Mobile QR Code QR CODE

2024

Acceptance Ratio

21%

※ The user interface design of www.ieiespc.org has been recently revised and updated. Please contact inter@theieie.org for any inquiries regarding paper submission.

Journal Search

  1. Home
  2. Archive
  3. 2021-06 (Vol.10 No.03)
  4. 10.5573/IEIESPC.2021.10.3.259
XML PDF INFO REF

REFERENCES

1 
Wadhwa N., Rangi S., Rathee D., 2014, Inter-symbol Interference Reduction and Bit Error Rate Reduction In Wireless Channels Using Zero Forcing Equalizer., IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), Vol. vol 9, No. issue 3, pp. 82-85.DOI
2 
García M., Oberli C., 2009, Inter-carrier Interference in OFDM: A General Model for Transmissions in Mobile Environments With Imperfect Synchronization., Eurasip Journal on Wireless Communications and Networking, Vol. 2009 (1)DOI
3 
Diana D. C., Rani S. P. J. V., 2016, Enhancement in channel equalization Using Particle Swarm Optimization Techniques., Circuits and Systems, Vol. 7, pp. 4071-4084.DOI
4 
Barhumi I., Leus G., Moonen M., 2006, Equalization for OFDMo Doubly Selective Channels., IEEE Transactions On Signal Processing, Vol. 54, No. 4, pp. 1445-1458DOI
5 
Agarwal A., Sur S. N., Singh A. K., Gurung H., Gupta A. K., Bera R., 2012, Performance Analysis of Linear and Non-Linear Equalizer in RICIAN Channel., Procedia Technology, Vol. 4, pp. 687-691.DOI
6 
Barhumi I., 2005, Transmission over Time- And Frequency-Selective Mobile Wireless Channels., Katholieke Universiteit Leuven, PhD Thesis.URL
7 
Das , Pattnaik P.K., Padhy S.K., 2014, Artificial Neural Network Trained By Particle Swarm Optimization For Nonlinear Channel Equalization, Expert Systems With Applications, Vol. 41, No. , pp. 3491-3496.DOI
8 
Muhammad T. N. Qaisrani , Imad Barhumi , 2015, A Low Complexity Approach To Equalization For Doubly Selective Channels, Wirel. Commun. Mob. Comput., Vol. 15, pp. 1882-1896DOI
9 
Zaka U., Tauqir I., Siddiqui A.M., Rashdi A., 2017, Time Varying Equalization Of Doubly Selective Channel, Sci. Int. (Lahore), Vol. 29, No. 1, pp. 153-156URL
10 
Sebald Daniel J., Bucklew James A., 2000, Support Vector Machine Techniques For Nonlinear Equalization, IEEE Transactions On Signal Processing, Vol. 48, No. 11DOI
11 
Guerreiro , Dinis R., Montezuma P., 2012, Ml-Based Receivers for Underwater Networks Using OFDM Signals with Strong Non Linear Distortion Effects, Military Communication Conference, pp. 1-7DOI
12 
Li Yabo , Ngebani I., Xia Xiang-Gen , 2012, On Performance of V-OFDM with Zero Forcing Receiver, IEEE International Conference On Signal Processing, Vol. 2, pp. 1506-1511DOI
13 
Hrycak T., Das S., Matz G., 2012, Inverse Methods for Reconstruction of Channel Taps in OFDM Systems, IEEE Trans. On Signal Processing, Vol. 60, No. 5, pp. 2666-2671DOI
14 
Liu G., Zhidkov S. V., Li H., Zeng L., 2012, Low-Complexity Iterative Equalization For Symbol-Reconstruction-Based OFDM Receivers Over Doubly Selective Channels, IEEE Trans. On Broadcasting, Vol. 58, No. 3, pp. 390-400DOI
15 
Wang , Sha X., Mei L., Qiu X., 2012, Performance Analysis of Hybrid Carrier System with Mmse Equalization Over Doubly-Dispersive Channels, IEEE Communication Letters, Vol. 16, No. 7, pp. 1048-1051DOI
