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Journal articles on the topic 'Inter-cell interference'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 January 2023

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1

Beigh, Aamir Nazir, and Er Prabhjot Kaur. "Inter-Cell Interference." International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (October 31, 2018): 43–46. http://dx.doi.org/10.31142/ijtsrd18406.

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2

HIGUCHI, Kenichi, Yoshiko SAITO, and Seigo NAKAO. "Inter-Cell Interference Coordination Method Based on Coordinated Inter-Cell Interference Power Control in Uplink." IEICE Transactions on Communications E98.B, no. 7 (2015): 1357–62. http://dx.doi.org/10.1587/transcom.e98.b.1357.

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3

Wigren, Torbjörn. "Wireless interference power estimation for inter-cell interference coordination." IET Communications 9, no. 12 (August 13, 2015): 1539–46. http://dx.doi.org/10.1049/iet-com.2014.0831.

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4

Fernández Campo, Betty Nayibe, Lesly Alejandra González Camacho, and 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, no. 1 (May 31, 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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Risi, Chiara, and Dereje Assefa Wassie. "Inter-cell Interference Modeling in LTE Systems." Wireless Personal Communications 72, no. 1 (February 7, 2013): 389–404. http://dx.doi.org/10.1007/s11277-013-1019-x.

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6

Wang, Yafeng, Guoxing Wei, and Wei Xiang. "Inter-cell interference modeling for cellular networks." Telecommunication Systems 53, no. 1 (May 2013): 99–105. http://dx.doi.org/10.1007/s11235-013-9682-5.

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7

Hwang, Duckdong. "Inter-cell interference alignment in multi cell multiuser channels." IEICE Electronics Express 9, no. 6 (2012): 586–89. http://dx.doi.org/10.1587/elex.9.586.

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8

Abdallah. Jazea, Najim, Hayam abood Kadim, and Adheed Hasan.Sallomi. "STUDY AND ANALYSIS OF INTRA-CELL INTERFERENCE AND INTER-CELL INTERFERENCE FOR 5G NETWORK." Journal of Engineering and Sustainable Development 24, no. 03 (May 1, 2020): 43–57. http://dx.doi.org/10.31272/jeasd.24.3.3.

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9

Trejo Narváez, Omar Albeiro, and Víctor Fabián Miramá Pérez. "Machine learning algorithms for inter-cell interference coordination." Sistemas y Telemática 16, no. 46 (July 6, 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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10

Zhang, Yinghai, Fan Zhang, Yan zhou, Gaofeng Cui, and 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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11

Li, Mengli, and Wei Song. "Inter-cell Interference Suppression Technology of OFDM Systems." Procedia Engineering 29 (2012): 3774–78. http://dx.doi.org/10.1016/j.proeng.2012.01.569.

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12

WANG, Ya-feng, Guo-xing WEI, and Wei XIANG. "Approximate inter-cell interference modeling for cellular network." Journal of China Universities of Posts and Telecommunications 18, no. 3 (June 2011): 75–79. http://dx.doi.org/10.1016/s1005-8885(10)60066-0.

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13

Li, Xu, Huarui Yin, Ying Xu, and Guo Wei. "Inter-cell interference mitigation based on joint beamforming." International Journal of Communication Systems 29, no. 3 (October 9, 2014): 507–21. http://dx.doi.org/10.1002/dac.2880.

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14

Abe, Taisuke, and Takahiko Saba. "Iterative Multi-cell Channel Estimation for Inter-cell Interference Suppression." Journal of Signal Processing 19, no. 4 (2015): 131–34. http://dx.doi.org/10.2299/jsp.19.131.

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15

Deepa, S., J. Jeneetha Jebanazer, S. Rajakumar, J. Mercy Sheeba, and J. Rryan. "Investigations on spectral efficiency of muticellnetworks using hybrid beamforming." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 2 (May 1, 2022): 826. http://dx.doi.org/10.11591/ijeecs.v26.i2.pp826-835.

