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Artículos de revistas sobre el tema "Inter-cell interference coordination (ICIC)"

Autor: Grafiati

Publicado: 25 de mayo de 2024

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1

Yussuff, Abayomi Isiaka O. y Abdul-Rasaq A. Bakare. "Performance evaluation of inter-cell interference prediction in massive MIMO". Applied Journal of Physical Science 3, n.º 1 (30 de abril de 2021): 28–36. http://dx.doi.org/10.31248/ajps2021.039.

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This paper presents inter-cell interference prediction in massive multiple input multiple output. The rapid demand for widespread multimedia services notwithstanding the deployment of 4G in Lagos, Nigeria and the urgent need to upgrade to 5G networks with downlink and uplink data capacities of not less than 300 and 60 Mbps, respectively for at least 95% penetration rate at any instantaneous time; there is a possibility of experiencing crosstalk and adjacent inter-cell interference within the receiving antennas. 5G inter-cell interference prediction scheme that employs LTE performance index using locally sourced data from Huawei Nigeria limited was presented. The performances of the currently deployed LTE network were evaluated by employing performance metrics such as uplink and downlink capacities and recommending a possible inter-cell interference mitigation technique to be implemented in the deployment of 5G network in Lagos. The identified key performance metrics used include over the air emulation, carrier to interference plus noise ratio, peak RLC throughput, coverage probability, and the map-based model. Hence, ICIC static coordination algorithm, which comprise NOICIC, Hard FFR, PFR, SFR and SFFR were analyzed. With static ICIC algorithm, the coverage probability was 78% for receiving more than 20 kbps, with cell-edge users using resources of centre-users and with edge-users of neighbouring cells using different resource block; therefore reducing interference and consequently increasing throughput when there is static ICIC coordination. Implementing the static ICIC schemes on the 5G network when deployed in Lagos will improve the average downlink throughput over what is currently attainable with the 4G network in use at the moment

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2

Aal-nouman, Mohammed I., Osamah Abdullah y Noor Qusay A. Al Shaikhli. "Inter-cell interference mitigation using adaptive reduced power subframes in heterogeneous networks". International Journal of Electrical and Computer Engineering (IJECE) 11, n.º 4 (1 de agosto de 2021): 3275. http://dx.doi.org/10.11591/ijece.v11i4.pp3275-3284.

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With the remarkable impact and fast growth of the mobile networks, the mobile base stations have been increased too, especially in the high population areas. These base stations will be overloaded by users, for that reason the small cells (like pico cells) were introduced. However, the inter-cell interference will be high in this type of Heterogeneous networks. There are many solutions to mitigate this interference like the inter-cell interference coordination (ICIC), and then the further enhanced ICIC (Fe-ICIC) where the almost blank subframes are used to give priority to the (victim users). But it could be a waste of bandwidth due to the unused subframes. For that reason, in this paper, we proposed an adaptive reduced power subframe that reduces its power ratio according to the user’s signal-to-interference-plus-noise ratio (SINR) in order to get a better throughput and to mitigate the intercell interference. When the user is far from the cell, the case will be considered as an edge user and will get a higher priority to be served first. The results show that the throughput of all users in the macro cells and pico cell will be improved when applying the proposed scheme in term of throughput for the users and the cells.

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Fernández Campo, Betty Nayibe, Lesly Alejandra González Camacho y Claudia Milena Hernández Bonilla. "IMPACTO DEL REUSO DE FRECUENCIA FRACCIONAL EN LA REDUCCIÓN DE INTERFERENCIA INTERCELDA EN LTE." Revista de Investigaciones Universidad del Quindío 25, n.º 1 (31 de mayo de 2014): 28–39. http://dx.doi.org/10.33975/riuq.vol25n1.146.

