FPGA Implementation of ML, ZF and MMSE Equalizers for MIMO Systems
This paper presents an FPGA implementation of Maximum likelihood (ML), zero forcing (ZF) and minimum mean squared error (MMSE) equalizers applied to wireless multi-input multi-output (MIMO) systems with no fewer receive than transmit antennas. In spite of much prior work on this subject, we reveal s...
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| Published in | Procedia computer science Vol. 73; pp. 226 - 233 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1877-0509 1877-0509 |
| DOI | 10.1016/j.procs.2015.12.022 |
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| Abstract | This paper presents an FPGA implementation of Maximum likelihood (ML), zero forcing (ZF) and minimum mean squared error (MMSE) equalizers applied to wireless multi-input multi-output (MIMO) systems with no fewer receive than transmit antennas. In spite of much prior work on this subject, we reveal several new and surprising analytical results in terms of output signal-to-noise ratio (SNR), by comparing the Bit Error Rate (BER) and the average detection time consuming. Results based on the platform of Xilinx Virtex 6. We discuss the case where there a multiple transmit antennas and multiple receive antennas resulting in the formation of a Multiple Input Multiple Output (MIMO) channel with Zero Forcing equalizer, MIMO with MMSE equalizer, MIMO with ZF Successive Interference Cancellation equalizer, MIMO with ML equalization, MIMO with MMSE SIC and optimal ordering. |
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| AbstractList | This paper presents an FPGA implementation of Maximum likelihood (ML), zero forcing (ZF) and minimum mean squared error (MMSE) equalizers applied to wireless multi-input multi-output (MIMO) systems with no fewer receive than transmit antennas. In spite of much prior work on this subject, we reveal several new and surprising analytical results in terms of output signal-to-noise ratio (SNR), by comparing the Bit Error Rate (BER) and the average detection time consuming. Results based on the platform of Xilinx Virtex 6. We discuss the case where there a multiple transmit antennas and multiple receive antennas resulting in the formation of a Multiple Input Multiple Output (MIMO) channel with Zero Forcing equalizer, MIMO with MMSE equalizer, MIMO with ZF Successive Interference Cancellation equalizer, MIMO with ML equalization, MIMO with MMSE SIC and optimal ordering. |
| Author | Trimeche, Abdessalem Sakly, Anis Mtibaa, Abdellatif |
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| Cites_doi | 10.1049/el:19990058 10.1109/DTIS.2012.6232979 10.1109/ReConFig.2013.6732293 10.1109/18.825818 10.3844/ajeassp.2011.425.428 10.1109/TIT.2003.809594 10.1109/18.978730 |
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| Keywords | FPGA,QAM MMSE SNR MIMO ZF BER ML |
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| References | Dirk Wubben, Ronald Bohnke, Near-Maximum-Likelihood Detection of MIMO Systems using MMSE-Based Lattice-Reduction, 7th International Symposium on Turbo Codes and Iterative Information Processing (ISTC), 2012. Michael Rueckauer, Daniel M. Munoz, Timo Stripf, A Flexible Implementation of the PSO Algorithm for Fine- and Coarse- Grained Reconfigurable Embedded Systems, International Conference on Reconfigurable Computing and FPGAs (ReConFig), 2013. Michael Palangpour (bib0065) 2010; 4 B. M. Hochwald and T. L. Marzetta, “Unitary space-time modulation for multiple-antenna communication in Rayleigh flat fading,” IEEE Trans. Inform. Theory, vol. 46, pp 543-564, Mar. 2000. Raghunandan Swain, Ajit Kumar Panda, Design of 16-QAM Transmitter and Receiver: Review of Methods of Implementation in FPGA, RESEARCH INVENTY: International Journal of Engineering and Science ISSN: 2278-4721, Vol. 1, Issue 9 (November 2012), PP 23-27. Bara’u Gafai Najashi and Tan Xiaoheng, A Comparative Performance Analysis of Multiple-Input Multiple-Output using MATLAB with Zero Forcing and Minimum Mean Square Error Equalizers, American J. of Engineering and Applied Sciences 4 (3): 425-428, 2011 ISSN 1941-7020. A.TRIMECHE, N. Boukid, A.SAKLY, A.MTIBAA, Performance Analysis of ZF and MMSE Equalizers for MIMO Systems, 7th International conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS), 2012. M. Taherzadeh, A . M obas h er, and A. K. Khandani, “L L L reduction achieves the r eceive diver s ity in MIMO. decoding,” IEEE Trans. Infor m . T heor y, vol. 53, no. 12, pp. 4801-4805, 2007. Golden GD, Foschini GJ, Valenzuelara. et al. “Detection algorithm and initiallaboratory resultsusingV-BLAST space-time communication architecture”, Electronics Letters,pp.14-16, 1999. B. Hassibi and B. M. Hochwald, “How much training is needed in multiple- antenna wireless links?,” IEEE. Trans. Inform. Theory, vol. 49, pp. 951-963, Apr. 2003. L. Zheng and D. Tse, “Communicating on the Grassmann Manifold: A Geometric Approach to the Non-coherent Multiple Antenna Channel”, IEEE Transactions on Information Theory, vol. 48(2), pp. 359-383, February 2002. T. L. Marzetta, “BLAST training: Estimating channel characteristics for high-capacity space-time wireless,” i n Proc. 37th Annu. Allerton Conf. Communications, Control, and Computing, Sept. 22-24, 1999. P. H. Tan and L. K. Rasmussen, Tabu search multiuser detection in CDMA, Radio Sci. and Comm. Conf., Stockholm, Sweden, pp. 744-748, Jun 2002. 