A Review on Compressed Sensing Space-Time Frequency Index Modulation in OFDM System

Sarita Yadav; Ashish Nema; Jitendra Kumar Mishra

doi:10.21276/ijircst.2019.7.2.2

Abstract

In wireless communication, orthogonal frequency division multiplexing (OFDM) plays a major role because of its high transmission rate. In space-time shift keying (STSK), the information is conveyed by both the spatial and time dimensions, which can be used to strike a trade-off between the diversity and multiplexing gains. On the other hand, orthogonal frequency division multiplexing (OFDM) relying on index modulation (IM) conveys information not only by the conventional signal constellations as in classical OFDM, but also by the indices of the subcarriers. In this review compressed sensing (CS) is studied in order to increase throughput and bit-error performance by transmitting extra information bits in each subcarrier block as well as to decrease the complexity of the detector.

Keywords

OFDM, MIMO, Space-Time Shift Keying (STSK), Frequency Index Modulation, Compressed Sensing (CS).

References

[1] BrankaVucetic and Jinhong Yuan, “Space-Time Coding”, John Wiley & Sons, British Library Cataloguing in Publication Data,(2003).

[2] Dipl.-Ing. BiljanaBadic, “Space-Time Block Coding for Multiple Antenna Systems”, Dr. Thesis, 2005.

[3] k. Kumar and A. Mitra, “Estimation of MIMO Channels Using Complex Time Delay Fully Recurrent Neural Network”, IEEE, 2nd National Conference Emerging Trends and Application in Computer Science (NCETACS), pp. 1-5, 2011.

[4] Kaleeswaran RAJESWARI, S. Jayaraman THIRUVENGADAM, “Optimal Power Allocation for Channel Estimation in MIMO-OFDMSystem with Per-Subcarrier Transmit Antenna Selection”,RADIOENGINEERING, VOL. 24, NO. 1, 2015.

[5] Sven Jacobsson_y, , “One-Bit Massive MIMO: Channel Estimation andHigh-Order Modulations”, Chalmers University of Technology, 2015.

[6] Z. Ling and Z. Xianda, “MIMO Channel Estimation and Equalizationusing Three-Layer Neural Networks with Feedback”, IEEE, Vol. 12,No.6, pp. 658- 662, 2007.

[7] C. Çiflikli, A. TuncayÖzsahin and A. Çagri, “Artificial Neural NetworkChannel Estimation Based on Levenberg-Marquardt for OFDMSystems”, Springer, Science+Business Media, Vol. 51, pp. 221- 229,2008.

[8] K. CharlyJomonand S. Prasanth, “Artificial Neural NetworkbChannel Estimation Based on LevenbergMarquardt for OFDMSystems”, ISSN 0735-2727, Radioelectronics and CommunicationsSystems, , Vol. 60, No. 2, pp. 80–87. © Allerton Press, Inc., 2017.

[9] Nanda, Y., & Singh, S. (2016). Comparison of bit error rate of OFDM-system with BPSK modulation and Co-OFDM. International journal online of science, 2(4). Retrieved from http://ijoscience.com/ojsscience/index.php/ojsscience /article/view/85.

[10]Cho YS, Kim J, Yang WY, Kang CG, “MIMOOFDM wireless communications with MATLAB”, Wiley, New York, 2010.

[11]Y. Chau and S.-H. Yu, “Space modulation on wireless fading channels,” Proc. IEEE VTC’2001, vol. 3, pp. 1668-1671, October 2001.

[12]M. I. Kadir, S. Sugiura, S. Chen, and L. Hanzo, “Unified MIMOmulticarrier designs: a space-time shift keying approach,” IEEE Communications Surveys Tutorials, vol. 17, no. 2, pp. 550–579, November 2015.

[13]R. Y. Mesleh, H. Haas, S. Sinanovic, C. W. Ahn, and S. Yun, “Spatial modulation,” IEEE Transactions on Vehicular Technology, vol. 57, no. 4, pp. 2228–2241, July 2008.

[14]J. Jeganathan, A. Ghrayeb, L. Szczecinski, and A. Ceron, “Space shift keying modulation for MIMO channels,” IEEE Transactions on Wireless Communications, vol. 8, no. 7, pp. 3692–3703, July 2009.

