efficiency, network scalability, network lifetime and latency. We have proposed analytical expression for cluster size optimisation using traditional sensing model of nodes for square sensing field with consideration of modulation effects. Energy minimisation can be achieved by changing the modulation schemes such as BPSK, 16-QAM, QPSK, 64-QAM, etc., so we are considering the effect of different modulation techniques in the cluster formation. The nodes in the sensing fields are random and uniformly deployed. It is also observed that placement of base station at centre of scenario enables very less number of modulation schemes to work in energy efficient manner but when base station placed at the corner of the sensing field, it enable large number of modulation schemes to work in energy efficient manner.

Measurement and Analysis of Quality of Service of Mobile Networks in Afghanistan – End User Perspective

Enhanced Quality of Service (QoS) and satisfaction of mobile phone user are major concerns of a service provider. In order to manage network efficiently and to provide enhanced end to end Quality of Experience (QoE), operator is expected to measure and analyze QoS from various perspectives and at different relevant points of network. The scope of this paper is measurement and statistically analysis of QoS of mobile networks from end user perspective in Afghanistan. The study is based on primary data collected on random basis from 1,515 mobile phone users of five cellular operators. The paper furthermore proposes adequate technical solutions to mobile operators in order to address existing challenges in the area of QoS and to remain competitive in the market. Based on the result of processed data, considering geographical locations, population and telecom regulations of the government, authors recommend deployment of small cells (SCs), increasing number of regular performance tests, optimal placement of base stations, increasing number of carriers, and high order sectorization as proposed technical solutions.

A Constellation Design Methodology Based on QoS and User Demand in High-Altitude Platform Broadband Networks

An investigation into the constellation design methodology of high-altitude platform (HAP) broadband networks is presented. The quality of service (QoS) metrics and user demand model are established in the HAP broadband networks. Each HAP is seen as a mobile base station, and a methodology of mobile base station placement is proposed with QoS and user demand guarantee for the first time. The multiple HAP coverage is analyzed with link geometry based on the single HAP coverage model. Besides, a cost-efficient optimization design framework for the HAP constellation is established by optimizing the design vector to maximize the network capacity per cost under the constraints of QoS metrics. In addition, the optimization model and improved artificial immune algorithm based on immune review are designed, and performance of the proposed method is demonstrated through in-depth numerical simulations. Simulation results show that the proposed constellation design method can effectively solve the problem of the mobile base station layout in the HAP broadband networks.

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

In this letter, advanced concepts in polygon computational geometry are combined to automate the placement of thousands of millimeter-wave (mmWave) wall-mounted base stations over two large urban areas, and to gather their line-of-sight coverage statistics; this is the first large-scale fully-automated channel modeling study of mmWave cells over massive open building data. This allows for a more accurate modeling of small-cell mmWave access networks, which are currently considered as a strong candidate technology for providing gigabit rates to dense urban areas.

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English

Energy-efficient placement and sleep control of relay nodes in heterogeneous small cell networks

Small cell (SC) provides low-power radio access with a relatively smaller coverage range than a macrocell. It has been regarded as a key solution for offloading traffic in the future 5G system. Previous works on energy-efficient placement of base stations (BSs) in cellular networks introduced placement and sleep control of low-power relay stations (RSs) to reduce the total power consumption for downlink transmission from BSs to users. As compared with legacy RSs, SC can serve as an RS with a larger coverage range though consuming a bit more circuit power. Hence, this work additionally considers to deploy small cells (SCs) in a one-dimensional highway cellular network with BSs and legacy RSs, and further models the power consumption minimization problem for placement and sleep control of legacy RSs and SCs in this network. Since the problem is hard to be solved analytically, a genetic algorithm with dynamic operator-selection mechanism is further proposed to resolve this problem. Performance of the proposed algorithm is evaluated via simulation with a practical experimental parameter setting.

Energy efficient positioning of mobile base stations to improve wireless sensor network lifetime

Base station placement problem has concerned the attention of lot of researchers as it has a major impact on the lifetime of wireless sensor network. This paper suggests using multiple mobile base stations and proposes a near optimal solution for maximising the lifetime of wireless sensor network. The base station placement problem relies on the idea of discretising the search space and is formulated as an optimisation problem. The optimum positions for base stations are obtained as the solution to an integer linear programming (ILP) formulation. The contribution of our paper is twofold. First we have offered a novel technique to transform the infinite solution space to a finite space with promising performance. Second we have formulated an ILP formulation to determine best locations for positioning the base station. We expand our contribution further to a distributed protocol which will provide a completely distributed and localised solution to the placement problem.

Optimal sink placement in backbone assisted wireless sensor networks

This article proposes a scheme for selecting the best site for sink placement in WSN applications employing backbone assisted communications. By placing the sink at a specific position, energy scavenging and delay constraints can effectively be controlled. In contrast to the conventional scheme for base station placement at the geographical centre or random placement at the end of the region of interest, the proposed scheme places the base station at either the graph theoretical centre or centroid of the backbone connecting nodes in the region of interest. This strategy shows a considerable reduction in the total number of hops that each packet needs to travel to reach the sink. The proposed scheme is applied on all the families of graphs prevalent in backbone assisted sensor networks to confirm the performance consistency and improvement in network parameters of the communication backbone measured in terms of delay, the carried load and the total energy consumption, eventually affected by the average number of hops for the message to reach the sink.

Base Station Placement for Wireless Sensor Network Positioning System via Lexicographical Stratified Programming

This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

Optimal location planning of relay-based next generation wireless access networks

Use of relays is considered one of the most effective ways for capacity enhancement and coverage extension in next-generation broadband wireless access networks (BWAN). The paper investigates the location planning problem in BWANs, aiming at an optimal deployment of relay stations and base stations to enhance capacity. We develop formulations in mixed integer linear programming to effectively capture various planning policies that govern relay and base station placement. Case studies are conducted to verify the effectiveness of the proposed formulations. We show that the same traffic demand can be satisfied with up to 73 % fewer relay stations with a slight (6 %) decrease in the overall network capacity, compared with our benchmark. Based on the developed formulations, we introduce a maximin objective function to properly distribute excess bandwidth to all subscriber stations rather than assigning it to a single one, which surprisingly leads to a significant gain in the rate allocated to each subscriber station.

Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks

Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators’ careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system throughput performance.

Uplink-Oriented Deployment Guidelines and Auto-Configuration Algorithms for Co-Channel W-CDMA Heterogeneous Networks

The operation of wireless cellular networks can be efficiently supported by secondary small cells that are deployed at traffic hotspots within the coverage area of the primary macro cells. To this end, we examine the conditions under which the secondary base stations can share the same communication channel with the primary base stations under the constraint of a predefined quality of service, typical for uplink communications. In particular, requiring a target signal-to-interference-and-noise ratio (SINR) for each transmission accommodated in a common interference-limited channel, we formally assess the impact of the secondary infrastructure in a W-CDMA system on the global achievability of the uplink target SINRs via distributed closed-loop power control. The effects of cell load and inter-cell coupling are distinguished. As a result, we define solutions to the problems of base station placement, cell coverage optimization, and target SINR adaptation in W-CDMA heterogeneous networks, as well as discuss their compatibility with standard downlink-oriented deployment guidelines. Analytical conclusions are validated numerically by 3GPP-compliant simulations of a W-CDMA heterogeneous network.