16 
Barhumi , 2012, Soft-Output Decision Feedback Equalization for Orthogonal Frequency Division Multiplexing Over Doubly Selective Channels, IET Communication, Vol. 6, No. 13, pp. 1890-1897DOI
17 
Haykin Simon, 2002, Adaptive Filter Theory, Fourth Ed. Pearson EducationURL
18 
Li Y., Chen M., Yang Y., Zhou M., 2017, Convolutional Recurrent Neural Network-Based Channel Equalization: An Experimental Study., In 2017 23rd Asia-Pacific Conference On Communi-cations (APCC), pp. pages 1-6DOI
19 
Trimeche A., Sakly A., Mtibaa A., 2015, FPGA Implementation of Ml, Zf and MMSE Equalizers for MIMO Systems., The International Conference on Advanced Wireless, Information, and Communi-cation Technologies, pp. 226-233.DOI
20 
Huang Y., Lu C., Berg M, Odling P., 2018, Functional Split of Zero-Forcing Based Massive MIMO for Fronthaul Load Reduction., IEEE Access, Vol. 6, pp. 6350-6359.DOI
21 
Ramadan K., Dessouky M. I., Elagooz S., Elkordy M., Abd El-Samie F. E., 2017, Equalization and Carrier Frequency Offset Compensation For Underwater Acoustic OFDM Systems., Annals Of Data Science, Vol. 5, No. issue 2, pp. 259-272.DOI
22 
Disxit S., Nagaria D., 2017, LMS Adaptive Filters for Noise Cancellation: A Review., International Journal of Electrical and Computer Engineering (IJECE), Vol. 7, No. 5, pp. 2520-2529.DOI
23 
Mishra R. C., Bhattacharjee R., 2017, Performance Analysis of Adaptive DFE Using Set-Membership Binormalized Data-Reusing LMS Algorithm for Frequency Selective Mimo Channels., Aeu - International Journal of Electronics and Communications, Vol. 77, pp. 91-99.DOI
24 
Li B., Yang H., Liu G., Peng X., 2017, A New Joint Channel Equalization and Estimation Algorithm for Underwater Acoustic Channels., Eurasip Journal on Wireless Communications and Networking.DOI
25 
Martinek R., Konecny J., Koudelka P., Nazeran H., 2017, Adaptive Optimization Of Control Parameters For Feed-Forward Software Defined Equalization., Wireless Personal Communications, Vol. 95, pp. 4001-4011.DOI
26 
Shah S. M., Samar R., Khan N. M., Raja M. A. Z., 2016, Design Of Fractional-Order Variants Of Complex LMS And NLMS Algorithms for Adaptive Channel Equalization., Nonlinear Dynamics, Vol. 88, pp. 839-858.DOI
27 
Nanda S. J., Jonwal N., 2017, Robust Nonlinear Channel Equalization Using Wnn Trained By Symbiotic Organism Search Algorithm., Applied Soft Computing, Vol. 57, pp. 197-209.DOI
28 
Zahoor T., Sabraj D. M., 2018, Lms-Rls Joint Adaptive Equalization In Wireless Communications., International Journal of Advanced Research In Computer Science, Vol. 9, No. 2, pp. 749-753URL
29 
Thu N. N., Sylvester G., Memon F. A., Bu C., 2019, Channel Equalization Techniques To Mitigate Inter-Symbol Interference In Wireless Communi-cation., International Journal Of Research In Engineering And Innovation (IJREI), Vol. 3, No. 3, pp. 195-199URL
30 
Bierk H., Alsaedi M. A., 2019, Recursive Least Squares Algorithm For Adaptive Transversal Equalization Of Linear Dispersive Communication Channel., Journal Of Engineering Science And Technology, Vol. 14, No. 2, pp. 1043-1054.URL
31 
Zhang Y., Zakharov Y. V., Li J., 2018, Soft-Decision-Driven Sparse Channel Estimation and Turbo Equalization for Mimo Underwater Acoustic Communications., IEEE Access, Vol. 6, pp. 4955-4973DOI
