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Journal articles on the topic 'Co-channel interference'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Xu, Yifan, Guochun Ren, Jin Chen, Xiaobo Zhang, Luliang Jia, and Lijun Kong. "Interference-Aware Cooperative Anti-Jamming Distributed Channel Selection in UAV Communication Networks." Applied Sciences 8, no. 10 (2018): 1911. http://dx.doi.org/10.3390/app8101911.

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This paper investigates the cooperative anti-jamming distributed channel selection problem in UAV communication networks. Considering the existence of malicious jamming and co-channel interference, we design an interference-aware cooperative anti-jamming scheme for the purpose of maximizing users’ utilities. Moreover, the channel switching cost and cooperation cost are introduced, which have a great impact on users’ utilities. Users in the UAV group sense the co-channel interference signal energy to judge whether they are influenced by co-channel interference. When the received co-channel inte

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2

Daniels, Karen, Kavitha Chandra, Sa Liu, and Sumit Widhani. "Dynamic channel assignment with cumulative co-channel interference." ACM SIGMOBILE Mobile Computing and Communications Review 8, no. 4 (2004): 4–18. http://dx.doi.org/10.1145/1052871.1052872.

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3

Wang, Haitao, Xiaoyong Lyu, and Kefei Liao. "Co-Channel Interference Suppression for LTE Passive Radar Based on Spatial Feature Cognition." Sensors 22, no. 1 (2021): 117. http://dx.doi.org/10.3390/s22010117.

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Passive radars based on long-term evolution (LTE) signals suffer from sever interferences. The interferences are not only from the base station used as the illuminator of opportunity (BS-IoO), but also from the other co-channel base stations (CCBS) working at the same frequency with the BS-IoO. Because the reference signals of the co-channel interferences are difficult to obtain, cancellation performance degrades seriously when traditional interference suppression methods are applied in LTE-based passive radar. This paper proposes a cascaded cancellation method based on the spatial spectrum co

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4

Ariska Cahya, Wisnu Djatmiko, and Aodah Diamah. "ANALISIS JARINGAN GSM 1800 MHZ PADA SEKTOR YANG MENGGUNAKAN FREQUENCY REUSE TERHADAP KUALITAS PELAYANAN BTS DKI JAKARTA DI PT. TELKOMSEL INDONESIA, TBK." JURNAL PENDIDIKAN VOKASIONAL TEKNIK ELEKTRONIKA (JVoTE) 1, no. 2 (2018): 20–23. http://dx.doi.org/10.21009/jvote.v1i2.17338.

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Abstrak- Tujuan dari penelitian ini adalah mencari hubungan antara Co – Channel Interference pada konsep Frequency Reuse terhadap kualitas pelayanan BTS DKI Jakarta.Penelitian ini menggunakan metode kuantitatif dimana data diolah dengan menggunakan korelasi product momment dengan bantuan microsoft excell. Penelitian ini menggunakan data sekunder yang bersumber dari PT, Telkomsel, tbk. yang diambil dengan metode drive test. Sampel yang diambil berjumlah 7 tempat di DKI Jakarta. Data yang diambil merupakan data dari nilai Carrier to Interference (C/I), juga nilai Rx Level dan jarak antara sel as

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5

Saini, Jatinder Singh, and Balwinder Singh Sohi. "Performance evaluation of interference aware topology power and flow control channel assignment algorithm." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 2503. http://dx.doi.org/10.11591/ijece.v10i3.pp2503-2512.

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Multi-Radio Multi-Channel Wireless Mesh Network (MRMC-WMN) has been considered as one of the key technology for the enhancement of network performance. It is used in a number of real-time applications such as disaster management system, transportation system and health care system. MRMC-WMN is a multi-hop network and allows simultaneous data transfer by using multiple radio interfaces. All the radio interfaces are typically assigned with different channels to reduce the effect of co-channel interference. In MRMC-WMN, when two nodes transmit at the same channel in the range of each other, gener

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6

Jatinder, Singh Saini, and Singh Sohi Balwinder. "Performance evaluation of interference aware topology power and flow control channel assignment algorithm." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 2503–12. https://doi.org/10.11591/ijece.v10i3.pp2503-2512.

