Low Access Latency and High Throughput for Full-Duplex Cognitive Radio Using Mobility Caching Placement Strategy

Madhunala  Srilatha; Anantha  Bharathi

doi:10.46604/aiti.2022.8504

Authors

Madhunala Srilatha Department of Electronics and Communication Engineering, Vardhaman College of Engineering, Hyderabad, India
Anantha Bharathi Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, Hyderabad, India

DOI:

https://doi.org/10.46604/aiti.2022.8504

Keywords:

full-duplex cognitive radio, latency, mobility caching placement strategy, self-residual suppression

Abstract

In a remote framework, the densely allotted radio range is not effectively utilized by an authorized primary user, which limits a secondary user to avoid disturbance to a primary user while utilizing a channel. To solve the shortage problem of accessible range, this study proposes a mobility caching placement strategy (MCPS) based sliding window scheme to optimize the latency and throughput of cognitive radio system. The performance parameters of the proposed system are analyzed using energy detection metrics by considering full-duplex communication. By the MATLAB analysis and the evaluation with and without self-interference suppression, the results demonstrate that the entrance inactivity of the MCPS based sliding window is diminished by a factor of 1.9 as contrasted with the existing full-duplex systems. With the improved latency and throughput, the proposed method can avoid the ruinous impacts of drawn-out self-residual suppression more effectively compared to the existing approaches.

References

A. Kumar and K. Kumar, “Multiple Access Schemes for Cognitive Radio Networks: A Survey,” Physical Communication, vol. 38, 100953, February 2020.

Federal Communications Commission, “Spectrum Policy Task Force Report”, Federal Communications Commission, Technical Report FCC 02-155, November 15, 2002.

J. Tiwari, A. Prakash, and R. Tripathi, “A Novel Cooperative MAC Protocol for Safety Applications in Cognitive Radio Enabled Vehicular Ad-Hoc Networks,” Vehicular Communications, vol. 29, 100336, June 2021.

O. Salameh, H. Bruneel, and S. Wittevrongel, “Performance Evaluation of Cognitive Radio Networks with Imperfect Spectrum Sensing and Bursty Primary User Traffic,” Mathematical Problems in Engineering, vol. 2020, 4102046, 2020.

A. El Rharras, M. Saber, A. Chehri, R. Saadane, N. Hakem, and G. Jeon, “Optimization of Spectrum Utilization Parameters in Cognitive Radio Using Genetic Algorithm,” Procedia Computer Science, vol. 176, pp. 2466-2475, October 2020.

B. Kodavati and M. Ramarakula, “Latency Based Re-Enforcement Learning over Cognitive Software Defined 5G Networks,” 7th International Conference on Advanced Computing and Communication Systems, pp. 1848-1853, March 2021.

J. N. Javed, M. Khalil, and A. Shabbir, “A Survey on Cognitive Radio Spectrum Sensing: Classifications and Performance Comparison,” International Conference on Innovative Computing, pp. 1-8, November 2019.

W. Khalid and H. Yu, “Sensing and Utilization of Spectrum with Cooperation Interference for Full-Duplex Cognitive Radio Networks,” 11th International Conference on Ubiquitous and Future Networks, pp. 598-600, July 2019.

V. Singh, A. Gadre, and S. Kumar, “Full-Duplex Radios: Are We There Yet?” Proc. of 19th ACM Workshop on Hot Topics in Networks, pp. 117-124, November 2020.

H. Alves, T. Riihonen, and H. A. Suraweera, Full-Duplex Communications for Future Wireless Networks, Singapore: Springer, 2020.

L. Irio, A. T. Abusabah, and R. Oliveira, “Residual Self-Interference Estimation in In-Band Full-Duplex Wireless Systems,” International Wireless Communications and Mobile Computing, pp. 1130-1134, June 2020.

G. Gaspard and D. S. Kim, “Optimal Sensing and Interference Suppression in 5G Cognitive Radio Networks,” Journal of Communications, vol. 15, no. 4, pp. 303-308, April 2020.

C. M. Wu, Y. C. Kao, and K. F. Chang, “A Multichannel MAC Protocol for IoT-Enabled Cognitive Radio Ad Hoc Networks,” Advances in Technology Innovation, vol. 5, no. 1, pp. 45-55, December 2019.