32 
Wang H., Guo Y., 2015, A Blind Equalization Algorithm Based on Global Artificial Fish Swarm and Genetic Optimization DNA Encoding Sequences., International Industrial Informatics and Computer Engineering Conference (IIICEC 2015), pp. 131-134DOI
33 
Geng Y., Zhang L., Sun Y., Zhang Y., Yang N., Wu J., 2016, Research on Ant Colony Algorithm Optimization Neural Network Weights Blind Equalization Algorithm., International Journal of Security and Its Applications, Vol. 10, No. 2, pp. 95-104DOI
34 
D.C. D. , S.P. J. V. R. , 2017, Novel Cat Swarm Optimization Algorithm to Enhance Channel Equalization., Compel - The International Journal For Computation And Mathematics In Electrical And Electronic Engineering, Vol. 36, No. 1, pp. 350-363DOI
35 
Utkarsh A., Kantha A. S., Praveen J., Kumar J. R., 2015, Hybrid GA-PSO Trained Functional Link Artificial Neural Network Based Channel Equalizer., 2nd International Conference on Signal Processing and Integrated Networks (Spin), pp. 285-290DOI
36 
Sahoo J., Mishra L., Mohanty M. N., 2016, Ga Based Optimization of Sign Regressor Flann Model for Channel Equalization., Advances in Intelligent Systems and Computing, pp. 124-130DOI
37 
Iqbal N., Zerguine A., Al-Dhahir N., 2015, Decision Feedback Equalization Using Particle Swarm Optimization., Signal Processing, Vol. 108, pp. 1-12DOI
38 
Lalbakhsh A., Afzal M. U., Esselle K. P., 2017, Multi-objective Particle Swarm Optimization to Design a Time-Delay Equalizer Metasurface for an Electromagnetic Band-Gap Resonator Antenna., IEEE Antennas and Wireless Propagation Letters, Vol. 16, pp. 912-915DOI
39 
Çavdar T., 2016, PSO Tuned ANFIS Equalizer Based On Fuzzy C-Means Clustering Algorithm., Aeu - International Journal of Electronics and Communications, Vol. 70, No. 6, pp. 799-807DOI
40 
Sarangi A., Priyadarshini S., Sarangi S. K., 2016, A MLP Equalizer Trained By Variable Step Size Firefly Algorithm for Channel Equalization., 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (Icpeices).DOI
41 
Romia A. M., Ali H. S., Abdalla M. I., 2018, Design Optimization of LMS-Based Adaptive Equalizer for Zigbee Systems with Fading Channels., 2018 International Conference On Computing Mathematics And Engineering Technologies (ICOMET).DOI
42 
Diana D. C., Rani S. P. J. V., 2016, Enhancement in channel equalization Using Particle Swarm Optimization Techniques., Circuits and Systems, Vol. 7, pp. 4071-4084DOI
43 
Das G., Panda S., Padhy S. K., 2017, Quantum Particle Swarm Optimization Tuned Artificial Neural Network Equalizer., Soft Computing: Theories and Applications, pp. 579-585DOI
44 
Saideh M., Berbineau M., Dayub L., 2018, On Doubly Selective Channel Estimation for Fbmc-Oqam Using The Lmmse Filter For Future Railway Communications., 16th International Conference on Intelligent Transportation Systems Telecommuni-cations (Itst).DOI
45 
Ma X., Yang F., Liu S., Song J., Han Z., 2018, Sparse Channel Estimation for MIMO-OFDM Systems in High-Mobility Situations., IEEE Transactions on Vehicular Technology, Vol. 67, No. 5, pp. 6113-6124DOI
46 
