Dynamic small cell placement strategies for LTE Heterogeneous Networks (original) (raw)
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Maximizing dual cell connectivity opportunities in LTE small cells deployment
2016 Twenty Second National Conference on Communication (NCC), 2016
Most of the LTE (Long Term Evolution) network operators are deploying low power small cells in hotspots like airports, shopping malls and corporate offices to meet increasing data demands. Since users are not deemed to fixed locations in such places, the network experiences uneven distribution of traffic load across the cells which degrades the average user throughput. This problem is even more severe if the deployment of small cells is unplanned. In order to address this, in this work, we propose two variant of small cell placement models: an optimal Femto placement with full power (OPT-FP) model and an opportunistic Femto placement with power control (OPPR-PC) model. These models incorporate a constraint which helps small cells providing dual cell connectivity (DCC) for as many number of users as possible and then schedule them jointly for improving their throughputs.
A novel optimal small cells deployment for next-generation cellular networks
International Journal of Electrical and Computer Engineering (IJECE), 2021
Small-cell-deployments have pulled cellular operators to boost coverage and capacity in high-demand areas (for example, downtown hot spots). The location of these small cells (SCs) should be determined in order to achieve successful deployments. In this paper, we propose a new approach that optimizes small cells deployment in cellular networks to achieve three objectives: reduce the total cost of network installation, balancing the allocation of resources, i.e. placement of each SC and their transmitted power, and providing optimal coverage area with a lower amount of interference between adjacent stations. An accurate formula was obtained to determine the optimum number of SC deployment (NSC). Finally, we derive a mathematical expression to calculate the critical-handoff-point (CHP) for neighboring wireless stations.
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IEEE Communications Magazine, 2000
Optimizing the cellular network's cell locations is one of the most fundamental problems of network design. The general objective is to provide the desired Quality-of-Service (QoS) with the minimum system cost. In order to meet a growing appetite for mobile data services, heterogeneous networks have been proposed as a cost-and energy-efficient method of improving local spectral efficiency. Whilst unarticulated cell deployments can lead to localized improvements, there is a significant risk posed to network-wide performance due to the additional interference.
LTE radio network planning with HetNets: BS placement optimization using simulated annealing
MELECON 2014 - 2014 17th IEEE Mediterranean Electrotechnical Conference, 2014
In this paper, the optimization of base station (BS) deployment is investigated. After determining an approximate number of required BSs to cover an area of interest, the positions of these BSs are determined using the simulated annealing (SA) algorithm. Deployment using SA is compared to a benchmark approach consisting of a uniform deployment of the BSs over the area of interest. Scenarios with uniform user distribution are investigated, in addition to scenarios with Gaussian distribution. These latter scenarios correspond to a hotspot case, where users are concentrated in the center of a given area and the concentration is reduced as we move away from the center. BS deployment in heterogeneous networks was also investigated, and shown to lead to better results than a network with only macrocell BSs.
Wireless Communications and Mobile Computing, 2017
The densification of serving nodes is one of the potential solutions to maximize the spectral efficiency per unit area. This is preposterous on account of conventional base stations (BS) for which site procurement is costly. Long term evolution-advanced (LTE-A) defines the idea of heterogeneous networks (HetNets), where BSs with different coverage and capacity are utilized to guarantee the quality of service (QoS) requirements of the clients. To maximize the transmission quality of the clients in the coverage holes, LTE-A also defines multihop relay (MHR) networks, where the relay stations (RSs) are also placed along with the BSs. Unfortunately, the placement approaches for HetNet and MHR serving nodes are not standardized. In this work, two different approaches like site selection with maximum service coverage (SSMSC) and site selection with minimum placement cost (SSMPC) are proposed, which identifies the required number of serving nodes, their types, and the placement locations t...
1999 IEEE 49th Vehicular Technology Conference (Cat. No.99CH36363), 1999
The cost and complexity of a network is closely related to the number of base-stations (BSs) required to achieve the system operator's service objectives. The location of BSs is not an easy task and there are numerous factors that must be taken into account when deciding the optimum position of BSs. This paper discusses the performance of three different algorithms developed to solve the BS location problem: the greedy algorithm (GR), the genetic algorithm (GA) and the combination algorithm for total optimisation (CAT). These three methods are compared and results are given for a typical test scenario.
Base-Station Location Optimization for LTE Systems with Genetic Algorithms
Minimizing the cost of a cellular network usually includes the optimum selection and location of base-stations, that meet certain coverage and capacity constraints. In the framework of LTE wireless networks, coverage and capacity planning are interrelated in terms of interference. Moreover, the ever increasing capacity demand for non-uniformly distributed users, along with mixed cell scenarios and relay nodes, makes base station location optimization a non trivial task. To address this issue we propose a genetic algorithm based methodology that optimally performs the task of basestations location by minimizing the cost of the network while fulfilling the coverage and capacity criteria. Example results are provided for case study scenarios that give useful planning insights for LTE systems.
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Lecture Notes in Computer Science, 2010
The optimal base station placement is a serious task in cellular wireless networks. In this paper we propose a method that automatically distributes the base stations on a studied scenario, maintaining coverage requirement and enabling the transmission of traffic demands distributed over the area. A city scenario with normal demands is examined and the advantages/disadvantages of this method are discussed. The planner and optimizing tasks are based on an iterative K-Means clustering method. Numerical results of coverage, as well as graphical results permit on radio coverage maps, are presented as base for main consequences. Furthermore, the final results are compared to another simple planning algorithm.
Optimal deployment of pico base stations in LTE-Advanced heterogeneous networks
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As data traffic demand in cellular networks grows exponentially, operators need to add new cell sites to keep up; unfortunately, it is costly to build and operate macrocells. Moreover, it may not be possible to obtain the needed approvals for additional macrocell sites. Recently, the 3rd Generation Partnership Project (3GPP) introduced the concept of heterogeneous networks in Long Term Evolution (LTE) Release 10, where low-power base stations (BSs) are deployed within the coverage area of a macrocell to carry traffic. However, this new type of deployment can cause more severe interference conditions than a macro-only system, due to inter-cell interference; hence, enhanced inter-cell interference coordination (eICIC) has been actively discussed in LTE Release 10. Nevertheless, eICIC cannot completely eliminate interference and, to make matters worse, high-power transmissions of the reference signals from the BSs may increase the interference level. In this paper, we propose an algorithm for deploying low-power nodes within macrocell
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