Refine your search
Collections
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Shaikh, Mohammad Shahnawaz
- Improving the Requirements Based Bandwidth Allocation In 5G Point To Point Networks
Abstract Views :87 |
PDF Views:1
Authors
Affiliations
1 Department of Electronic and Communication Engineering, K.L.E. College of Engineering and Technology, IN
2 Department of Computer Science and Business System, R.M.K Engineering College, IN
3 Department of Computer Science, Kristu Jayanti College, IN
4 Department of Electronics and Telecommunication Engineering, G.H. Raisoni College of Engineering, IN
1 Department of Electronic and Communication Engineering, K.L.E. College of Engineering and Technology, IN
2 Department of Computer Science and Business System, R.M.K Engineering College, IN
3 Department of Computer Science, Kristu Jayanti College, IN
4 Department of Electronics and Telecommunication Engineering, G.H. Raisoni College of Engineering, IN
Source
ICTACT Journal on Communication Technology, Vol 13, No 4 (2022), Pagination: 2810-2814Abstract
In General, the 5G is a fifth-generation technology that works at speeds of 4G to 100 times the network speed. The main objective of introducing modern information technologies is to facilitate and facilitate access to public services. The use of new technologies is a key factor in improving the overall structure of public administration and increasing its efficiency. In addition, it is important to improve the infrastructure of all types of communications. The telecom operators are often willing to invest more in infrastructure development. In this paper, a new model was proposed to enhance the bandwidth allocation and utilization. It is a requirements-based network that allows the users to increase the speed of wireless networks. This proposed method also increases the amount of data that can be transmitted over wireless networks.Keywords
5G, Telecom Operators, Bandwidth, Wireless Networks
References
- E. Hossain, D. Niyato, and Z. Han, “Dynamic Bandwidth Access in Cognitive Radio Networks”, Cambridge University Press, 2009.
- T.D. Lagkas and I. Tomkos, “Joint Spatial and Spectral Resource Optimization over Both Wireless and Optical Fronthaul Domains of 5G Architectures”, Proceedings of International Conference on Transparent Optical Networks, pp. 1-7, 2020.
- Yuan Ai and Yaohua Sun, “Joint Resource Allocation and Admission Control in Sliced Fog Radio Access Networks”, China Communications, Vol. 17, No. 8, pp. 14-30, 2020.
- N. Khumalo and L. Mfupe, “Reinforcement Learning-based Computation Resource Allocation Scheme for 5G Fog-Radio Access Network”, Proceedings of International Conference on Fog and Mobile Edge Computing, pp. 353-355. 2020.
- Y.H. Robinson, V. Saravanan and P.E. Darney, “Enhanced Energy Proficient Encoding Algorithm for Reducing Medium Time in Wireless Networks”, Wireless Personal Communications, Vol. 119, No. 4, pp. 3569-3588, 2021.
- V. Hanumante and S. Roy, “Comparative Study of Microstrip Patch Antenna Using Different Dielectric Materials”, Proceedings of International Conference on Microwave, Antennas and Propagation, Remote Sensing, pp. 56-60, 2013.
- Y. Wang, K. Wang, H. Huang, T. Miyazaki and S. Guo, “Traffic and Computation Co-Offloading With Reinforcement Learning in Fog Computing for Industrial Applications”, IEEE Transactions on Industrial Informatics, Vol. 15, No. 2, pp. 976-986, 2019.
- J. Gowrishankar, P.S. Kumar and T. Narmadha, “A Trust Based Protocol for Manets in IoT Environment”, International Journal of Advanced Science and Technology, Vol. 29, No. 7, pp. 2770-2775, 2020.
- L. Huang, X. Feng, C. Zhang, L. Qian and Y. Wu, “Deep Reinforcement Learning-based Joint Task Offloading and Bandwidth Allocation for Multiuser Mobile Edge Computing”, Digital Communications and Networks, Vol. 5, No. 1, pp. 10-17, 2019.
- C. Yang, J. Li, M. Guizani and M. Elkashlan “Advanced Bandwidth Sharing in 5G Cognitive Heterogeneous Networks”, IEEE Wireless Communications, Vol. 15, No. 2, pp. 94-101, 2016.
- M. Rajalakshmi, V. Saravanan and C. Karthik, “Machine Learning for Modeling and Control of Industrial Clarifier Process”, Intelligent Automation and Soft Computing, Vol. 32, No. 1, pp. 339-359, 2022.
- M. Matinmikko, P. Ahokangas and M. Mustonen, “Bandwidth Sharing using Licensed Shared Access: The Concept and its Workflow for LTE-Advanced Networks”, IEEE Wireless Communications, Vol. 21, No. 2, pp. 72-79, 2014.
- E. Jorswieck, E. Karipidis and J. Luo, “Bandwidth Sharing Improves the Network Efficiency for Cellular Operators”, IEEE Communications Magazine, Vol. 52, No. 3, pp. 129-136. 2014.
- N. Michelusi, M. Nokleby, U.i Mitra, and R. Calderbank “Multi-Scale Bandwidth Sensing in Dense Multi-Cell Cognitive Networks”, IEEE Transactions on Wireless Communications, vol. 67, no. 4, pp. 2673–2688, 2019
- Z. Ai and H. Zhang, “A Smart Collaborative Charging Algorithm for Mobile Power Distribution in 5G Networks”, IEEE Access, Vol. 6, pp. 28668-28679, 2018.
