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Amaefule, Ikechukwu A.
- Analyzing the Performance of Multiuser MIMO Uplink System with Detection Techniques
Abstract Views :92 |
PDF Views:0
Authors
Temple C. Okeahialam
1,
Donatus O. Njoku
2,
Gilean C. Onukwugha
2,
Ikechukwu A. Amaefule
3,
Janefrances E. Jibi
4
Affiliations
1 Department of Information Technology, Federal University of Technology, Minna-Niger State, NG
2 Department of Computer Science, Federal University of Technology, Owerri-Imo State, NG
3 Imo State University, Owerri, Imo State, NG
4 Department of Information Technology, Federal University of Technology, Owerri-Imo State, NG
1 Department of Information Technology, Federal University of Technology, Minna-Niger State, NG
2 Department of Computer Science, Federal University of Technology, Owerri-Imo State, NG
3 Imo State University, Owerri, Imo State, NG
4 Department of Information Technology, Federal University of Technology, Owerri-Imo State, NG
Source
International Journal of Advanced Networking and Applications, Vol 15, No 1 (2023), Pagination: 5796-5800Abstract
This In this paper, performance analysis of multiuser multiple-input multiple-output (MU-MIMO) in terms of bit error rate (BER) against with detection techniques has been presented. With the increasing demand for wireless communication system that offers users better satisfaction, different detection schemes have been developed and implemented for uplink system. Hence, this paper was basically designed to study the effect of linear minimum mean square error (MMSE-Linear) and MMSE with signal interference cancellation (MMSE-SIC) detectors on BER performance of MU-MIMO system with based station antennas taken as 4 or 8 while the number of user equipment(UE) taken as 2, 4, or 8. Each UE is considered to be equipped with one antenna at time. A model representing the wireless communication of a MU-MIMO system in uplink scenario was developed as MATLAB program. Computer simulation was conducted using the developed model and the analysis of revealed that MMSE-SIC outperformed MMSE-linear. Nevertheless, an obvious observation was the fact with lower number of antenna at BS together with number of receive antenna of UE, the BER performance of both techniques were almost the same.Keywords
BER, Detection Techniques, MMSE-Linear, MMSE-SIC, MU-MIMO.References
- . A. Alshammari, Optimal capacity and energy efficiency of massive MIMO systems [Doctoral dissertation, University of Denver]. Electronic Thesis and Dissertation. 2017, https://digitalcommons.du.edu/etd/1377
- . J. Andrews,G. W. Choi, & R.W. Health, Overcoming interference in spatial multiplexing mimo cellular networks. IEEE Wireless Communications, 2006, 1-24.
- . D. Borges, P. Montezuma, R. Dinis, & M. Beko. Massive MIMO techniques for 5G and beyond – opportunities and challenges. Electronics, 10(1667), 2021, 1 – 29. https://doi.org/10.3390/electronics10141667
- . S.Y. Cho, J. Kim, W.Y. Yang & G.C. Kang, MIMO-OFDM Wireless Communications with MATLAB, John Wiley & Sons (Asia) Pte Ltd., 2010.
- . B. Clerckx, & C. Oestges MIMO Wireless Networks: Channels Techniques and Standards for Multi-Antenna, Multi-User and Multi-Cell Systems. (Cambridge: Academic Press, 2013) 225-237
- . D. Gesbert, M. Shafi, D. Shiu, D.,P.J. & Smith. Theory to Practice: an Overview of Mimo Space-time Coded wireless system. IEEE Journal on Selected Areas in communications, 21(3), 2003, 281-302.
- . C-C Hu, & C-L. Yang, Combined transceiver optimization for uplink multiuser MIMO with limited CSI. International Scholarly Research Network, (20) 11, 2011 doi:10.5402/2011/735695
- . S. A. Khwandah, J.P. Cosmas, P.I. Lazaridis, Z. Zaharis, & I. P. Chochilouros. Massive MIMO systems for 5G communications. Wireless Personal Communications, 12(10), 2021, 2101 – 2115. https://doi.org/10.1007/s11277-021-08550-9
- . C. S. Shreelakshmi, N. S., Shettar, & A. V. Srikantan, Adaptive monitoring technique for MIMO-OFDM systems. GSSS Institute Of Engineering And Technology For Women, Mysuru, (National Level PG Project Symposium On Electronics & Communication, Computer Science, 2016), 1-4.
