Security Improvement in Next Generation Wireless System by Interleaver in Transceiver Structures
DOI:
https://doi.org/10.13052/2245-1439.641Keywords:
Interleave Division Multiple Access (IDMA), Multiple Input Multiple Output (MIMO), Multi-User Detection (MUD), Multi-User Interference (MUI), Multi-Stream Interference (MSI), Polarization diversity, Stanford University Interim (SUI) channel model, Long Term Evolution (LTE) channel modelAbstract
This paper presents the multiple-input multiple-output Interleave division multiple access (MIMO-IDMA) system with dual polarized division multiplexing (DPDM). Dual polarized antenna system replaces the uni-polarized antenna system availing cost and space features. We have considered dual- Polarized antennas at both the transmitter and the receiver ends to establish DPDM. For the purpose of accommodation, the users are separated with userspecific interleaver in combination with a low rate spreading sequence. In the receiver, we consider the minimum mean square error (MMSE) algorithm based successive interference cancellation (SIC) Multi-user detection (MUD) technique to diminish the effects of multi-stream interference (MSI). Furthermore, we implement Log-maximum a posteriori probability (MAPP) decoding algorithm at the mobile stations (MSs) to alleviate the effects of multi-user interference (MUI).We evaluate the effects of codedMIMO-IDMA system in the context of downlink (DL) communication pertaining to the Stanford University Interim (SUI) and Long-term Evolution (LTE) channel model specifications.We observe that our simulation results considered turbo coded Dual-PolarizedMIMO-IDMAsystem with iterative decoding algorithm provides a better bit error rate (BER) performance with less signal to noise ratio (SNR) when compared to uncoded system. Furthermore our simulation results show that MIMO-IDMA system with Dual-Polarized antenna requires higher SNR than uni-polarized antennas in order to achieve same BER. However, it provides the advantage of replacing two uni-polarized antennas by a single Dual-Polarized antenna which can therefore help achievement of a higher data rate with a reduced size of MS in the context of DL transmission.
Downloads
References
Oestges, C., Erceg, V., and Paulraj, A. J. (2004). Propagation modeling of MIMO multipolarized fixed wireless channels. IEEE Transaction on Vehicular Technology (53), 644–654.
Foschini, G., and Gans, M. (1998). On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Communication (6), 311–335.
Ping, L., Liu, L., Wu, K., et al. (2006). Interleave-division multiple access. IEEE Transaction on Wireless Communication (5), 938–947.
Ping, L. (2005). Interleave-division multiple access and chip-by-chip iterative multi-user detection. IEEE Communication Magazine(43), 19–23.
Kusume, K., and Bauch, G. (2005). CDMA and IDMA: Iterative multiuser detections for near-far asynchronous communications, in Proceedings of IEEE PIMRC, Berlin, Germany, 426–431.
Partibane, B., Nagarajan, V., Vishvaksenan, K. S., et al. (2015). Performance of Multi-User Transmitter Pre-Processing Assisted Multi-Cell IDMA System for Downlink Transmission. Fluctuation and Noise Letters (14), 1550030-16, doi: 10.1142/S0219477515500303
Kusume, K., Dietl, G., Utschick, W., et al. (2007). Performance of interleave division multiple access based on minimum mean square error detection, in Proceeding of IEEE International Conference on Communication, Glasgow, UK, 2961–2966.
Cristea, B., Roviras, D., and Escrig, B. (2009). Turbo receivers for interleave division Multiple access systems. IEEE Transaction on Communication (57), 2090–2097.
Kusume, K., Bauch, G., and Utschick, W. (2009). IDMA vs. CDMA: Detectors, performance and complexity, in Proceedings of IEEE GLOBECOM, Honolulu, HI,USA.
Novak, C., Hlawatsch, F., and Matz, G. (2007). MIMO-IDMA: Uplink multiuser MIMO communications using interleave-division multiple access and low-complexity iterative receivers, in Proceedings of IEEE ICASSP, Honolulu, HI, USA, 225–228.
Hao, D., and Hoeher, P. A. (2008). Helical interleaver set design for interleave division multiplexing and related techniques. IEEE Communication Letters (12), 843–845.
Nabar, R.U., B’lcskei, H., Erceg, V., et al. (2002). Performance of multi antenna signalling techniques in the presence of polarization diversity. IEEE Transaction on Signal Processing (50), 2553–2562.
Zhou, X., Shi, Z., and Reed, M. C. (2007). Iterative channel estimation for IDMA systems in time-varying channels. In Proceedings of IEEE GLOBECOM, Washington, DC, USA, 4020–4024.