10.1016/j.procs.2015.12.022_bib0060 10.1016/j.procs.2015.12.022_bib0050 10.1016/j.procs.2015.12.022_bib0040 10.1016/j.procs.2015.12.022_bib0030 10.1016/j.procs.2015.12.022_bib0020 10.1016/j.procs.2015.12.022_bib0010 10.1016/j.procs.2015.12.022_bib0055 10.1016/j.procs.2015.12.022_bib0045 10.1016/j.procs.2015.12.022_bib0035 10.1016/j.procs.2015.12.022_bib0025 Michael Palangpour (10.1016/j.procs.2015.12.022_bib0065) 2010; 4 10.1016/j.procs.2015.12.022_bib0015 10.1016/j.procs.2015.12.022_bib0005 |
| References_xml | – reference: Golden GD, Foschini GJ, Valenzuelara. et al. “Detection algorithm and initiallaboratory resultsusingV-BLAST space-time communication architecture”, Electronics Letters,pp.14-16, 1999. – reference: A.TRIMECHE, N. Boukid, A.SAKLY, A.MTIBAA, Performance Analysis of ZF and MMSE Equalizers for MIMO Systems, 7th International conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS), 2012. – reference: Raghunandan Swain, Ajit Kumar Panda, Design of 16-QAM Transmitter and Receiver: Review of Methods of Implementation in FPGA, RESEARCH INVENTY: International Journal of Engineering and Science ISSN: 2278-4721, Vol. 1, Issue 9 (November 2012), PP 23-27. – volume: 4 year: 2010 ident: bib0065 publication-title: “FPGA Implementation of PSO Algorithm and Neural Networks” page – reference: Bara’u Gafai Najashi and Tan Xiaoheng, A Comparative Performance Analysis of Multiple-Input Multiple-Output using MATLAB with Zero Forcing and Minimum Mean Square Error Equalizers, American J. of Engineering and Applied Sciences 4 (3): 425-428, 2011 ISSN 1941-7020. – reference: T. L. Marzetta, “BLAST training: Estimating channel characteristics for high-capacity space-time wireless,” i n Proc. 37th Annu. Allerton Conf. Communications, Control, and Computing, Sept. 22-24, 1999. – reference: B. Hassibi and B. M. Hochwald, “How much training is needed in multiple- antenna wireless links?,” IEEE. Trans. Inform. Theory, vol. 49, pp. 951-963, Apr. 2003. – reference: L. Zheng and D. Tse, “Communicating on the Grassmann Manifold: A Geometric Approach to the Non-coherent Multiple Antenna Channel”, IEEE Transactions on Information Theory, vol. 48(2), pp. 359-383, February 2002. – reference: B. M. Hochwald and T. L. Marzetta, “Unitary space-time modulation for multiple-antenna communication in Rayleigh flat fading,” IEEE Trans. Inform. Theory, vol. 46, pp 543-564, Mar. 2000. – reference: Michael Rueckauer, Daniel M. Munoz, Timo Stripf, A Flexible Implementation of the PSO Algorithm for Fine- and Coarse- Grained Reconfigurable Embedded Systems, International Conference on Reconfigurable Computing and FPGAs (ReConFig), 2013. – reference: P. H. Tan and L. K. Rasmussen, Tabu search multiuser detection in CDMA, Radio Sci. and Comm. Conf., Stockholm, Sweden, pp. 744-748, Jun 2002. – reference: M. Taherzadeh, A . M obas h er, and A. K. Khandani, “L L L reduction achieves the r eceive diver s ity in MIMO. decoding,” IEEE Trans. Infor m . T heor y, vol. 53, no. 12, pp. 4801-4805, 2007. – reference: Dirk Wubben, Ronald Bohnke, Near-Maximum-Likelihood Detection of MIMO Systems using MMSE-Based Lattice-Reduction, 7th International Symposium on Turbo Codes and Iterative Information Processing (ISTC), 2012. – ident: 10.1016/j.procs.2015.12.022_bib0050 doi: 10.1049/el:19990058 – ident: 10.1016/j.procs.2015.12.022_bib0045 doi: 10.1109/DTIS.2012.6232979 – ident: 10.1016/j.procs.2015.12.022_bib0005 doi: 10.1109/ReConFig.2013.6732293 – ident: 10.1016/j.procs.2015.12.022_bib0040 – volume: 4 year: 2010 ident: 10.1016/j.procs.2015.12.022_bib0065 publication-title: “FPGA Implementation of PSO Algorithm and Neural Networks” page – ident: 10.1016/j.procs.2015.12.022_bib0010 doi: 10.1109/18.825818 – ident: 10.1016/j.procs.2015.12.022_bib0060 doi: 10.3844/ajeassp.2011.425.428 – ident: 10.1016/j.procs.2015.12.022_bib0035 – ident: 10.1016/j.procs.2015.12.022_bib0030 – ident: 10.1016/j.procs.2015.12.022_bib0015 – ident: 10.1016/j.procs.2015.12.022_bib0020 doi: 10.1109/TIT.2003.809594 – ident: 10.1016/j.procs.2015.12.022_bib0025 doi: 10.1109/18.978730 – ident: 10.1016/j.procs.2015.12.022_bib0055 |
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| Title | FPGA Implementation of ML, ZF and MMSE Equalizers for MIMO Systems |
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