Wei L., Zheng J., 2019, Approximate Message Passing-Aided Iterative Channel Estimation and Data Detection of OFDM-IM in Doubly Selective Channels., IEEE Access, Vol. 7, pp. 133410-133420DOI
47 
Yong L., Guodong S., Xuanfan S., Zhumin Z., Xinyi Y., Xiaoyan Z., Haimei Y., Nan Z., 2018, BEM-Based Channel Estimation and Interpolation Methods for Doubly-Selective OFDM Channel., BEM-Based Channel Estimation and Interpolation Methods for Doubly-Selective OFDM Channel, pp. 70-75DOI
48 
Yang Y., Gao F., Ma X., Zhang S., 2019, Deep Learning-Based Channel Estimation For Doubly Selective Fading Channels., IEEE Access, Vol. 7, pp. 36579-36589DOI
49 
Tian Z., Fong S., 2016, Survey of Meta-Heuristic Algorithms for Deep Learning Training., Optimization Algorithms - Methods and Applications.DOI
50 
Mohammad Khajehzadeh , Mohd Raihan Taha , Ahmed El-Shafie , Mahdiyeh Eslami. , 2011, A Survey on Meta-Heuristic Global Optimization Algorithms., Research Journal of Applied Sciences, Engineering and Technology, Vol. 3, No. 6, pp. 569-578URL
51 
Hamamoto A. H., Carvalho L. F., Sampaio L. D. H., Abrão T., Proença M. L., 2018, Network Anomaly Detection System using Genetic Algorithm and Fuzzy Logic., Expert Systems with Applications, Vol. 92, pp. 390-402DOI
52 
M. F. Sohail , Sheraz Alam , Asad Hussain , Sajjad A. Ghauri , Mubashar Sarfraz , M. A. Ahmed. , 2017, Multiuser detection: Comparative analysis of heuristic approach., International Journal of Advanced and Applied Sciences, Vol. 4, No. 6, pp. 115-120URL
53 
Sheraz Alam , Mubashar Sarfraz , M. B. Usman , M. A. Ahmad , 2017, , Dynamic resource allocation for cognitive radio based smart grid communication networks., International Journal of Advanced and Applied Sciences, Vol. 4, No. 10, pp. 76-83URL
54 
Saptarshi Sengupta , Sanchita Basak , Richard Alan Peters II. , Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives., Machine learning and knowledge extraction, Vol. 1, No. , pp. 157-191DOI
55 
Tharwat A., Elhoseny M., Hassanien A. E., Gabel T., Kumar A., 2018, Intelligent Bézier curve-based path planning model using Chaotic Particle Swarm Optimization algorithm., Cluster Computing.DOI
56 
Wang D., Tan D., Liu L., 2017, Particle swarm optimization algorithm: an overview., Soft Computing, Vol. 22, No. 2, pp. 387-408DOI
57 
Pan X., Xue L., Lu Y., Sun N., 2018, Hybrid particle swarm optimization with simulated annealing., Multimedia Tools and Applications.DOI
58 
Xu G., Yu G., 2018, Reprint of: On convergence analysis of particle swarm optimization algorithm., Journal of Computational and Applied Mathematics, Vol. 340, pp. 709-717DOI
59 
Rahmani Hosseinabadi A. A., Vahidi J., Saemi B., Sangaiah A. K., Elhoseny M., 2018, Extended Genetic Algorithm for solving open-shop scheduling problem., Soft Computing.DOI
60 
Deng W., Liu H., Xu J., Zhao H., Song Y., 2020, An Improved Quantum-Inspired Differential Evolution Algorithm for Deep Belief Network., IEEE Transactions on Instrumentation and MeasurementDOI
61 
Mohamed A. W., 2017, A novel differential evolution algorithm for solving constrained engineering optimization problems., Journal of Intelligent Manufacturing, Vol. 29, No. 3, pp. 659-692DOI
62 