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Multi-Radio Multi-Channel Wireless Mesh Network (MRMC-WMN) has been considered as one of the key technology for the enhancement of network performance. It is used in a number of real-time applications such as disaster management system, transportation system and health care system. MRMC-WMN is a multi-hop network and allows simultaneous data transfer by using multiple radio interfaces. All the radio interfaces are typically assigned with different channels to reduce the effect of co-channel interference. In MRMC-WMN, when two nodes transmit at the same channel in the range of each other, gener

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7

Su, Dongchu, Zengtian Chang, Jian Yang, Bowei Chang, Zhijun Zhu, and Lu Qiang. "Detection Technology of Intentional Electromagnetic Co-channel Interference Source." Journal of Physics: Conference Series 2366, no. 1 (2022): 012026. http://dx.doi.org/10.1088/1742-6596/2366/1/012026.

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Abstract The characteristics and action mechanisms of intentional interference sources were analyzed. Then, a fast detection method of intentional co-channel interference was proposed based on such technologies as real-time spectrum analysis, digital phosphor display, and co-channel signal direction-finding. Next, two classical intentional interference scenarios were reproduced, and interference sources were detected fast through the proposed method.

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8

Li, Nuozhou, Tong Liu, and Hangqi Li. "An Improved Adaptive Median Filtering Algorithm for Radar Image Co-Channel Interference Suppression." Sensors 22, no. 19 (2022): 7573. http://dx.doi.org/10.3390/s22197573.

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In order to increase the accuracy of ocean monitoring, this paper proposes an improved adaptive median filtering algorithm based on the tangential interference ratio to better suppress marine radar co-channel interference. To solve the problem that co-channel interference reduces the accuracy of radar images’ parameter extraction, this paper constructs a tangential interference ratio model based on the improved Laplace operator, which is used to describe the ratio of co-channel interference along the antenna rotation direction in the original radar image. Based on the idea of between-class var

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9

Li, Yue, Liang Ye, and Xuejun Sha. "Time-Frequency Energy Sensing of Communication Signals and Its Application in Co-Channel Interference Suppression." Sensors 18, no. 7 (2018): 2378. http://dx.doi.org/10.3390/s18072378.

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As the number of mobile users and video traffics grow explosively, the data rate demands increase tremendously. To improve the spectral efficiency, the spectrum are reused inter cell or intra cell, such as the ultra dense network with multi-cell or the cellular network with Device-to-Device communications, where the co-channel interferences are brought and needs to be suppressed. According to the time-frequency energy sensing to the communication signals, the desired signal and the interference signal have different energy concentration areas on the time frequency plane, which provide opportun

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10

A., Soler, EI-Osmani A., and Ahmed M. "CO-CHANNEL INTERFERENCE CANCELLER FOR CELLULAR SYSTEMS." International Conference on Aerospace Sciences and Aviation Technology 9, ASAT Conference, 8-10 May 2001 (2001): 1–9. http://dx.doi.org/10.21608/asat.2001.31135.

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11

A., Soler, EI-Osmani A., and Ahmed M. "CO-CHANNEL INTERFERENCE CANCELLER FOR CELLULAR SYSTEMS." International Conference on Aerospace Sciences and Aviation Technology 9, no. 9 (2001): 817–25. http://dx.doi.org/10.21608/asat.2001.59702.

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12

Ren, Shihai, Junhui Zhao, Huan Zhang, and Xuan Li. "Connectivity Analysis with Co-Channel Interference for Urban Vehicular Ad Hoc Networks." Electronics 12, no. 9 (2023): 2021. http://dx.doi.org/10.3390/electronics12092021.