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<span>Millimeter wave communication systems with antenna beamforming facilitates practical solutions to the capacity crunch issues in the upcoming 5G wireless networks. Multi-cell dense networks are prone to three major interferences-inter-cell, intra-cell and Inter layer interference-the most dominating being the inter-cell interference. This paper focuses to alleviate inter-cell interference using hybrid beamforming (HBF) approach, leveraging coordinated multipoint (CoMP) technique, thereby improving the SE of 5G networks. Simulation results show HBFpeforms in par with optimal weights, making it a suitable candidate for 5G networks. As the number of data streams is increased from Ns=1 to 4 for 0 dB signal to noise ratio (SNR) with Nt=64 and Nr=16, the SE increases from 9.5557 bits/s/Hz to 26.423 bits/s/Hz for optimal weights and from 9.1885 bits/s/Hz to 19.763 bits/s/Hz and hybrid weights, respectively. The second set of experiments are conducted to study the effect of number of transmit antennas on spectral efficiency (SE). The results show that as the number of transmit antennas is increased from Nt=16 to 64 for 0 dB SNR, with Nr=16 and Ns=4, the SE increases from 17.735 bits/s/Hz to 26.423 bits/s/Hz and 13.750 bits/s/Hz to 19.763 bits/s/Hz for optimal weights and hybrid weights, respectively.</span>

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Iskandar, Iskandar, I. Setyawan, and H. Nuraini. "Inter-cell Interference Management Technique for Multi-Cell LTE-A Network." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 5 (October 1, 2017): 2696. http://dx.doi.org/10.11591/ijece.v7i5.pp2696-2705.

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In modern cellular system such as LTE Advanced (LTE-A), frequency reuse scheme is targeted to be applied to fulfill the requirement of high capacity broadband access and high spectrum efficiency. But this kind of frequency planning may lead to the worse inter-cell interference (ICI) level experienced especially by a user located at the cell edge. Soft Frequency Reuse (SFR) is considered as an effective way to mitigate inter-cell interference and maintain capacity. We propose a power division SFR, known as multi level SFR technique to minimize ICI in a designed LTE-A network for sub-urban environment. Service area of LTE-A network was first developed to deploy particular number of eNB by using LTE network planning tools in the frequency of 1800 MHz with the use of SISO (Single Input Single Output) antennas. Coverage dimensioning and propagation consideration determine LTE-A parameters which were used in the simulation. Monte carlo simulation is executed to examine the performance of SFR for LTE-A downlink transmission to address different power ratio and traffic loads problem. Both performance of cell edge users and overall cell performance are evaluated in terms of CINR, BLER, and throughput. Performance with SFR is also compared with the classical frequency reuse one and three.

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17

Yussuff, Abayomi Isiaka O., and Abdul-Rasaq A. Bakare. "Performance evaluation of inter-cell interference prediction in massive MIMO." Applied Journal of Physical Science 3, no. 1 (April 30, 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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18

Xie, Sheng-dong, and Meng Wu. "Analysis of Inter-cell Interference in Multimedia Cellular CDMA." Journal of Electronics & Information Technology 30, no. 5 (March 14, 2011): 1159–62. http://dx.doi.org/10.3724/sp.j.1146.2006.01616.

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19

Mahmood, Nurul Huda, Klaus Ingemann Pedersen, and 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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20

nka, Priya. "Fuzzy Based Inter Cell Interference Cancellation in LTE System." International Journal of Engineering Trends and Technology 25, no. 3 (July 25, 2015): 126–29. http://dx.doi.org/10.14445/22315381/ijett-v25p223.

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21

Li, Yue Heng, Ming Hao Fu, Li Wang, Mei Yan Ju, and Ping Huang. "Analysis of Distributed MIMO Systems in a Multi-Cell Environment." Applied Mechanics and Materials 696 (November 2014): 183–90. http://dx.doi.org/10.4028/www.scientific.net/amm.696.183.