- Enhancement of Bandwidth and Beam Forming Antenna Arrays in 5G Cellular Communication Networks
Abstract Views :95 |
PDF Views:1
Authors
Affiliations
1 Department of Electronics and Telecommunication Engineering, GH Raisoni Institute of Engineering and Technology, IN
2 Department of Computer Science, Soundarya Institute of Management and Science, IN
3 Department of Electronic and Communication Engineering, K.L.E. College of Engineering and Technology, IN
4 Department of Electronics and Communication Engineering, Samara University, ET
1 Department of Electronics and Telecommunication Engineering, GH Raisoni Institute of Engineering and Technology, IN
2 Department of Computer Science, Soundarya Institute of Management and Science, IN
3 Department of Electronic and Communication Engineering, K.L.E. College of Engineering and Technology, IN
4 Department of Electronics and Communication Engineering, Samara University, ET
Source
ICTACT Journal on Communication Technology, Vol 13, No 4 (2022), Pagination: 2820-2825Abstract
In general, an antenna is an interface that transmits signal data and receives incoming signal data. The radio waves received through this interface help to do the necessary things for the transmitter and receiver circuit systems used there. Also a radio transmitter antenna transmits different waves generated from the current generated at its tip to different areas. In this paper, the functions of increasing its bandwidth by making changes in some dimensions of the antenna are proposed. The oscillating current used in its transmitter area increases its vibration waves. This increases the amount of airwaves generated there and the number of data transmitted through it. So its bandwidth is more likely to be high. Furthermore these functions generate varying magnetic fields so that the time taken by the cross-sectional magnetic fields of the antenna varies.Keywords
Antenna, Radio Waves, Electric Current, Radio Transmitter, Bandwidth, Broadcasting, Two-Way RadioReferences
- S.F. Chuang and Y.T. Liu, “High-Resolution AoA Estimation for Hybrid Antenna Arrays”, IEEE Transactions on Antennas Propagations, Vol. 63, No. 7, pp. 2955-2968, 2015.
- X.M. Chen, Z.Y. Zhang and H.H. Chen, “Enhancing Wireless Information and Power Transfer by Exploiting Multi-Antenna Techniques”, IEEE Communications Magazine, Vol. 53, No. 4, pp. 133-141, 2015.
- S. Darzi, T.S. Kiong and M.T. Islam, “Null Steering of Adaptive Beam Forming using Linear Constraint Minimum Variance Assisted by Particle Swarm Optimization, Dynamic Mutated Artificial Immune System, and Gravitational Search Algorithm”, Scientific World Journal, Vol. 2014, pp. 1-19, 2014.
- P Saravanan, V. Thirukumaran, S. Anitha and S. Shanthana, “Enabling Self Auditing for Mobile Clients in Cloud Computing”, International Journal of Advanced Computer Technology, Vol. 2, pp. 53-60, 2013.
- M. Mohammed and V. Manikandan, “Advanced Expert System using Particle Swarm Optimization based Adaptive Network based Fuzzy Inference System to Diagnose the Physical Constitution of Human Body”, Proceedings of International Conference on Emerging Technologies in Computer Engineering, pp. 349-362, 2019.
- M.H. Alsharif, A.H. Kelechi, M.A. Albreem and S. Kim, “Sixth Generation (6G) Wireless Networks: Vision, Research Activities, Challenges and Potential Solutions”, Symmetry, Vol. 12, No. 4, pp. 676-687, 2020.
- H. Ahmadi and N. Marchetti, “A Game Theoretic Approach for Pilot Contamination Avoidance in Massive MIMO”, IEEE Wireless Communications, Vol. 5, No. 1, pp. 12-15, 2019.
- G. Dhiman and S. Chandragandhi, “An IoT and Machine Learning‐based Routing Protocol for Reconfigurable Engineering Application”, IET Communications, Vol. 45, No. 1, pp. 1-14, 2021.
- M. Rajalakshmi, V. Saravanan and C. Karthik, “Machine Learning for Modeling and Control of Industrial Clarifier Process”, Intelligent Automation and Soft Computing, Vol. 32, No. 1, pp. 339-359, 2022.
- K. Sakthisudhan and P.N.S. Sailaja, “Textile EF Shaped Antenna based on Reinforced Epoxy for Breast Cancer Detection by Composite Materials”, Materials Today: Proceedings, Vol. 45, pp. 6142-6148, 2021.
- J.S. Bae and J.S. Kim, J.S., “Architecture and Performance Evaluation of Mmwave Based 5G Mobile Communication System”, Proceedings of International Conference on Information and Communication Technology Convergence, p.847-851, 2014.
- T. Karthikeyan and K. Praghash, “An Improved Task Allocation Scheme in Serverless Computing using Gray Wolf OPTIMIZATION (GWO) based Reinforcement Learning (RIL) Approach”, Wireless Personal Communications, Vol. 117, No. 3, pp. 2403-2421, 2021.
- S. Barua, S.C. Lam and P. Ghosa, “A Survey of Direction of Arrival Estimation Techniques and Implementation of Channel Estimation based on SCME”, Proceedings of International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, p.1-5, 2015.
- M.Z.A. Bhotto, “Constant Modulus Blind Adaptive Beamforming based on Unscented Kalman Filtering”, IEEE Signal Processing Letters, Vol. 22, No. 4, pp. 474-478, 2015.
- S.A. Syed, K. Sheela Sobana Rani, K.K. Chennam and R. Jaikumar, “Design of Resources Allocation in 6G Cybertwin Technology using the Fuzzy Neuro Model in Healthcare Systems”, Journal of Healthcare Engineering, Vol. 2022, pp. 1-9, 2022.