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La Interferencia Inter-Celda (ICI, Inter-Cell Interference) es un problema que desafía el desempeño de las redes Evolución a Largo Término (LTE, Long Term Evolution), sin embargo existen técnicas de Coordinación de Interferencia Inter-Celda (ICIC, Inter-Cell Interference Coordination) como el Reuso de Frecuencia Fraccional (FFR, Fractional Frequency Reuse) que permiten mitigar dicha interferencia y mejorar el desempeño de los Equipos de Usuario (UE, User Equipment), especialmente aquellos terminales situados en el borde de la celda. Este artículo analiza el desempeño de la técnica Reuso de Frecuencia Fraccional (FFR) en LTE, en función de dos parámetros de configuración: Umbral de Relación Señal a Ruido más Interferencia (SINR, Signal to Interference plus Noise Ratio) y partición de Ancho de Banda (BW, Band Width). Se evalúa la capacidad e interferencia mediante diagramas de dispersión, curvas de Función de Probabilidad Acumulada Empírica (ECDF, Empirical Cumulative Density Function) y cálculos estadísticos.

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4

Kosta, Chrysovalantis, Bernard Hunt, Atta UI Quddus y Rahim Tafazolli. "On Interference Avoidance Through Inter-Cell Interference Coordination (ICIC) Based on OFDMA Mobile Systems". IEEE Communications Surveys & Tutorials 15, n.º 3 (2013): 973–95. http://dx.doi.org/10.1109/surv.2012.121112.00037.

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5

Wang, Jian-Sing y Jeng-Shin Sheu. "Study of Handover Techniques for 4G Network MIMO Systems". International Journal of Communications 15 (23 de abril de 2021): 10–16. http://dx.doi.org/10.46300/9107.2021.15.3.

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For the upcoming 4G systems, network multiple-input multiple-output (MIMO) and inter-cell interference coordination (ICIC) are two of key techniques adopted in 4G systems to mitigate the serious inter-cell interference (ICI) and improve coverage and cell-edge throughput. Network MIMO is referred to as coordinated multi-point (CoMP) in LTE-A. In this paper, we propose a simulation platform to analyze the handover issue for downlink CoMP transmissions in LTE-A cellular systems. Among the variety of ICIC strategies, we apply the widely adopted soft frequency reuse (SFR) and the fractional frequency reuse (FFR) schemes. Both schemes are based on the idea of applying a frequency reuse factor of one in cell-center areas, and a higher reuse factor in cell-edge areas. Therefore, the ICI is reduced at the expense of the available frequency resources for each cell.

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6

N. Sirhan, Najem y Manel Martinez-Ramon. "Radio Resource Management for Eicic, Comp, Relaying and Back-hauls Techniques in LTE-advanced Networks: Concepts and a Literature Survey". International Journal of Wireless & Mobile Networks 14, n.º 4 (31 de agosto de 2022): 41–61. http://dx.doi.org/10.5121/ijwmn.2022.14404.

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Frequency reuse in cells is one of the strategies that LTE (Long Term Evolution) uses to maximize the spectrum efficiency. However, it leads to an interference among the cells, especially at the cell edges where the probability for a cell-edge user to be scheduled on a resource block that is being transmitted by the neighbouring cell is high; consequently, the interference is high. In-order to mitigate Inter-Cell Interference (ICI), Inter-Cell Interference Coordination (ICIC) was proposed by the Third Generation Partnership Project (3GPP) standards for the LTE network, and later on, the enhanced Inter-Cell Interference Coordination (eICIC) was proposed for the LTE-Advanced network. ICIC reduces cell-edge interference on traffic channels from neighbouring cells by the use of three interference reduction schemes that works in the power and frequency domain, and they are based on lowering the power of some channels to limit their reception to the users that are close to the base station, and by reducing the chance of frequency overlap. eICIC was proposed to handle ICI in Heterogeneous Network (HetNet) deployments. It reduces the interference on both the traffic and control channels. It uses power, frequency and also time domain to mitigate intra-frequency interference in HetNets. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can reduce the ICI and improve the cell average and cell-edge user throughput is the Coordinated Multi-Point (CoMP) transmission/reception technique. CoMP can increase the cell average and cell edge user throughput in both the uplink and downlink transmission by joint scheduling and data processing in multiple cells/eNBs. Another technique that was proposed by the 3GPP for the LTE-Advanced network that can improve the LTE network coverage in difficult conditions is to deploy Relay Nodes (RNs). In this paper, we survey Radio Resource Management (RRM) for some of the techniques that are used with LTE-A. The included techniques in this paper are; the ICIC, eICIC, CoMP, Relaying and Back-hauls. We start by explaining the concepts of these techniques. Then, by summarizing the radio resource management approaches that were proposed in the literature for these techniques. And finally, we provide some concluding remarks in the last section.