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In urban vehicular ad hoc networks (VANETs), the complex channel environment and co-channel interference resulted in the uncertain delay of inter-vehicle packet transmission, which causes serious delay jitter. Connectivity is proposed as a key metric to describe this uncertainty. However, existing works lack a discussion of inter-vehicle connectivity in urban VANETs, particularly with regards to the process of transmitting packets between vehicles. In this paper, we analyze the connectivity probability of urban VANETs under co-channel interference with both complete and incomplete information.

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13

Lan, Lina, Xuerong Gou, Jingli Mao, and Wenyuan Ke. "GSM co-channel and adjacent channel interference analysis and optimization." Tsinghua Science and Technology 16, no. 6 (2011): 583–88. http://dx.doi.org/10.1016/s1007-0214(11)70078-5.

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14

Uchegbu, Chinenye Eberechi, Okorocha Richard, and Okore Uchenna Elekwa. "Co-Channel Interference Mitigation in 5g Network using Particle Swarm Optimization." International Journal of Latest Technology in Engineering, Management & Applied Science XII, no. XII (2024): 27–36. http://dx.doi.org/10.51583/ijltemas.2023.121203.

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The co-channel interference problem in 5G wireless networks is the subject of this research project. Even with the improvements brought forth by 5G, co-channel interference still degrades network speed and signal quality. Particle Swarm Optimization (PSO) is the method used in this study to minimize this interference and improve network performance by fine-tuning resource allocation settings. PSO-based interference mitigation, network modeling, simulation, an overview of the literature, and comparative analysis are all included in the study. The study is valuable for communication engineers si

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15

Wang, Jui Teng. "Interference-Free Criterion for Interference-Unaware Receive Transform in MIMO Co-Channel Interference." IEEE Wireless Communications Letters 7, no. 2 (2018): 210–13. http://dx.doi.org/10.1109/lwc.2017.2764910.

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16

Hussain, Z., A. ur R. Khan, H. Mehdi, and S. M. A. Saleem. "Analysis of D2D Communications over Gamma/Nakagami Fading Channels." Engineering, Technology & Applied Science Research 8, no. 2 (2018): 2693–98. http://dx.doi.org/10.48084/etasr.1828.

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In this paper, we investigate the outage probability, channel capacity and symbol error rate (SER) performance of device-to-device (D2D) communication systems. The D2D communication system is affected by several co-channel interferers. Gamma fading channel is considered for the D2D communication system. The channel for the co-channel interference is assumed to be Nakagami faded. An expression for the probability density function (PDF) of the signal-to-interference ratio (SIR) is presented. The PDF is a function of distances between various devices in the D2D system, path-loss, channel fading c

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17

Wei, Chuan Ting, Quan Li Ning, and Dong Chen. "Research on Multi-Fuze Co-Channel Interference Suppression Based on Pseudorandom Code Phase Modulation." Applied Mechanics and Materials 539 (July 2014): 190–93. http://dx.doi.org/10.4028/www.scientific.net/amm.539.190.

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This paper introduces the working principle of the pseudorandom code phase modulation pulse, analyzes the theoretical foundation of multi-fuze co-channel interference suppression achieved by phase modulation of the signals through pseudorandom coding, and through the calculation and analysis of simulation, verifies the feasibility of the multi-fuze co-channel interference suppression based on pseudorandom code phase modulation.

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18

El-Jaafreh, Yousef G. "Co-channel and Adjacent Channel Interference Calculations in Cellular Communications Systems." Journal of King Saud University - Engineering Sciences 12, no. 1 (2000): 153–67. http://dx.doi.org/10.1016/s1018-3639(18)30711-6.

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19

Cristallini, Diego, Ashley Summers, Philipp Wojaczek, Robert Young, and Daniel O'Hagan. "Dealing with co‐channel interference in multi‐channel airborne passive radar." IET Radar, Sonar & Navigation 15, no. 1 (2020): 85–100. http://dx.doi.org/10.1049/rsn2.12016.