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This paper focuses its research work on the capacity and outage performances of a distributed multiple-input multiple-output (DMIMO) system in a multi-cell environment. For this purpose, the multi-cell DMIMO structure is modeled first, and based on this model, the so-called blanket communication and selective communication schemes are compared, and the formula of the output signal to interference plus noise ratio (SINR) of the above two schemes are given to illustrate the way of an inter-cell interference affecting the system performance. Then the expressions of the average capacity and outage probability are derived by using the probability density function (PDF) of the output SINR in the preferred selective communication scheme with some necessary approximations. Finally, the computer simulations are provided to explore the possible rule of upper layer network scheduling in overcoming the inter-cell interferences and in optimizing the capacity and outage performances in the DMIMO systems.

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22

Maruta, Kazuki. "Dynamic Clustering and Coordinated User Scheduling for Cooperative Interference Cancellation on Ultra-High Density Distributed Antenna Systems." Entropy 20, no. 8 (August 19, 2018): 616. http://dx.doi.org/10.3390/e20080616.

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This paper proposes dynamic clustering and user scheduling for previously conceived inter-cluster interference cancellation scheme on ultra-high density distributed antenna system (UHD-DAS). UHD-DAS is composed of one central unit (CU) and densely deployed remote radio units (RUs) serving as small cell access points. It can enhance spatial spectral efficiency by alleviating traffic load imposed per radio unit; however, intenser small cell deployment revives the inter-cell interference (ICI) problem. Cell clustering, cooperation of multiple RUs, can mitigate ICI partially, whereas inter-cluster interference (ICLI) still limits its possible capacity. Simplified ICLI cancellation based on localized RU cooperation was previously proposed to mitigate interference globally. The resolved issue is that it required frequency reuse distance to fully obtain its interference cancellation ability. This paper introduces dynamic clustering with coordinated user scheduling to ensure reuse distance without extra frequency reuse. Joint dynamic clustering and ICLI cancellation can effectively work and almost reaches ideal performance as full cooperative spatial multiplexing transmission.

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23

Zhang, Wenjian, and Senlin Jiang. "Performance Evaluation of MU-MIMO Transmissions with Joint Interference Constraint in HetNet." Mathematical Problems in Engineering 2021 (November 23, 2021): 1–10. http://dx.doi.org/10.1155/2021/2397803.

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In this paper, we investigate the per-tier outage probability of multiuser multiple-input multiple-output (MU-MIMO) transmissions in heterogeneous networks (HetNets) with joint interference constraint. In the tier of cellular cell, user equipment (UE) is required to report measured channel information and the base station (BS) adopts ZF-based precoding MU-MIMO transmission to achieve multiuser diversity gain. With the constraint of cross-tier interference and unpredicted inter-beam interference, we derive the closed-form expression of outage probability of downlink MU-MIMO transmissions. Considering the capacity of nodes in the tier of ad hoc networks, a max-SINR scheduler and codebook-based MU-MIMO transmission are employed. The scheduler selects the best receiving nodes for each beam in predefined codebook according to measured signal to interference plus noise ratio (SINR), and the transmitting node performs data transmissions using orthogonal beams. In the presence of inter-node interference, inter-beam interference, and cross-tier interference, we obtain the closed-form expression of outage probability of MU-MIMO transmissions when downlink or uplink transmissions occur in cellular cell. Additionally, in case that the outage probability in ad hoc networks should satisfy quality of service (QoS) requirement, a restricted area in cellular cell in which the outage probability in ad hoc networks is not greater than a required threshold is explored. Numerical results show that the unpredictable inter-beam interference in cellular cell degrades the outage probability slightly. The restricted area increases with the outage probability threshold.

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Zhang, Xuefei, Xiaofeng Tao, Qimei Cui, and Juan Bai. "Intra‐cell and inter‐cell interference‐constrained D2D communication underlaying cellular networks." Electronics Letters 51, no. 14 (July 2015): 1117–19. http://dx.doi.org/10.1049/el.2015.0197.

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25

Jiang, Weilin, Zhongzhao Zhang, Yubin Xu, and Linan Sun. "Dynamic Inter-cell Interference Cancellation for Uplink in Multi-cell OFDMA Systems." Information Technology Journal 9, no. 7 (September 15, 2010): 1490–94. http://dx.doi.org/10.3923/itj.2010.1490.1494.