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7

Bin Sediq, Akram, Rainer Schoenen, Halim Yanikomeroglu y Gamini Senarath. "Optimized Distributed Inter-Cell Interference Coordination (ICIC) Scheme Using Projected Subgradient and Network Flow Optimization". IEEE Transactions on Communications 63, n.º 1 (enero de 2015): 107–24. http://dx.doi.org/10.1109/tcomm.2014.2367020.

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8

Diógenes do Rego, Iago y Vicente A. de Sousa. "Solution for Interference in Hotspot Scenarios Applying Q-Learning on FFR-Based ICIC Techniques". Sensors 21, n.º 23 (27 de noviembre de 2021): 7899. http://dx.doi.org/10.3390/s21237899.

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This work explores interference coordination techniques (inter-cell interference coordination, ICIC) based on fractional frequency reuse (FFR) as a solution for a multi-cellular scenario with user concentration varying over time. Initially, we present the problem of high user concentration along with their consequences. Next, the use of multiple-input multiple-output (MIMO) and small cells are discussed as classic solutions to the problem, leading to the introduction of fractional frequency reuse and existing ICIC techniques that use FFR. An exploratory analysis is presented in order to demonstrate the effectiveness of ICIC techniques in reducing co-channel interference, as well as to compare different techniques. A statistical study was conducted using one of the techniques from the first analysis in order to identify which of its parameters are relevant to the system performance. Additionally, another study is presented to highlight the impact of high user concentration in the proposed scenario. Because of the dynamic aspect of the system, this work proposes a solution based on machine learning. It consists of changing the ICIC parameters automatically to maintain the best possible signal-to-interference-plus-noise ratio (SINR) in a scenario with hotspots appearing over time. All investigations are based on ns-3 simulator prototyping. The results show that the proposed Q-Learning algorithm increases the average SINR from all users and hotspot users when compared with a scenario without Q-Learning. The SINR from hotspot users is increased by 11.2% in the worst case scenario and by 180% in the best case.

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9

Kosta, C., B. Hunt, A. U. Quddus y R. Tafazolli. "A Distributed Method of Inter-Cell Interference Coordination (ICIC) Based on Dual Decomposition for Interference-Limited Cellular Networks". IEEE Communications Letters 17, n.º 6 (junio de 2013): 1144–47. http://dx.doi.org/10.1109/lcomm.2013.040913.130224.

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10

Mehta, Mahima, Osianoh Glenn Aliu, Abhay Karandikar y Muhammad Ali Imran. "A SELF-ORGANIZED RESOURCE ALLOCATION USING INTER-CELL INTERFERENCE COORDINATION (ICIC) IN RELAY-ASSISTED CELLULAR NETWORKS". ICTACT Journal on Communication Technology 02, n.º 02 (1 de junio de 2011): 300–313. http://dx.doi.org/10.21917/ijct.2011.0043.

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11

Ahmad, Ishtiaq, Sajjad Hussain, Sarmad Nozad Mahmood, Hala Mostafa, Ahmed Alkhayyat, Mohamed Marey, Ali Hashim Abbas y Zainab Abdulateef Rashed. "Co-Channel Interference Management for Heterogeneous Networks Using Deep Learning Approach". Information 14, n.º 2 (20 de febrero de 2023): 139. http://dx.doi.org/10.3390/info14020139.