- .B. C. Agwah, M. I. Aririguzo (2020), MIMO-OFDM system in wireless communication: a survey of peak to average power ratio minimization and research direction, International Journal of Computer Science Engineering, 9 (4) , 2020, 219-234
- . C. G. Onukwugha, D.O. Njoku, J.E. Jibiri, & Chigozie D (2023), Bit Error Rate Analysis of Multiuser Massive MIMO Wireless System Using Linear Precoding Techniques, Int. J. Advanced Networking and Applications, 14(4), 20223, 5517-5522
- Effect of Increasing Node Population on the Performance of Cluster Based Energy-Efficient Routing Protocols in Wireless Sensor Network
Abstract Views :55 |
PDF Views:2
Authors
Innocent Chika
1,
Ikechukwu A. Amaefule
2,
Christopher I. Ofoegbu
3,
Chigozie Dimoji
3,
Amadi Christian Onyekachi
3,
Agbakwuru A. O.
4
Affiliations
1 Department of Telecommunication Engineering, Federal University of Technology Minna, Minna, NG
2 Department of Computer Science, Imo State University , Owerri, NG
3 Department of Computer Science, Federal University of Technology Owerri, Owerri, NG
4 Department of Computer Science, Imo State University, Owerri, NG
1 Department of Telecommunication Engineering, Federal University of Technology Minna, Minna, NG
2 Department of Computer Science, Imo State University , Owerri, NG
3 Department of Computer Science, Federal University of Technology Owerri, Owerri, NG
4 Department of Computer Science, Imo State University, Owerri, NG
Source
International Journal of Advanced Networking and Applications, Vol 15, No 4 (2023), Pagination: 6069 - 6075Abstract
A wireless sensor network (WSN) is a network consisting of miniaturized smart sensors communicating the information gathered or collected from a monitored environment via a wireless link. The sensors are capable of sensing the events within their environment, process the data, and transmit the data to the base station (BS). The entire processing of data and subsequent transmission to BS requires high energy consumption. The operation of WSN is limited by repeated dead nodes, which results in energy depletion. Hence, to prolong the life-span of the network, several routing protocols have been developed. However, the effectiveness of these protocols has not been well examined in terms of increasing node population for a given WSN field or area. Therefore, in this work the effect of increasing node density on cluster based energy-efficient routing protocols in wireless sensor network was analysed. The implemented routing protocols were Low Energy Adaptive Clustering Hierarchy LEACH, stable election protocol (SEP), and zone-SEP (Z-SEP). The dimension of the WSN was 100 × 100 square metre area with varying number of sensor nodes: 50, 60, 70, 80, 90, and 100. The results of the simulation conducted in MATLAB revealed that increasing node density resulted in increased alive node and throughput (measures in terms of transmitted number of packets). On the contrary, the protocol with the best performance was ZSEP.Keywords
LEACH, Node population, SEP, ZSEP, WSN.References
- Rahman, Md. A., Anwar, S., Pramanik, Md. I., & Rahman, Md. F. (2013). A survey on energy efficient routing techniques in wireless sensor network. Proceedings of 15th International Conference on Advanced Communications Technology, 200-205.
- Bazzi, H. S., Haidar, A. M., & Bilal, A. (2015). Classification of routing protocols in wireless sensor network. Conference Paper, ICCAAD, IEEE, 2015.
- Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. In Proceeding of the International Workshop on SANPA, August 2004.
- Chandanse, A., Bharane, P., Anchan, S., & Patil, H. (2019). Performance analysis of LEACH protocol in sensor network. 2nd International Conference on Advances in Science & Technology (ICAST-2019), 1-5.
- Akuildiz, I. F., & Vuran, M. C. (2010). Wireless sensor networks. John Wiley and Sons Ltd.
- Faisal, S., Javaid, N., Javaid, A., Khan, M. A., Bouk, S. H., & Khan, Z. A. (2013). Z-SEP: zonal-stable election protocol for wireless sensor networks. Journal of Basic and Applied Scientific Research, 3(5), 132-139.