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26

Guevara, Andrea P., and Sofie Pollin. "Densely Deployed Indoor Massive MIMO Experiment: From Small Cells to Spectrum Sharing to Cooperation." Sensors 21, no. 13 (June 25, 2021): 4346. http://dx.doi.org/10.3390/s21134346.

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Massive MIMO is a key 5G technology that achieves high spectral efficiency and capacity by significantly increasing the number of antennas per cell. Furthermore, due to precoding, massive MIMO allows co-channel interference cancellation across cells. In this work, based on experimental channel data for an indoor scenario, we analyse the impact of inter and intra-cell interference suppression in terms of spectral efficiency, capacity, user fairness and computational cost for three simulated systems under different cooperation levels. The first scenario assumes a cooperative case where eight neighbouring cells share the spectrum and infrastructure. This scenario provides the highest system performance; however, user fairness is achieved only when there is inter and intra-cell interference suppression. The second scenario considers eight cells that only share the spectrum; with full intra-cell and inter-cell interference cancellation, it is possible to achieve 32% of the optimal capacity with 20% of the computational cost in each distributed CPU, although the total computational cost per system is the highest. The third scenario considers eight independent cells operating in different frequency bands; in this case, intra-cell interference suppression leads to higher spectral efficiency compared to the cooperative case without intra-cell interference suppression.

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27

Padmaloshani, Palanisamy, and Sivaraj Nirmala. "Semi‐distributed dynamic inter‐cell interference coordination scheme for interference avoidance in heterogeneous networks." ETRI Journal 42, no. 2 (April 2020): 175–85. http://dx.doi.org/10.4218/etrij.2018-0362.

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28

Kosta, Chrysovalantis, Bernard Hunt, Atta UI Quddus, and Rahim Tafazolli. "On Interference Avoidance Through Inter-Cell Interference Coordination (ICIC) Based on OFDMA Mobile Systems." IEEE Communications Surveys & Tutorials 15, no. 3 (2013): 973–95. http://dx.doi.org/10.1109/surv.2012.121112.00037.

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29

Hassen, Wafa Ben, Mériem Afif, and Sami Tabbane. "Interference Mitigation Through Inter-Cell Interference Coordination Using Virtual PRB Allocation in 4G Networks." Wireless Personal Communications 90, no. 3 (June 4, 2016): 1179–209. http://dx.doi.org/10.1007/s11277-016-3384-8.

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30

Park, Suk Kwang, and Jaekyun Moon. "Characterization of Inter-Cell Interference in 3D NAND Flash Memory." IEEE Transactions on Circuits and Systems I: Regular Papers 68, no. 3 (March 2021): 1183–92. http://dx.doi.org/10.1109/tcsi.2020.3047484.

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31

N. Østerbø, Olav, and Ole Grøndalen,. "Comparison of Some Inter-Cell Interference Models for Cellualar Networks." International Journal of Wireless & Mobile Networks 9, no. 3 (June 30, 2017): 69–100. http://dx.doi.org/10.5121/ijwmn.2017.9307.

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32

Park, Sang-Kyu, and Sae-Woong Bahk. "Dynamic Inter-Cell Interference Avoidance in Self-Organizing Femtocell Networks." Journal of Korean Institute of Communications and Information Sciences 36, no. 3A (March 31, 2011): 259–66. http://dx.doi.org/10.7840/kics.2011.36a.3.259.

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33

Kwon, Hojoong, Soomin Ko, Hanbyul Seo, and Byeong Gi Lee. "Inter-cell interference management for next-generation wireless communication systems." Journal of Communications and Networks 10, no. 3 (September 2008): 258–67. http://dx.doi.org/10.1109/jcn.2008.6388347.

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34

Prabha. "MIGITATION OF INTER CELL INTERFERENCE AND FADING IN LTE SYSTEMS." Journal of Computer Science 10, no. 3 (March 1, 2014): 434–42. http://dx.doi.org/10.3844/jcssp.2014.434.442.