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The co-channel interference for mobile users (MUs) of a public safety network (PSN) in the co-existence of heterogeneous networks such as unmanned aerial vehicles (UAVs) and LTE-based railway networks (LRNs) needs a thorough investigation, where UAVs are deployed as mobile base stations (BSs) for cell-edge coverage enhancement. Moreover, the LRN is employed for the train, and its control signal demands high reliability and low latency. It is necessary to provide higher priority to LRN users when allocating resources from shared radio access channels (RACs). By considering both sharing and non-sharing of RACs, co-channel interference was analyzed in the downlink network of the PSN, UAV, and LRN. By offloading more PSN MUs to the LRN or UAVs, the resource utilization of the LRN and UAV BSs was enhanced. In this paper, we aimed to adopt deep-learning (DL)-based enhanced inter-cell interference coordination (eICIC) and further enhanced ICIC (FeICIC) strategies to deal with the interference from the PSN to the LRN and UAVs. Moreover, a DL-based coordinated multipoint (CoMP) for coordinated scheduling technique was utilized along with FeICIC and eICIC to enhance the performance of PSN MUs. In the simulation results, the performance of DL-based interference management was compared with simple eICI, FeICIC, and coordinated scheduling CoMP. The DL-based FeICIC and CoMP for coordinated scheduling performed best with shared RACs.

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12

An, SangHoon y KyungHi Chang. "Resource Management for Collaborative 5G-NR-V2X RSUs to Enhance V2I/N Link Reliability". Sensors 23, n.º 8 (14 de abril de 2023): 3989. http://dx.doi.org/10.3390/s23083989.

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In the development of autonomous driving technology, 5G-NR vehicle-to-everything (V2X) technology is a key technology that enhances safety and enables effective management of traffic information. Road-side units (RSUs) in 5G-NR V2X provide nearby vehicles with information and exchange traffic, and safety information with future autonomous vehicles, enhancing traffic safety and efficiency. This paper proposes a communication system for vehicle networks based on a 5G cellular network with RSUs consisting of the base station (BS) and user equipment (UE), and validates the system performance when providing services from different RSUs. The proposed approach maximizes the utilization of the entire network and ensures the reliability of V2I/V2N links between vehicles and each RSU. It also minimizes the shadowing area in the 5G-NR V2X environment, and maximizes the average throughput of vehicles through collaborative access between BS- and UE-type RSUs. The paper applies various resource management techniques, such as dynamic inter-cell interference coordination (ICIC), coordinated scheduling coordinated multi-point (CS-CoMP), cell range extension (CRE), and 3D beamforming, to achieve high reliability requirements. Simulation results demonstrate improved performance in outage probability, reduced shadowing area, and increased reliability through decreased interference and increased average throughput when collaborating with BS- and UE-type RSUs simultaneously.

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13

Zhou, Xiaodi, Yuxiang Chen y Zhuo Chen. "Further Research on Frequency Allocation (19-Cell System) Method based on IFR and FFR". Highlights in Science, Engineering and Technology 27 (27 de diciembre de 2022): 561–69. http://dx.doi.org/10.54097/hset.v27i.3816.

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Many of the most advanced technology has a basic need for efficient telecommunication. In order to achieve this goal, the team should allocate those frequency channels in an intelligent way so that the interference can be reduced to the maximum extent. Here the team introduced a new method based on IFR3&IFR1 (Integer frequency reuse) in a 19-cell network, but also apply the FFR (fractional frequency reuse) method to reduce the interference ulteriorly. In the pure IFR situation, the integer frequency reuse factor and the cellular network specification collectively decide the network capacity. While in FFR only a fraction of the whole bandwidth is used by the users in the edge. By contrast, the users near the BS can make use of the total bandwidth. The cell is divided into an outer and an inner part in this effective way. Fractional Frequency Reuse (FFR) and its derivative method are accepted widely in the downlink (DL) inter-cell interference coordination(ICIC) schemes. The team also optimized the FFR method by measuring the distance in a more precise way. The team utilized Matlab to make a simulation of the system applying the new method and come to a couple of reasonable conclusions by comparing the FFR+IFR3 with FFR+IFR3. FFR+IFR3 has a better performance against FFR+IFR1 in a system whose distance between each cell is with more accuracy. While the average number of users per cell and transmission power for cell edge have little impact on average capacity. When the SNR increases, the network capacity starts steep but later flattens. Our method is more intelligent and can minish interference efficiently.

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14

Adeel, Ahsan, Hadi Larijani, Abbas Javed y Ali Ahmadinia. "Impact of Learning Algorithms on Random Neural Network based Optimization for LTE-UL Systems". Network Protocols and Algorithms 7, n.º 3 (30 de noviembre de 2015): 157. http://dx.doi.org/10.5296/npa.v7i3.8295.