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20

Chiu, Chien-Ching, Chun-Liang Liu, and Shu-Han Liao. "Channel characteristics of ultra-wideband systems with single co-channel interference." Wireless Communications and Mobile Computing 13, no. 9 (2011): 864–73. http://dx.doi.org/10.1002/wcm.1146.

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21

Akella, Mohan R., Rajan Batta, Moises Sudit, Peter Rogerson, and Alan Blatt. "Cellular network configuration with co-channel and adjacent-channel interference constraints." Computers & Operations Research 35, no. 12 (2008): 3738–57. http://dx.doi.org/10.1016/j.cor.2007.02.006.

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22

ZHANG, Wei Jiong, Xi Lang ZHOU, and Rong Hong JIN. "MIMO-OC Scheme to Suppress Co-channel Interference." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E93-A, no. 6 (2010): 1244–47. http://dx.doi.org/10.1587/transfun.e93.a.1244.

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23

Ye, Jia, Shuping Dang, Basem Shihada, and Mohamed-Slim Alouini. "Modeling Co-Channel Interference in the THz Band." IEEE Transactions on Vehicular Technology 70, no. 7 (2021): 6319–34. http://dx.doi.org/10.1109/tvt.2021.3089427.

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24

Wang, L. C., and C. T. Lea. "Co-channel interference analysis of shadowed Rician channels." IEEE Communications Letters 2, no. 3 (1998): 67–69. http://dx.doi.org/10.1109/4234.662629.

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25

Lee, Seung-Hwan, Hyung-Sin Kim, and Yong-Hwan Lee. "Mitigation of Co-Channel Interference in Bluetooth Piconets." IEEE Transactions on Wireless Communications 11, no. 4 (2012): 1249–54. http://dx.doi.org/10.1109/twc.2012.021412.100185.

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26

Caijun Zhong, Shi Jin, and Kai-kit Wong. "MIMO rayleigh-product channels with co-channel interference." IEEE Transactions on Communications 57, no. 6 (2009): 1824–35. http://dx.doi.org/10.1109/tcomm.2009.06.070606.

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27

Li, Jian, Shenghong Li, Feng Zhao, and Rong Du. "Co-Channel Interference Modeling in Cognitive Wireless Networks." IEEE Transactions on Communications 62, no. 9 (2014): 3114–28. http://dx.doi.org/10.1109/tcomm.2014.2341628.

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28

Kozono, S. "Co-channel interference measurement method for mobile communication." IEEE Transactions on Vehicular Technology 36, no. 1 (1987): 7–13. http://dx.doi.org/10.1109/t-vt.1987.24091.

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29

Grant, Alex. "Co-channel interference reduction in Rayleigh fading channels." Digital Signal Processing 16, no. 5 (2006): 619–27. http://dx.doi.org/10.1016/j.dsp.2004.10.005.

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30

Abdulsatar Assim, Ara, Aarno Pärssinen, and Timo Rahkonen. "Cancelling Co-Channel Interference in Extremely Broadband Receivers." Journal of Communications 20, no. 2 (2025): 105–12. https://doi.org/10.12720/jcm.20.2.105-112.

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31

Hussain, Zakir, Rehman Khan Asim ur, Haider Mehdi, and Atif Saleem Syed Muhammad. "Analysis of D2D Communications over Gamma/Nakagami Fading Channels." Engineering, Technology & Applied Science Research 8, no. 2 (2018): 2693–98. https://doi.org/10.5281/zenodo.1257524.