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35

Jung, Sun-Young, Do-Hoon Kwon, Se-Hoon Yang, and Sang-Kook Han. "Inter-cell interference mitigation in multi-cellular visible light communications." Optics Express 24, no. 8 (April 11, 2016): 8512. http://dx.doi.org/10.1364/oe.24.008512.

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36

Tianmin Ren and R. J. La. "Downlink beamforming algorithms with inter-cell interference in cellular networks." IEEE Transactions on Wireless Communications 5, no. 10 (October 2006): 2814–23. http://dx.doi.org/10.1109/twc.2006.04580.

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37

Fernandes, Fabio, Alexei Ashikhmin, and Thomas L. Marzetta. "Inter-Cell Interference in Noncooperative TDD Large Scale Antenna Systems." IEEE Journal on Selected Areas in Communications 31, no. 2 (February 2013): 192–201. http://dx.doi.org/10.1109/jsac.2013.130208.

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38

Bertrand, Moubagou Deflandre, and Chang Yong Yu. "Base Station Coordination towards an Effective Inter-cell Interference Mitigation." International Journal of Future Generation Communication and Networking 8, no. 2 (April 30, 2014): 45–58. http://dx.doi.org/10.14257/ijfgcn.2015.8.2.05.

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Bertrand, Moubagou Deflandre, and Yong Yu Chang. "Base Station Coordination towards an Effective Inter-cell Interference Mitigation." International Journal of Future Generation Communication and Networking 8, no. 2 (April 30, 2015): 45–58. http://dx.doi.org/10.14257/ijfgcn.2015.8.2.5.

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40

Zhang, Zihan, and Guanding Yu. "FdICIC: Inter-cell Interference Coordination for Full-Duplex Cellular Systems." Wireless Personal Communications 101, no. 1 (May 14, 2018): 1–22. http://dx.doi.org/10.1007/s11277-018-5627-3.

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41

Maurizka, Alvita, F. Hamdani, M. M. Ulfah, and Iskandar Iskandar. "Soft Frequency Reuse (SFR) in LTE-A Heterogeneous Networks based upon Power Ratio Evaluation." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 3 (June 1, 2018): 1569. http://dx.doi.org/10.11591/ijece.v8i3.pp1569-1576.

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As the traffic demand grows and the RF environment changes, the mobile network relies on techniques such as SFR in Heterogeneous Network (HetNet) to overcome capacity and link budget limitation to maintain user experience. Inter-Cell Interference (ICI) strongly affecting Signal-to-Interference plus Noise Ratio (SINR) of active UEs, especially cell-edge users, which leads to a significant degradation in the total throughput. In this paper we evaluate the performance of SFR with HetNet system in order dealing with interferences. Simulation result shows that the power ratio control in SFR HetNet system doesn’t have much effect on total achieved capacity for overall cell.

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Aal-nouman, Mohammed I., Osamah Abdullah, and 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, no. 4 (August 1, 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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43

Al-hubaishi, Ahmed, Nor Noordin, Aduwati Sali, Shamala Subramaniam, and Ali Mohammed Mansoor. "An Efficient Pilot Assignment Scheme for Addressing Pilot Contamination in Multicell Massive MIMO Systems." Electronics 8, no. 4 (March 27, 2019): 372. http://dx.doi.org/10.3390/electronics8040372.

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The reuse of the same pilot group across cells to address bandwidth limitations in a network has resulted in pilot contamination. This causes severe inter-cell interference at the targeted cell. Pilot contamination is associated with multicell massive multiple-input multiple-output (MIMO) systems which degrades the system performance even when extra arrays of antennas are added to the network. In this paper, we propose an efficient pilot assignment (EPA) scheme to address this issue by maximizing the minimum uplink rate of the target cell’s users. To achieve this, we exploit the large-scale characteristics of the fading channel to minimize the amount of outgoing inter-cell interference at the target cell. Results from the simulation show that the EPA scheme outperforms both the conventional and the smart pilot assignment (SPA) schemes by reducing the effect of inter-cell interference. These results, show that the EPA scheme has significantly improved the system performance in terms of achievable uplink rate and cumulative distribution function (CDF) for both signal-to-interference-plus-noise ratio (SINR), and uplink rate.