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This paper presents an application of context-aware decision making to the problem of radio resource management (RRM) and inter-cell interference coordination (ICIC) in long-term evolution-uplink (LTE-UL) system. The limitations of existing analytical, artificial intelligence (AI), and machine learning (ML) based approaches are highlighted and a novel integration of random neural network (RNN) based learning with genetic algorithm (GA) based reasoning is presented. In first part of the implementation, three learning algorithms (gradient descent (GD), adaptive inertia weight particle swarm optimization (AIWPSO), and differential evolution (DE)) are applied to RNN and two learning algorithms (GD and levenberg-marquardt (LM)) are applied to artificial neural network (ANN). In second part of the implementation, the GA based reasoning is applied to the trained ANN and RNN models for performance optimization. Finally, the ANN and RNN based optimization results are compared with the state-of-the-art fractional power control (FPC) schemes in terms of user throughput and power consumption. The simulation results have revealed that an RNN-DE (RNN trained with DE algorithm) based cognitive engine (CE) can provide up to 14% more cell capacity along with 6dBm and 9dBm less user power consumption as compared to RNN-GD (RNN trained with GD algorithm) and FPC methods respectively.

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15

Kumbhar, Abhaykumar. "Performance Improvement Using ICIC for UAV-Assisted Public Safety Networks with Clustered Users during Emergency". Telecom 4, n.º 4 (20 de noviembre de 2023): 816–35. http://dx.doi.org/10.3390/telecom4040036.

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The application of drones, also known as unmanned aerial vehicles deployed as unmanned aerial base stations (UABSs), has received extensive interest for public safety communications (PSC) to fill the coverage gaps and establish ubiquitous connectivity. In this article, we design a PSC LTE-Advanced air–ground-based HetNet (AG-HetNet) that is a scenario representation of a geographical area during and after a disaster. As part of the AG-HetNet infrastructure, we have UABSs and ground user equipment (GUE) flocking together in clusters at safe places or evacuation shelters. AG-HetNet uses cell range expansion (CRE), intercell interference coordination (ICIC), and 3D beamforming techniques to ensure ubiquitous connectivity. Through system-level simulations and using a brute-force technique, we evaluate the performance of the AG-HetNet in terms of fifth-percentile spectral efficiency (5pSE) and coverage probability. We compare system-wide 5pSE and coverage probability when UABSs are deployed on a hexagonal grid and for different clustering distributions of GUEs. The results show that reduced power subframes (FeICIC) defined in 3GPP Release-11 can provide practical gains in 5pSE and coverage probability than the 3GPP Release-10 with almost blank subframes (eICIC).

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16

Wigren, Torbjörn. "Wireless interference power estimation for inter-cell interference coordination". IET Communications 9, n.º 12 (13 de agosto de 2015): 1539–46. http://dx.doi.org/10.1049/iet-com.2014.0831.

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HIGUCHI, Kenichi, Yoshiko SAITO y Seigo NAKAO. "Inter-Cell Interference Coordination Method Based on Coordinated Inter-Cell Interference Power Control in Uplink". IEICE Transactions on Communications E98.B, n.º 7 (2015): 1357–62. http://dx.doi.org/10.1587/transcom.e98.b.1357.

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18

Trejo Narváez, Omar Albeiro y Víctor Fabián Miramá Pérez. "Machine learning algorithms for inter-cell interference coordination". Sistemas y Telemática 16, n.º 46 (6 de julio de 2018): 37–57. http://dx.doi.org/10.18046/syt.v16i46.3034.

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The current LTE and LTE-A deployments require larger efforts to achieve the radio resource management. This, due to the increase of users and the constantly growing demand of services. For this reason, the automatic optimization is a key point to avoid issues such as the inter-cell interference. This paper presents several proposals of machine-learning algorithms focused on this automatic optimization problem. The research works seek that the cellular systems achieve their self-optimization, a key concept within the self-organized networks, where the main objective is to achieve that the networks to be capable to automatically respond to the particular needs in the dynamic network traffic scenarios.