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In this paper, we investigate the outage probability, channel capacity and symbol error rate (SER) performance of device-to-device (D2D) communication systems. The D2D communication system is affected by several co-channel interferers. Gamma fading channel is considered for the D2D communication system. The channel for the co-channel interference is assumed to be Nakagami faded. An expression for the probability density function (PDF) of the signal-tointerference ratio (SIR) is presented. The PDF is a function of distances between various devices in the D2D system, path-loss, channel fading co

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32

Rajesh, Varshini, and A. R. Abdul Rajak. "Cancellation Techniques for Co-channel Interference in MIMO-OFDM Systems and Evaluating Their Performance." Emerging Science Journal 5, no. 6 (2021): 824–39. http://dx.doi.org/10.28991/esj-2021-01313.

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In a wireless communication system, the transmitted signal is exposed to various surfaces where it bounces and results in several delayed versions of the same signal at the receiver end. The delayed signals are in the form of electromagnetic waves that are diffracted and reflected from the various object surfaces. These result in co-channel interferences for wireless systems. MIMO has proven to be a striking solution for the new generation of wireless systems. MIMO-OFDM system with QPSK modulation is considered as the wireless system for studying the performance of interference cancellation te

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33

Song, Xinkang, Shanghong Zhao, Xiang Wang, Xin Li, and Qin Tian. "Performance Analysis of UAV RF/FSO Co-Operative Communication Network with Co-Channel Interference." Drones 8, no. 3 (2024): 70. http://dx.doi.org/10.3390/drones8030070.

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The unmanned aerial vehicle (UAV) communication network has emerged as a promising paradigm capable of independent operation and as a relay to enhance communication coverage and efficiency. However, densely distributed terrestrial base stations with shared communication frequencies inevitably generate co-channel interference (CCI). The interference effect can be effectively eliminated by implementing free-space optical (FSO) communication in the UAV communication network. This paper proposes a solution for the UAV communication network to address interference effectively, specifically by emplo

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34

Dai, Yuan-Kao, Li-Hsing Yen, and Jia-Wei Su. "Toward an Access Infrastructure for Mobile Cloud." International Journal of Grid and High Performance Computing 5, no. 3 (2013): 6–19. http://dx.doi.org/10.4018/jghpc.2013070102.

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The provision of mobile cloud service calls for a wireless access infrastructure that offers high bandwidth to mobile users. Among all enabling technologies, wireless mesh networks (WMNs) have the advantage of low deployment cost and widely available user equipments. To provide more bandwidth, access points in WMNs are commonly equipped with multiple wireless interfaces (radios) that can operate on multiple non-overlapping channels in parallel. The objective of channel assignments in a multi-channel, multi-radio MWN is to reduce co-channel interference experienced by links so as to increase ne

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35

Hu, Donglin, and Shiwen Mao. "On co-channel and adjacent channel interference mitigation in cognitive radio networks." Ad Hoc Networks 11, no. 5 (2013): 1629–40. http://dx.doi.org/10.1016/j.adhoc.2013.02.009.

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36

Wang, Maolin, Xu Ma, Zhi Wang, and Yang Guo. "Analysis of Co-Channel Interference in Connected Vehicles WLAN with UAV." Wireless Communications and Mobile Computing 2022 (January 31, 2022): 1–12. http://dx.doi.org/10.1155/2022/6045213.

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Unmanned aerial vehicle (UAV) has the advantages of flexibility, strong controllability, and easy deployment. It provides wireless communication with low delay and high throughput. However, under the background of the increasing shortage of spectrum resources, the frequency band resources of UAV systems are tight, resulting in increasingly serious co-channel interference between services, and the communication quality cannot be effectively guaranteed. Therefore, it is very important to evaluate the co-channel interference of UAV system and improve its spectral efficiency. This paper introduces

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37

Mital, Rajeev Kumar, and Umesh Kumar. "A Cumulative Study of Performance Degrading Factors in a High Capacity Cellular Zone System." Active and Passive Electronic Components 18, no. 2 (1995): 119–28. http://dx.doi.org/10.1155/1995/81872.

