Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33117
An Intelligent Scheme Switching for MIMO Systems Using Fuzzy Logic Technique
Authors: Robert O. Abolade, Olumide O. Ajayi, Zacheaus K. Adeyemo, Solomon A. Adeniran
Abstract:
Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.Keywords: Channel quality indicator, fuzzy logic, link adaptation, MIMO, spatial multiplexing, transmit diversity.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.2363330
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 736References:
[1] R. O. Abolade and O. O. Ajayi, “Reduction of outage probability in fast rayleigh fading MIMO channels using OFDM,” International Journal of Engineering Research and Applications, vol. 4, Issue 9, pp. 06-10, 2014.
[2] C. Kim and J. Lee, “Dynamic rate-adaptive MIMO mode switching between spatial multiplexing and diversity,” EURASIP Journal on Wireless Communications and Networking, 2012:238., August 2012.
[3] H. Touheed, A. U. Quddus, R. Tafazolli, “An Improved Link Adaptation Scheme for High Speed Downlink Packet Access”, IEEE 68th Vehicular Technology Conference (VTC), Spring, pp. 2051 – 2055, September 2008.
[4] R. W. Heath Jr., A. J. Paulraj, “Switching between diversity and multiplexing in MIMO systems”. IEEE Trans. Commun., vol. 53, no. 6, pp. 962–968, June 2005.
[5] J. H. Winters, “The diversity gain of transmit diversity in wireless systems with Rayleigh fading,” IEEE Trans. Veh. Technol., vol. 47, no. 1, pp. 119–123, Feb. 1998
[6] G. Ganesan and P. Stoica, “Space-time block codes: A maximum SNR approach,” IEEE Trans. Inf. Theory, vol. 47, no. 4, pp. 1650–1656, May 2001.
[7] A. Forenza, A. Pandharipande, H. Kim and R.W. Heath Jr, “Adaptive MIMO Transmission Scheme: Exploiting the Spatial Selectivity of Wireless Channels”, IEEE 2005.
[8] L. C. Png, L. Xiaoy, K. S. Yeoz, T. S. W. and Y. L. Guan, “MIMO-diversity switching techniques for digital transmission in visible light communication,” 18th IEEE Symposium on Computers and Communications (ISCC’13) (Split, Croatia, 2013), pp. 576–582. Jul. 2013.
[9] S. Catreux, V. Erceg, D. Gesbert, R.W. Heath Jr., “Adaptive modulation and MIMO coding for broadband wireless data networks,” IEEE Commun. Mag., vol. 40, no. 6, pp. 108–115, June 2002.
[10] J. Huang and S. Signell, “Discrete rate spectral efficiency improvement by scheme switching for MIMO systems.” in Proc. IEEE Int. Conf. Commun. (ICC’08), (Beijing, China, 2008), pp. 3998–4002, 2008.
[11] C. G. Patil and M. T. Kolte, "An approach for optimization of handoff algorithm using fuzzy logic system", International Journal of Computer Science and Communication, vol. 2, no. 1, pp. 113-118. 2011.
[12] A. M. Orimogunje, O. O. Ajayi, O. A. Fakolujo and J. O. Abolade (2017), “Adaptive Network Based Fuzzy Inference System Model for Minimizing Handover Failure in Mobile Networks,” International Journal of Innovative Science and Research Technology, Vol. 2, Issue 9, pp. 332-342.
[13] Oka, A. and Lampe, L. (2010), “Distributed Target Tracking Using Signal Strength Measurements by a Wireless Sensor Network,” International Journal of Computer Science and Communication, vol. 28, no. 7, pp. 1006-1015. 2010.
[14] Y. Chapre, P. Mohapatra, S. Jha and A. Seneviratne (2013), “Received Signal Strength Indicator and Its Analysis in a Typical WLAN System,” 38th Annual IEEE Conference on Local Computer Networks.
[15] A. Fourie, (2015), “Received signal strength indicator,” Poynting Group. Retrieved from http://LinkedIn/ on 31/05/18.