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Zhang, Yinghai, Fan Zhang, Yan zhou, Gaofeng Cui y Weidong Wang. "Inter-Cell Interference Coordination Based on Shared Relay". Physics Procedia 25 (2012): 1909–18. http://dx.doi.org/10.1016/j.phpro.2012.03.329.

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Mahmood, Nurul Huda, Klaus Ingemann Pedersen y Preben Mogensen. "Interference Aware Inter-Cell Rank Coordination for 5G Systems". IEEE Access 5 (2017): 2339–50. http://dx.doi.org/10.1109/access.2017.2672799.

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Bertrand, Moubagou Deflandre y Chang Yong Yu. "Base Station Coordination towards an Effective Inter-cell Interference Mitigation". International Journal of Future Generation Communication and Networking 8, n.º 2 (30 de abril de 2014): 45–58. http://dx.doi.org/10.14257/ijfgcn.2015.8.2.05.

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Bertrand, Moubagou Deflandre y Yong Yu Chang. "Base Station Coordination towards an Effective Inter-cell Interference Mitigation". International Journal of Future Generation Communication and Networking 8, n.º 2 (30 de abril de 2015): 45–58. http://dx.doi.org/10.14257/ijfgcn.2015.8.2.5.

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23

Zhang, Zihan y Guanding Yu. "FdICIC: Inter-cell Interference Coordination for Full-Duplex Cellular Systems". Wireless Personal Communications 101, n.º 1 (14 de mayo de 2018): 1–22. http://dx.doi.org/10.1007/s11277-018-5627-3.

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Padmaloshani, Palanisamy y Sivaraj Nirmala. "Semi‐distributed dynamic inter‐cell interference coordination scheme for interference avoidance in heterogeneous networks". ETRI Journal 42, n.º 2 (abril de 2020): 175–85. http://dx.doi.org/10.4218/etrij.2018-0362.

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Hassen, Wafa Ben, Mériem Afif y Sami Tabbane. "Interference Mitigation Through Inter-Cell Interference Coordination Using Virtual PRB Allocation in 4G Networks". Wireless Personal Communications 90, n.º 3 (4 de junio de 2016): 1179–209. http://dx.doi.org/10.1007/s11277-016-3384-8.

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Deb, Supratim, Pantelis Monogioudis, Jerzy Miernik y James P. Seymour. "Algorithms for Enhanced Inter-Cell Interference Coordination (eICIC) in LTE HetNets". IEEE/ACM Transactions on Networking 22, n.º 1 (febrero de 2014): 137–50. http://dx.doi.org/10.1109/tnet.2013.2246820.

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Kucera, Stepan y David Lopez-Perez. "Inter-Cell Interference Coordination for Control Channels in LTE Heterogeneous Networks". IEEE/ACM Transactions on Networking 24, n.º 5 (octubre de 2016): 2872–84. http://dx.doi.org/10.1109/tnet.2015.2495270.

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Brehm, Michael y Ravi Prakash. "Proactive resource allocation optimization in LTE with inter-cell interference coordination". Wireless Networks 20, n.º 5 (27 de octubre de 2013): 945–60. http://dx.doi.org/10.1007/s11276-013-0657-y.

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Zhang, Xinchen y Martin Haenggi. "A Stochastic Geometry Analysis of Inter-Cell Interference Coordination and Intra-Cell Diversity". IEEE Transactions on Wireless Communications 13, n.º 12 (diciembre de 2014): 6655–69. http://dx.doi.org/10.1109/twc.2014.2339273.

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FUSHIKI, Masashi, Noriaki MIYAZAKI, Xiaoqiu WANG y Satoshi KONISHI. "Analysis on Effectiveness of TDM Inter-Cell Interference Coordination in Heterogeneous Networks". IEICE Transactions on Communications E96.B, n.º 6 (2013): 1318–26. http://dx.doi.org/10.1587/transcom.e96.b.1318.

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Sciancalepore, Vincenzo, Ilario Filippini, Vincenzo Mancuso, Antonio Capone y Albert Banchs. "A Multi-Traffic Inter-Cell Interference Coordination Scheme in Dense Cellular Networks". IEEE/ACM Transactions on Networking 26, n.º 5 (octubre de 2018): 2361–75. http://dx.doi.org/10.1109/tnet.2018.2866410.