Hoeher, P. A., Schoeneich, H., and Fricke, C. (2008). Multi-layer interleave-division multiple access: Theory and practice. European Transaction on Telecommunication (19), 523–536.
Mahafeno, I., Langlais, C., and Jego, C. (2006). OFDM-IDMA versus IDMA with ISI cancellation for quasi-static Rayleigh fading multipath channels, in Proceedings of 4th International Symposium on Turbo Codes Related Topics, Munich, Germany, 3–7.
Ping, L., Guo, Q., and Tong, J. (2007). The OFDM-IDMA approach to wireless communication systems. IEEE Wireless Communication (14), 18–24.
Novak, C., Matz, G., and Hlawatsch (2009). Factor graph based design of an OFDM-IDMA receiver performing joint data detection, channel estimation, and channel length selection, in Proceedings of IEEE ICASSP, Taipei (Taiwan), 2561–2564.
Aamir Habib (2012). Receive antenna selection in diversely polarized MIMO transmissions with convex optimization. Elsevier Journal on Physical Communications (5), 328–337.
Loeliger, H. A., Dauwels, J., Hu, J., et al. (2007). The factor graph approach to model-based signal processing, in Proceedings IEEE 2007, Vol. 95, 1295–1322.
Boutros, J., and Caire, G. (2002). Iterative multiuser joint decoding: Unified framework and asymptotic analysis. IEEE Transaction on Information Theory (48), 1772–1793.
Worthen, A. P., and Stark, W. E. (2001). Unified design of iterative receivers using factor graphs. IEEE Transaction on Information Theory (47), 843–849.
Valenti, M. C., and Woerner, B. D. (2001). Iterative channel estimation and decoding of pilot symbol assisted turbo codes over flat-fading channels. IEEE Journal on Selected Areas Communication (19),1697–1705.
Huaning, N., Manyuan, S., Ritcey, J., et al. (2005). A factor graph approach to iterative channel estimation and LDPC decoding over fading channels. IEEE Transaction on Wireless Communication (4), 1345–1350.
Liu, Y., BruneL, L., and Boutros, J. J. (2008). Belief propagation with Gaussian approximation for joint channel estimation and decoding, in Proceedings of IEEE PIMRC, Cannes, France, 1–5.
Zhao, M., Shi, Z., and Reed, M. C. (2008). Iterative turbo channel estimation for OFDM system over rapid dispersive fading channel. IEEE Transaction on Wireless Communication (7), 3174–3184.
Kermoal, J. P., Schumacher, L., K. Pedersen, K. L., et al. (2002). A stochastic MIMO radio channel model with experimental vali-dation. IEEE Journal on Selected Areas in Communication (20),1211–1226.
3GPPP(TR 30.803) (2007). Evolved universal terrestrial radio access (E-UTRA) user equipment (UE) radio transmission and reception (Release8). Technical specification, 2007, Sophia Antipolis, France.
IEEE 802.16a-03/01. Channel Models for Fixed Wireless Applications, 2003-06-27.
3GPP TR25.996 V6.1.0. Spatial Channel Model for Multiple Input Multiple Output (MIMO) Simulation (Rel.6), 2003-09.
Kalidoss, R., Vijayarangan, V, and Sukanesh, R. (2006). “Low Crest Mapping for PAPR reduction in OFD M system”, IET International Conference on Wireless, Mobile and Multimedia Networks,China, 1–4.
Kalidoss, R., Bhagyaveni, M. A., and Vishvaksenan, K. S. (2014). A location based duplex scheme for cost effective rural broadband connectivity using IEEE 802.22 cognitive radio based wireless regional area networks. Fluctuation and Noise Letters (13).
Karthipan, R., Vishvaksenan, K. S., Kalidoss, R., and Sureshbabu, R. (2016). Uplink capacity enhancement in IEEE 802.22 using modified duplex approach. Wireless Personal Communication (86),635–656.
Vishvaksenan, K. S., Mithra, K., Kalidoss, R., and Karthipan, R. (2016). Experimental study on Elliot wave theory for Handoff Prediction. Fluctuation and Noise Letters (15), 1–11.
Vishvaksenan, K. S., Kalaiarasan, R., Kalidoss, R., and Karthipan, R. (2017). “Real time experimental study and analysis of Elliott wave theory in signal strength prediction,” in Proceedings of National Academy of Sciences, Springer, 2017. (Article in Press).
Saravanan, M., Kalidoss, R., Partibane, B., and Karthipan, R. (2017). Mitigation of mutual exclusion problem in 5G new radio standards by token and non token based algorithms. Cluster Computing, 2017.