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Telecommunications and Radio Engineering
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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v78.i13.60
pages 1203-1211

BEAMFORMING BASED ON SLR FOR UPLINK CHANNEL IN MU-MIMO SYSTEM AND DETECTION DESIGN

C. Ciftlikli
Erciyes University, Talas, Kayseri, 38280, Turkey
W. Al-Obaidi
Erciyes University, Talas, Kayseri, 38280, Turkey
M. Al-Obaidi
Erciyes University, Talas, Kayseri, 38280, Turkey

SINOPSIS

Multi-user (MU) techniques are adopted in wireless systems to fully benefit from multiple-input multiple-output (MIMO) antenna array. Beamforming (BF) technique in the MU-MIMO limits the effect of the co-channel interference (CCI) and improves capacity, and quality of service (QoS) of the system. In this study, we propose a new uplink MU-MIMO precoding scheme based on maximizing the signal to leakage ratio (SLR). The SLR based beamforming can exclude the CCI and noise for MU-MIMO mode effectively and can be realized more easily than the traditional ideal SINR based system. Our major assumption for the study is that base station (BS) use ordered successive interference cancellation (OSIC) detection when the channel state information (CSI) of each user is available at the BS and in each user. We propose the maximum-likelihood (ML) method to estimate the received symbols. Promising results from the simulation show that the performance of the proposed scheme over Rayleigh and Rician fading channels is significantly better than the performance of the classical uplink MU-MIMO precoding system. In addition, in our proposed scheme there is no restriction on the number of antennas at the transmitter and receiver comparing with the classical uplink MU-MIMO precoding system.

REFERENCIAS

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  2. Bengtsson, E.L., Rusek, F., Malkowsky, S., Tufvesson, F. et al., (2017) A simulation framework for multiple-antenna terminals in 5G massive MIMO system, IEEE Access, 5, pp. 26819-26831, https://doi.org/10.1109/ACCESS.2017.2775210.

  3. Gupta, A. and Jha, R.K., (2015) A survey of 5G network: Architecture and emerging technologies, IEEE Access, 3, pp. 1206-1232, https://doi.org/10.1109/ACCESS.2015.2461602.

  4. Liu, L.J., Chen, R.H., Geirhofer, S., (2012) Downlink MIMO in LTE-advanced: SU-MIMO vs MU- MIMO, IEEE Commun. Magazine, 50(2), pp. 140-147, https://doi.org/10.1109/MCOM. 2012.6146493.

  5. Schubert, M. and Boche, H., (2004) Solution of the multiuser downlink beamforming problem with individual SINR constraints, IEEE Transaction on Vehicular Technology, 53(1), pp. 18-28, https://doi.org/10.1109/TVT.2003.819629.

  6. Zhang, J., Wu, Y., Xu, M., and Wang, J., (2005) Linear transmitter precoding design for downlink of multiuser MIMO systems, Electronics Letters, 41(14), pp. 811-813, https://doi.org/10.1049/ el:20050847.

  7. Wiesel, A., Eldar, Y.C., and Shamai, S., (Shitz) (2006) Linear precoding via conic optimization for fixed MIMO receivers, IEEE Transaction on Signal Processing, 54(1), pp. 161-176. https://doi.org/10.1109/TSP.2005.861073.

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  9. Sadek, M., Tarighat, A., and Sayed, A.H., (2007) Active antenna selection in multi-user MIMO communications,, IEEE Trans. Signal Processing, 55(4), pp. 1498-1510. https://doi.org/ 10.1109/TSP.2006.888893.

  10. Sadek, M., Tarighat, A., and Sayed, A.H., (2007) A leakage-based precoding scheme for downlink multi-user MIMO Channels, IEEE Trans. Wirel. Commun., 6(5), pp. 1711-172. https://doi.org/ 10.1109/TWC.2007.360373.

  11. Rhee, W., Wei Yu, and Cioffi, J.M., (2004) The optimality of beamforming in uplink multiuser wireless systems, IEEE Trans. Wireless Commun., 3(1), pp. 86-96, https://doi.org/ 10.1109/TWC.2003.819017.

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  13. Cho, Y.S., Kim, J., Yang, W.Y., Kang, C-G., (2010) MIMO-OFDM Wireless Communications with MATLAB, Singapore: John Wiley & Sons. https://doi.org/10.1002/9780470825631.


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