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ZHANG, Hui, Xiao-dong XU, Jing-ya LI, Xiao-feng TAO, Svensson Tommy y Botella Carmen. "Performance of power control in inter-cell interference coordination for frequency reuse". Journal of China Universities of Posts and Telecommunications 17, n.º 1 (febrero de 2010): 37–43. http://dx.doi.org/10.1016/s1005-8885(09)60421-0.

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Simsek, Meryem, Mehdi Bennis y Ismail Guvenc. "Learning Based Frequency- and Time-Domain Inter-Cell Interference Coordination in HetNets". IEEE Transactions on Vehicular Technology 64, n.º 10 (octubre de 2015): 4589–602. http://dx.doi.org/10.1109/tvt.2014.2374237.

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Rahman, Mahmudur y Halim Yanikomeroglu. "Enhancing cell-edge performance: a downlink dynamic interference avoidance scheme with inter-cell coordination". IEEE Transactions on Wireless Communications 9, n.º 4 (abril de 2010): 1414–25. http://dx.doi.org/10.1109/twc.2010.04.090256.

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Younes, Balboul y Najiba El Amrani El Idrissi. "Inter-cell Interference Mitigation through Flexible Resource Reuse, LP-OFDM and Coordination techniques for LTE Advanced in Dense Urban Area". Indonesian Journal of Electrical Engineering and Computer Science 3, n.º 3 (1 de septiembre de 2016): 527. http://dx.doi.org/10.11591/ijeecs.v3.i3.pp527-533.

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<p><em>The inter-cell interference problem is a key issue in LTE Advanced system especially in dense urban environments. This paper present a new inter-cell interference reduction technique for LTE Advanced downlink system in dense urban area based on a new coordination algorithm with the use of linear precoding OFDM, coordination between cells and power management techniques. The objective of our new technique is to improve cell edge and centre capacity in LTE Advanced downlink system. For this purpose, we prove with real time simulations using Matlab that the S.F.R and P.F.R scheme with our algorithm is a good candidate to enhance the average cell capacity and edge user experience, without sacrificing the average cell throughput.</em><br /><strong></strong></p>

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Yoon, Jonghun y Ganguk Hwang. "Distance-Based Inter-Cell Interference Coordination in Small Cell Networks: Stochastic Geometry Modeling and Analysis". IEEE Transactions on Wireless Communications 17, n.º 6 (junio de 2018): 4089–103. http://dx.doi.org/10.1109/twc.2018.2819998.

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37

Kim, Byoung-June, Haesung Park y Duk Kyung Kim. "Inter-cell Interference Coordination Method Based on Active Antenna System in Heterogeneous Networks". Journal of Korea Information and Communications Society 39A, n.º 9 (30 de septiembre de 2014): 548–56. http://dx.doi.org/10.7840/kics.2014.39a.9.548.

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38

Pedersen, K. I., Yuanye Wang, S. Strzyz y F. Frederiksen. "Enhanced inter-cell interference coordination in co-channel multi-layer LTE-advanced networks". IEEE Wireless Communications 20, n.º 3 (junio de 2013): 120–27. http://dx.doi.org/10.1109/mwc.2013.6549291.

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39

CHEN, Mu-qiong, Hong JI y Xi LI. "Load-adaptive frequency reuse scheme for inter-cell interference coordination in relay networks". Journal of China Universities of Posts and Telecommunications 17, n.º 5 (octubre de 2010): 38–43. http://dx.doi.org/10.1016/s1005-8885(09)60505-7.

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40

Zhang, Hui, XiaoDong Xu, JingYa Li, XiaoFeng Tao, Ping Zhang, Tommy Svensson y Carmen Botella. "Multicell power allocation method based on game theory for inter-cell interference coordination". Science in China Series F: Information Sciences 52, n.º 12 (diciembre de 2009): 2378–84. http://dx.doi.org/10.1007/s11432-009-0213-7.