J. Tiwari, A. Prakash, and R. Tripathi, “A Multichannel Link-Layer Cooperation Protocol (MLCP) for Cognitive Radio Ad Hoc Network,” International Conference on VLSI, Communication, and Signal Processing, pp. 191-200, October 2019.

A. Kumar and K. Kumar, “Energy-Efficient Resource Optimization Using Game Theory in Hybrid NOMA Assisted Cognitive Radio Networks,” Physical Communication, vol. 47, 101382, August 2021.

H. Mokhtarzadeh, A. Taherpour, A. Taherpour, and S. Gazor, “Throughput Maximization in Energy Limited Full-Duplex Cognitive Radio Networks,” IEEE Transactions on Communications, vol. 67, no. 8, pp. 5287-5296, August 2019.

A. Ayesha and S. M. Chaudhry, “Self-Interference Cancellation for Full-Duplex Radio Transceivers Using Extended Kalman Filter,” National Academy Science Letters, vol. 43, no. 7, pp. 631-634, February 2020.

A. Ayesha, M. Rahman, A. Haider, and S. M. Chaudhry, “On Self-Interference Cancellation and Non-Idealities Suppression in Full-Duplex Radio Transceivers,” Mathematics, vol. 9, no. 12, 1434, June 2021.

G. Eappen and T. Shankar, “Multi-Objective Modified Grey Wolf Optimization Algorithm for Efficient Spectrum Sensing in the Cognitive Radio Network,” Arabian Journal for Science and Engineering, vol. 46, no. 4, pp. 3115-3145, November 2020.

V. Aswathi and A. V. Babu, “Full/Half Duplex Cooperative Relaying NOMA Network under Power Splitting Based SWIPT: Performance Analysis and Optimization,” Physical Communications, vol. 46, 101335, June 2021.

H. Jiang, Y. Wang, X. Yue, and X. Li, “Performance Analysis of NOMA-Based Mobile Edge Computing with Imperfect CSI,” EURASIP Journal on Wireless Communications and Networking, vol. 2020, 138, July 2020.

A. Kumar and K. Kumar, “Relay Sharing with DF and AF Techniques in NOMA Assisted Cognitive Radio Networks,” Physical Communication, vol. 42, 101143, October 2020.

K. Kirubahini, J. J. Triphena, P. G. S. Velmurugan, and S. J. Thiruvengadam, “Optimal Spectrum Sensing in Cognitive Radio Systems Using Signal Segmentation Algorithm,” International Conference on Wireless Communications, Signal Processing, and Networking, pp. 118-121, August 2020.

S. DasMahapatra, S. Patnaik, S. N. Sharan, and M. Gupta, “Performance Analysis of Prediction-Based Spectrum Sensing for Cognitive Radio Networks,” 2nd International Conference on Intelligent Communication and Computational Techniques, pp. 271-274, September 2019.

R. Li and P. Zhu, “Spectrum Allocation Strategies Based on QoS in Cognitive Vehicle Networks,” IEEE Access, vol. 8, pp. 99922-99933, May 2020.

L. Li, G. Zhao, and R. S. Blum, “A Survey of Caching Techniques in Cellular Networks: Research Issues and Challenges in Content Placement and Delivery Strategies,” IEEE Communications Surveys and Tutorials, vol. 20, no. 3, pp. 1710-1732, March 2018.

X. Zheng, G. Wang, and Q. Zhao, “A Cache Placement Strategy with Energy Consumption Optimization in Information-Centric Networking,” Future Internet, vol. 11, no. 3, 64, March 2019.

J. Xia, F. Zhou, X. Lai, H. Zhang, H. Chen, Q. Yang, et al., “Cache Aided Decode and Forward Relaying Networks: From the Spatial View,” Wireless Communications and Mobile Computing, vol. 2018, 5963584, April 2018.

H. Shehata and T. Khattab, “Energy Detection Spectrum Sensing in Full-Duplex Cognitive Radio: The Practical Case of Rician RSI,” IEEE Transactions on Communications, vol. 67, no. 9, pp. 6544-6555, September 2019.

N. Fatima, S. A. Siddiqui, and A. Ahmad, “Comparative Performance Analysis of Digital Modulation Schemes with Digital Audio Transmission through AWGN Channel,” International Conference on Power Electronics, Control, and Automation, pp. 1-3, November 2019.