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44

S, Shibu, and Saminadan V. "Improved hybrid inter and intra-cell interference cancellation mechanism for LTE-A HETNETS." International Journal of Engineering & Technology 7, no. 3 (July 8, 2018): 1381. http://dx.doi.org/10.14419/ijet.v7i3.11022.

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In Heterogeneous networks (HetNets), operators need to ensure reliable service to their users in terms of network performance and low cost. The growing demand of user traffic necessitates the incorporation of femto cells and pico cells for facilitating seamless services. The network performance of Long Term Evolution (LTE) and LTE Advanced (LTE-A) HetNets is drastically influenced by the degree of interference that is realized in the inter-cell and intra-cell during communication. In this paper, an Improved Hybrid inter and intra-cell interference cancellation mechanism (CRS-IIC-LFLS) is propounded for handling interference at the inter and intra-cell level. Inter-cell interference cancellation is achieved through the use of an Improved CRS-IIC algorithm that uses the benefits of Linear Filtering Least Square (LFLS) method for channel estimation. CRS-IIC-LFLS is found to potent in rapid interference cancellation facilitation by suppressing the noise level, reducing the impact of fading channel and inherently eliminates small energy aware paths from large energy aware paths. The Simulation results confirm that the proposed scheme ensures better network throughput under light load, medium load and heavy load conditions of the network. The results prove that the performance of CRS-IIC-LFLS with CRS-IC-LFLS and CRS-IC-LLS based on spectral efficiency is improved at a mean rate of 21% and 26% respectively. The simulation results also portrays that the increase in the spectral efficiency of CRS-IIC-LFLS (64-QAM) is phenomenal to a maximum improvement of 12% over CRS-IIC-LFLS (16-QAM).

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OHWATARI, Yusuke, Nobuhiko MIKI, Takahiro ASAI, Tetsushi ABE, and Hidekazu TAOKA. "Performance of Interference Rejection Combining Receiver to Suppress Inter-Cell Interference in LTE-Advanced Downlink." IEICE Transactions on Communications E94-B, no. 12 (2011): 3362–69. http://dx.doi.org/10.1587/transcom.e94.b.3362.

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Zhang, Xinchen, and Martin Haenggi. "A Stochastic Geometry Analysis of Inter-Cell Interference Coordination and Intra-Cell Diversity." IEEE Transactions on Wireless Communications 13, no. 12 (December 2014): 6655–69. http://dx.doi.org/10.1109/twc.2014.2339273.

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Ryoo, Hae-Nah, Do-Hoon Kwon, Se-Hoon Yang, and Sang-Kook Han. "Differential Optical Detection in VLC for Inter-Cell Interference Reduced Flexible Cell Planning." IEEE Photonics Technology Letters 28, no. 23 (December 1, 2016): 2728–31. http://dx.doi.org/10.1109/lpt.2016.2615644.

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Zhang, Hui, Zhikun Wang, Yangbo Liu, Haitao Zhao, Yanfei Sun, and Hongbo Zhu. "Virtual resource mapping in inter‐cell interference‐constrained ultra‐dense networks." IET Communications 15, no. 6 (February 2021): 790–801. http://dx.doi.org/10.1049/cmu2.12121.

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Kim, Kyunghoon, Jinhua Piao, and Seungwon Choi. "Novel Beamforming and User Scheduling Algorithm for Inter-cell Interference Cancellation." IEIE Transactions on Smart Processing and Computing 5, no. 5 (October 30, 2016): 346–48. http://dx.doi.org/10.5573/ieiespc.2016.5.5.346.

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Zhu, Yuan-ping, Jing Xu, Yang Yang, and Jiang Wang. "Statistical Analysis of the Uplink Inter-cell Interference for Cellular Systems." Journal of Electronics & Information Technology 35, no. 8 (February 25, 2014): 1971–76. http://dx.doi.org/10.3724/sp.j.1146.2012.01613.

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