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41

Hamza, Abdelbaset S., Shady S. Khalifa, Haitham S. Hamza y Khaled Elsayed. "A Survey on Inter-Cell Interference Coordination Techniques in OFDMA-Based Cellular Networks". IEEE Communications Surveys & Tutorials 15, n.º 4 (2013): 1642–70. http://dx.doi.org/10.1109/surv.2013.013013.00028.

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42

Hamza, Haitham S., Shady S. Khalifa y Khaled Elsayed. "Autonomous Schemes for Inter-cell Interference Coordination in the Downlink of LTE Systems". International Journal of Wireless Information Networks 21, n.º 3 (30 de mayo de 2014): 181–95. http://dx.doi.org/10.1007/s10776-014-0243-y.

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43

Ullah, Rahat, Fahim Ullah, Zubair Khalid y Hashim Safdar. "A REVIEW OF INTER CELL INTERFERENCE MANAGEMENT IN REGULAR AND IRREGULAR GEOMETRY CELLULAR NETWORKS". Jurnal Teknologi 83, n.º 5 (1 de agosto de 2021): 45–56. http://dx.doi.org/10.11113/jurnalteknologi.v83.16866.

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Resumen

This paper reviews the inter-cell interference (ICI) mitigation approaches in the OFDMA based multicellular networks with more emphasis on the frequency reused based ICI coordination schemes in the downlink systems. The geometry of the network severely affects the Signal to Interference and Noise Ratio (SINR); therefore, the wireless cellular systems are strongly dependent on the spatial BSs configuration and topology of a network. ICI mitigation techniques for both regular and irregular geometry networks are analyzed and a qualitative comparison along with the future research directions are presented.

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44

Koudouridis, Georgios y Christer Qvarfordt. "Path-loss Based Power Suppression for Spectral and Energy Efficient Inter-cell Interference Coordination". Recent Advances in Communications and Networking Technology 3, n.º 1 (10 de marzo de 2014): 44–54. http://dx.doi.org/10.2174/2215081102666140311010423.

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45

GIL, Gye-Tae, Seong-Choon LEE y Dong-Hoi KIM. "A Dynamic Resource Allocation Scheme for Inter-Cell Interference Coordination in Cellular OFDMA Systems". IEICE Transactions on Communications E94-B, n.º 3 (2011): 758–64. http://dx.doi.org/10.1587/transcom.e94.b.758.

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46

SEKI, Hiroyuki y Fumiyuki ADACHI. "Centralized Inter-Cell Interference Coordination Using Multi-Band 3D Beam-Switching in Cellular Networks". IEICE Transactions on Communications E98.B, n.º 7 (2015): 1363–72. http://dx.doi.org/10.1587/transcom.e98.b.1363.

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47

Hwang, Taemin, Yujin Nam, Min-A. Jeong y Jaewoo So. "Downlink System Level Simulator for Enhanced Inter-Cell Interference Coordination in Maritime Heterogeneous Networks". Journal of Korean Institute of Communications and Information Sciences 40, n.º 7 (31 de julio de 2015): 1424–32. http://dx.doi.org/10.7840/kics.2015.40.7.1424.

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48

Kashaf, Aasia, Moazzam Islam Tiwana, Imran Usman y Mohsin Islam Tiwana. "Self-organizing inter-cell interference coordination in 4G and beyond networks using genetic algorithms". Automatika 58, n.º 1 (2 de enero de 2017): 48–54. http://dx.doi.org/10.1080/00051144.2017.1337394.

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49

Liu, An, Vincent K. N. Lau, Liangzhong Ruan, Junting Chen y Dengkun Xiao. "Hierarchical Radio Resource Optimization for Heterogeneous Networks With Enhanced Inter-Cell Interference Coordination (eICIC)". IEEE Transactions on Signal Processing 62, n.º 7 (abril de 2014): 1684–93. http://dx.doi.org/10.1109/tsp.2014.2302748.

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50

Dominique, Charles y David Dominique. "Deriving the phase synchronisation requirement for outdoor long-term evolution small cell enhanced inter-cell interference coordination". Journal of Engineering 2016, n.º 11 (1 de noviembre de 2016): 402–5. http://dx.doi.org/10.1049/joe.2016.0172.

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