Peng L., Liu S., Liu R., Wang L., 2018, Effective Long short-term Memory with Differential Evolution Algorithm for Electricity Price Prediction., Energy.DOI
63 
Wu X., Che A., 2018, A memetic differential evolution algorithm for energy-efficient parallel machine scheduling., Omega.DOI
64 
Alam S., Malik A. N., Qureshi I. M., Ghauri S. A., Sarfraz M., 2018, Clustering-Based Channel Allocation Scheme for Neighborhood Area Network in a Cognitive Radio Based Smart Grid Communication., IEEE Access, Vol. 6, pp. 25773-25784DOI
65 
Pappula L., Ghosh D., 2018, Cat swarm optimization with normal mutation for fast convergence of multimodal functions., Applied Soft Computing, Vol. 66, pp. 473-491DOI
66 
Zhang Y.-D., Sui Y., Sun J., Zhao G., Qian P., 2018, Cat Swarm Optimization applied to alcohol use disorder identification., Multimedia Tools and Applications, Vol. 77, No. 17, pp. 22875-22896DOI
67 
Guo L., Meng Z., Sun Y., Wang L., 2018, A modified cat swarm optimization based maximum power point tracking method for photovoltaic system under partially shaded condition., Energy, Vol. 144, pp. 501-514DOI
68 
Alarifi A., Tolba A., Al-Makhadmeh Z., Said W., 2018, A big data approach to sentiment analysis using greedy feature selection with cat swarm optimization-based long short-term memory neural networks., The Journal of Supercomputing.DOI
69 
Xue Y., Jiang J., Zhao B., Ma T., 2017, A self-adaptive artificial bee colony algorithm based on global best for global optimization., Soft Computing, Vol. 22, No. 9, pp. 2935-2952DOI
70 
Chen J., Yu W., Tian J., Chen L., Zhou Z., 2018, Image contrast enhancement using an artificial bee colony algorithm., Swarm and Evolutionary Computation, Vol. 38, pp. 287-294DOI
71 
Han X, Wang Y, Cai C, Hou X, Wang L, 2020, An Efficient Universal Bee Colony Optimization Algorithm., Tehnicki Vjesnik - Technical Gazette, Vol. 27, No. 1DOI
72 
Rao H., Shi X., Rodrigue A. K., Feng J., Xia Y., Elhoseny M., Gu L., 2018, Feature selection based on artificial bee colony and gradient boosting decision tree., Applied Soft Computing.DOI
73 
Moslehi F., Haeri A., Martínez-Álvarez F., 2019, A novel hybrid GA-PSO framework for mining quantitative association rules., Soft Computing.DOI
74 
Liang Z., Ouyang J., Yang F., 2018, A hybrid GA-PSO optimization algorithm for conformal antenna array pattern synthesis., Journal of Electromagnetic Waves and Applications, Vol. 32, No. 13, pp. 1601-1615DOI
75 
Shah S. I. H., Alam S., Ghauri S. A., Hussain A., Ansari F. A., 2019, A Novel Hybrid Cuckoo Search-Extreme Learning Machine Approach for Modulation Classification., IEEE AccessDOI
76 
Alam S., Aqdas N., Qureshi I. M., Ghauri S. A., Sarfraz M., 2019, Joint power and channel allocation scheme for IEEE 802.11af based smart grid communication network., Future Generation Computer Systems.DOI
77 
Ali M., Ahn C. W., 2014, An optimal image watermarking approach through cuckoo search algorithm in wavelet domain., International Journal of System Assurance Engineering and Management, Vol. 9, No. 3, pp. 602-611DOI
78 
Aziz M. A. E., Hassanien A. E., 2016, Modified cuckoo search algorithm with rough sets for feature selection., Neural Computing and Applications, Vol. 29, No. 4, pp. 925-934DOI