Design, Simulation & Concept Verification of 4 × 4, 8 × 8 MIMO With ZF, MMSE and BF Detection Schemes
DOI:
https://doi.org/10.1515/ecce-2017-0010Keywords:
Bit Error Rate (BER), Beamforming (BF), MIMO system, Minimum mean square error (MMSE), Signal to Noise Ratio (SNR), Zero forcing (ZF)Abstract
A conventional MIMO system is designed consisting of 4 antenna elements at both the receiver and transmitter ends. Different kinds of signal detection techniques, namely, zero forcing (ZF), minimum mean square error (MMSE) and beamforming (BF), are used at the receiver end for signal detection. The performance of the system is analyzed by calculating BER vs SNR for each of the above techniques separately. The present work has been thoroughly analyzed and implemented using MATLAB. On the basis of the results obtained, it is summarized that as the values of SNR increase, BER decreases for ZF and MMSE and it almost vanishes to zero even for low SNR values if BF is used. Although ZF and MMSE are suitable for designing a conventional MIMO system with 4 antenna elements, it becomes too difficult for a large number of antenna elements due to its complexity of calculating the inverse of a (N × N) matrix. Based on the results analyzed so far, it is concluded that beamforming (BF) is a suitable technique for designing a system that has a large number of antenna elements at the base station. A further improved system with enhanced performance regarding lower BER for even smaller values of SNR is designed in the present study, consisting of 8 antennas at the base station. The results obtained are enthusiasm-provoking and encouraging for further studies to develop a concept for next-generation wireless communication systems with an optimum design.References
W. D. Bliss, K.W. Forsythe, and M. A. Chan, “MIMO Wireless Communication,” Lincoln Laboratory Journal, vol. 15, no.1, pp. 97–126, 2005.
T. Yasodha, “Decoding for 8×8 MIMO System Using Convolution Coding Implemented in VLSI,” Int. J. Eng. Res. Appl., vol. 3, no. 1, pp. 278–282, Jul.–Aug. 2013.
J. Hoydis, C. Hoek, T. Wild, and S. ten Brink, “Channel Measurements for Large Antenna Arrays,” Proc. Int. Symp. Wireless Communication. Syst. (ISWCS), pp. 811–815, Aug. 2012. https://doi.org/10.1109/iswcs.2012.6328480
E. Bjornson, J. Hoydis, M. Kountouris, and M. Debbah, “Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits”, IEEE Transactions on Information Theory, vol. 60, no. 11, pp. 7112–7139, Nov. 2014. https://doi.org/10.1109/tit.2014.2354403
K. Sengar, N. Rani, A. Singhal, D. Sharma, S. Verma, and T. Singh, “Study and Capacity Evaluation of SISO, MISO and MIMO RF Wireless Communication Systems,” Int. J. Eng. Trends Technology (IJETT), vol. 9, no. 9, pp. 437–440, Mar. 2014. https://doi.org/10.14445/22315381/ijett-v9p283
D. Zhu, B. Li, and P. Liang, “On the Matrix Inversion Approximation Based on Neumann Series in Massive-MIMO Systems,” IEEE ICC - Wireless Communication Symposium, pp. 1763–1769, Jun. 2015. https://doi.org/10.1109/icc.2015.7248580
A. Kumar and M. Gupta, “Design of 4:8 MIMO OFDM With MSE Equalizer for Different Modulation Techniques,” Wireless personal Communication, vol. 95, no. 4, pp. 4535–4560, Mar. 2017. https://doi.org/10.1007/s11277-017-4099-1
A. Kumar and M. Gupta, “Design and Performance Evaluation of MBMIMO-UWB for Different Transmission Techniques,” Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci, 2017. https://doi.org/10.1007/s40010-017-0400-7
A. Kumar and M. Gupta, “Design, Development of MC-CDMA, and Reduction of ISI for Different Modulation Techniques,” Proc. Int. Conf. on Recent Cognizance in Wireless Communication and Image Process, pp. 81–91, 2016. https://doi.org/10.1007/978-81-322-2638-3_9
A. Kumar and M. Gupta, “Design, Comparative Study and Analysis of CDMA for Different Modulation Techniques,” Egyptian Informatics Journal, vol. 16, no. 3, pp. 351–365, 2015. https://doi.org/10.1016/j.eij.2015.07.004
X. Gao, O. Edforce, F. Rusek, and F. Tufvesson, “Massive MIMO Performance Evaluation Based on Measured Propagation Data,” IEEE Transactions on Wireless Communication, vol. 14, no. 7, pp. 3899–3911, Jun. 2015. https://doi.org/10.1109/twc.2015.2414413
T. L. Marzetta, “Noncooperative Cellular Wireless With Unlimited Numbers of Base Station Antennas,” IEEE Transaction on Wireless Communication, vol. 9, no. 11, pp. 3590–3600, Nov. 2010. https://doi.org/10.1109/twc.2010.092810.091092
D. W. Yue and G. Y. Li, “LOS-Based Conjugate Beamforming and Power-Scaling Law in Massive-MIMO Systems,” arXiv preprint, arXiv:1404.1654, Dec. 2014.
C.-S. Park, Y.-S. Byun, A. M. Bokiye, and Y.-H. Lee, “Complexity Reduced Zero-Forcing Beamforming in Massive MIMO Systems,” Information Theory and Applications Workshop (ITA), pp. 1–5, Feb. 2014.
S. Lakshminarayana, M. Assaad, and M. Debbah, “Coordinated Multicell Beamforming for Massive MIMO: A Random Matrix Approach,” IEEE Transactions on Information Theory, vol. 61, no. 6, pp. 3387–3412, Jun. 2015. https://doi.org/10.1109/tit.2015.2421446
Z. Gao, L. Dai, W. Dai, and Z. Wang, “Block Compressive Channel Estimation and Feedback for FDD Massive MIMO,” Computer Communications Workshops (INFOCOM WKSHPS), 2015 IEEE Conference, pp. 49–50, Apr. 2015. https://doi.org/10.1109/infcomw.2015.7179337
Y. Han, J. Ni, and G. Du, “The Potential Approaches to Achieve Channel Reciprocity in FDD System With Frequency Correction Algorithms,” Proc. Int. ICST Conf. Commun. Netw., pp. 143–149, 2010. https://doi.org/10.4108/chinacom.2010.154
J. Hoydis, S. ten Brink, and M. Debbah, “Massive MIMO: How Many Antennas Do We Need?,” IEEE 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp. 545–550, Sep. 2011. https://doi.org/10.1109/allerton.2011.6120214
Downloads
Published
Issue
Section
License
Copyright (c) 2017 Arun Kumar, Piyush Vardhan (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 Unported License.
How to Cite
