Comparative Analysis of Channel Estimation Techniques in SISO, MISO and MIMO Systems

• Autorzy: Obinna O. , Kennedy O. , Osemwegie O. , Nsikan N.

Identyfikatory

DOI

10.1515/eletel-2017-0040

• Języki publikacji: EN

Abstrakty

EN

The ever-growing need for high data rate, bandwidth efficiency, reliability, less complexity and less power consumption in our communication systems is on the increase. Modern techniques have to be developed and put in place to meet these requirements. Research has shown, that compared to conventional Single Input Single Output (SISO) systems, Multiple-Input Single Output (MISO), and Multiple-Input Multiple-Output (MIMO) can actually increase the data rate of a communication system, without actually requiring more transmit power or bandwidth. This paper aims at the investigation of the existing channel estimation techniques. Based on the pilot arrangement, the block type and comb type are compared, employing the Least Square estimation (L.S) and Minimum Mean Squared Error (MMSE) estimators. Pilots occupy bandwidth, minimizing the number of pilots used to estimate the channel, in order to allow for more bandwidth utilization for data transmission, without compromising the accuracy of the estimates is taken into consideration. Various channel interpolation techniques and pilot-data insertion ratio are investigated, simulated and compared, to determine the best performance technique with less complexity and minimum power consumption. As performance measures, the Mean Squared Error (MSE) and Bit Error Rate (BER) as a function of Signal to Noise power Ratio (SNR) of the different channel estimation techniques are plotted, in order to identify the technique with the most optimal performance. The complexity and energy efficiency of the techniques are also investigated. The system modelling and simulations are carried out using Matlab simulation package. The MIMO gives the optimum performance, followed by the MISO and SISO. This is as a result of the diversity and multiplexing gain experienced in the multiple antenna techniques using the STBC.

Słowa kluczowe

EN

multiple-input multiple-output; MIMO; multiple-input single output; MISO; single input single output; SISO; least square estimation; minimum mean squared error estimators; MMSE; mean squared error; MSE; bit error rate; BER

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2017
• Tom: Vol. 63, No. 3
• Strony: 299--304
• Opis fizyczny: Bibliogr. 13 poz., tab., wykr.

Twórcy

autor

Obinna O.

• Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria

autor

Kennedy O.

• Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria

autor

Osemwegie O.

• Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria

autor

Nsikan N.

• Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria

Bibliografia

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• [3] S. Coleri, M. Ergen, A. Puri, and A. Bahai, Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems IEEE Trans. Broadcasting, vol. 48, no. 3, Sept. 2002, pp 223-229.
• [4] M. H. Hsieh and C. H. Wei, Channel Estimation for OFDM Systems Based on Comb-Type Pilot Arrangement in Frequency Selective Fading Channels IEEE Trans. Consumer Electronics, vol. 44, no. 1, Feb. 1998, pp. 217-225.
• [5] K. Kwak et al, New OFDM Channel Estimation with Dual-ICI Cancellation in Highly Mobile Channel, IEEE Trans. Wireless Communications, vol. 9, no. 10, Oct. 2010, p. 3156.
• [6] H. Yang, A road to future broadband wireless access: MIMO-OFDM based air interface, IEEE Commun. Mag., vol. 43, no. 1, Jan. 2005, pp. 53-60.
• [7] H. Sampath, et al, A fourth-generation MIMO-OFDM broadband wireless system: design, performance and Field trial results, IEEE Communications Magazine, No. 9, Sep. 2002, pp. 143-149.
• [8] A. Sibille, C. Oestges, and A. Zanella, MIMO from Theory to Implementation, Academy Press, Burlington, USA, 2011.
• [9] G. J. Foschini and M. J. Gans, On Limits Of Wireless Communicationsin A Fading Environment When Using Multiple Antennas,Wireless Pers.Commun.,vol. 6, no. 3, Mar. 1998, pp. 311-335.
• [10] Y. S. Cho et al, MIMO-OFDM Wireless Communications with MATLAB, IEEE Press, John Wiley and Sons (Asia) Pte Ltd. 2010.
• [11] T. S. Rappaport, Wireless Communications: Principles and Practice, Second Edition, Prentice Hall, 2002.
• [12] J. P. Javaudin, et al,An OFDM Evolution for the UMTS High Speed Downlink Packet Access, France Telecom R and D, DMR/DDH Laboratory, Wireless Technology Labs, Nortel Networks, Station C, Ottawa, Canada.
• [13] S. Yatawatta, A. P. Petropulu, and C. J. Graff, Energy-Efficient Channel Estimation in MIMO Systems, EURASIP Journal on Wireless Communications and Networking, vol. 2006, Article ID 27694, pp 111.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).