[15]M. I. Kadir, S. Chen, K. Hari, K. Giridhar, and L. Hanzo, “OFDMaided differential space-time shift keying using iterative soft multiplesymbol differential sphere decoding,” IEEE Transactions on Vehicular Technology, vol. 63, no. 8, pp. 4102–4108, Oct 2014.

[16]I. A. Hemadeh, M. El-Hajjar, S. Won, and L. Hanzo, “Layered multigroup steered space-time shift-keying for millimeter-wave communications,” IEEE Access, vol. 4, pp. 3708–3718, April 2016.

[17]Ibrahim A. Hemadeh, Mohammed El-Hajjar, SeungHwan Won, Lajos Hanzo, “Multi-set spacetime shift keying and space- frequency spacetime shift keying for millimeter-wave communications,” IEEE Access, vol. 5, pp. 8324–8342, December 2016.

[18]Ibrahim A. Hemadeh, Mohammed El-Hajjar, SeungHwan Won, Lajos Hanzo, “Multiuser steered multiset space-time shift keying for millimeterwave communications,” IEEE Transactions on Vehicular Technology, vol. 66, no. 6, pp. 5491–5495, June 2017.

[19]E. Basar, “Index modulation techniques for 5G wireless networks,” IEEE Communications Magazine, vol. 54, no. 7, pp. 168–175, July 2016.

[20]J. Jeganathan, A. Ghrayeb, L. Szczecinski, and A. Ceron, “Space shift keying modulation for MIMO channels,” IEEE Trans. Wireless Commun., vol. 8, no. 7, pp. 3692–3703, Jul. 2009.

[21]E. Basar, U. Aygolu, E. Panayirci, and H. V. Poor, “Orthogonal frequency division multiplexing with index modulation,” IEEE Trans. Signal Process., vol. 61, no. 22, pp. 5536–5549, Nov. 2013.

[22]M. Di Renzo, H. Haas, A. Ghrayeb, S. Sugiura, and L. Hanzo, “Spatial modulation for generalized MIMO: Challenges, opportunities, and implementation,” Proc. of the IEEE, vol. 102, no. 1, pp. 56–103, Jan. 2014.

[23]D. L. Donoho, “Compressed sensing,” IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289–1306, April 2006.

[24]Z. Han, H. Li, and W. Yin, Compressive sensing for wireless networks. Cambridge University Press,2013. [Online]. Available: https://books.google.co.uk/books?id=h7g29nWN8z8 C

[25]Y. Eldar and G. Kutyniok, Compressed sensing: theory and applications, ser. Compressed Sensing: Theory and Applications. Cambridge University Press, 2012. [Online]. Available: https://books.google.co.uk/books?id=Gm3ihcJwN0Y C

[26]Cimini LJ, “Analysis and simulation of digital mobile channel using orthogonal frequency multiplex”, IEEE Trans Commun, vol 33, pp. 665–675, 1985.

[27]H. Zhang, L. L. Yang, and L. Hanzo, “Compressed sensing improves the performance of subcarrier index-modulation-assisted OFDM,” IEEE Access, vol. 4, pp. 7859–7873, October 2016.

[28]J. W. Choi, B. Shim, Y. Ding, B. Rao, and D. I. Kim, “Compressed sensing for wireless communications : useful tips and tricks,” IEEE Communications Surveys Tutorials, vol. PP, no. 99, pp. 1–1, February, 2017.

[29]Z. Gao, L. Dai, C. Qi, C. Yuen, and Z. Wang, “Nearoptimal signal detector based on structured compressive sensing for massive SMMIMO,” IEEE Transactions on Vehicular Technology, vol. 66, no. 2, pp. 1860–1865, Feb 2017.

Cites this article as

S. Yadav, A. Nema, J. K. Mishra, "A Review on Compressed Sensing Space-Time Frequency Index Modulation in OFDM System", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-7, no.2, pp.12-17, 2019. Available from: https://doi.org/10.21276/ijircst.22019.7.2.2

Corresponding Author

Sarita Yadav

BE in EC, Patel College of Science and Technology RGPV Bhopal, MTECH in Digital Communications, Patel Collage of Science and Technology RGPV Bhopal

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