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In high capacity cellular zone systems, cell size is reduced considerably: hence cells may be re-defined as microcells. The key point in microcell interference modeling is that the desired signal, as wall as co-channel interferers' signals should have different statistics. A microcell interference model that which provides different fading parameters to the concerned signals is used in this paper to evaluate various performance degrading factors. Outage probability and spectrum efficiency have been calculated. Various techniques to counteract the above mentioned interferences have been suggest

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38

Zhao, Ting-ting, and Yu-ping Zhao. "A Co-channel Interference Suppression Scheme in OFDM Systems." Journal of Electronics & Information Technology 33, no. 8 (2011): 1993–97. http://dx.doi.org/10.3724/sp.j.1146.2010.01294.

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39

Liu, Chenguang, Yunfei Chen, and Shuang-Hua Yang. "Signal detection with co-channel interference using deep learning." Physical Communication 47 (August 2021): 101343. http://dx.doi.org/10.1016/j.phycom.2021.101343.

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40

Feng, Man, and Lenan Wu. "Novel Anti Co-Channel Interference Scheme for Sensor Networks." Sensors 10, no. 4 (2010): 3170–79. http://dx.doi.org/10.3390/s100403170.

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41

Ryu, Kwanwoong, Sung Ik Park, and Heung Mook Kim. "Analysis on Co-channel Interference Coverage of ATSC DTV." Journal of Broadcast Engineering 18, no. 1 (2013): 59–65. http://dx.doi.org/10.5909/jbe.2013.18.1.59.

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42

Yang, Liang, and Mohamed-Slim Alouini. "Outage Probability of Distributed Beamforming with Co-Channel Interference." IEEE Communications Letters 16, no. 3 (2012): 334–37. http://dx.doi.org/10.1109/lcomm.2011.122211.112096.

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43

Chen, S., S. McLaughlin, B. Mulgrew, and P. M. Grant. "Bayesian decision feedback equaliser for overcoming co-channel interference." IEE Proceedings - Communications 143, no. 4 (1996): 219. http://dx.doi.org/10.1049/ip-com:19960612.

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44

Giangaspero, L., L. Agarossi, G. Paltenghi, S. Okamura, M. Okada, and S. Komaki. "Co-channel interference cancellation based on MIMO OFDM systems." IEEE Wireless Communications 9, no. 6 (2002): 8–17. http://dx.doi.org/10.1109/mwc.2002.1160076.

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45

Srinivasan, Muralikrishnan, and Sheetal Kalyani. "Analysis of MRC With $\eta -\mu$ Co-Channel Interference." IEEE Transactions on Vehicular Technology 69, no. 1 (2020): 738–45. http://dx.doi.org/10.1109/tvt.2019.2954129.

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46

Daoud Yacoub, M. "Fading distributions and co-channel interference in wireless systems." IEEE Antennas and Propagation Magazine 42, no. 1 (2000): 150–60. http://dx.doi.org/10.1109/74.826357.

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47

Ji, Baofeng, Jun Zhu, Kang Song, Yongming Huang, and Luxi Yang. "Performance analysis of femtocells network with co-channel interference." Signal Processing 100 (July 2014): 32–41. http://dx.doi.org/10.1016/j.sigpro.2014.01.006.

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48

Meng, Xin, Bin Jiang, and XiQi Gao. "Efficient co-channel interference suppression in MIMO-OFDM systems." Science China Information Sciences 58, no. 2 (2014): 1–15. http://dx.doi.org/10.1007/s11432-014-5099-3.

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49

Abdelsalam Ahmed, Ahmed Mohamed, and Ian Marsland. "Downlink co-channel interference cancellation in multihop relay networks." Computer Communications 32, no. 7-10 (2009): 1131–37. http://dx.doi.org/10.1016/j.comcom.2008.10.013.

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50

Furukawa, H., Y. Kamio, and H. Sasaoka. "Co-channel interference canceller using CMA adaptive array antenna." Electronics Letters 33, no. 13 (1997): 1106. http://dx.doi.org/10.1049/el:19970749.

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