Analyses of Virtual MIMO Multi-User System Performance with Linear Precoding Schemes Using Indoor Measurements at 5 GHz
- 1 Department of Computer Sciences, University of Law and Political Sciences of Bamako, Bamako, Mali
Abstract
In this paper, based on 5 GHz indoor multi-user measurements, linear precoding schemes such as zero-forcing (ZF), minimum mean square error (MMSE) and successive interference cancelation (SIC) are applied in the base station in order to investigate the performance of virtual multi-input multi-output (MIMO) over single-user MIMO system. However, to form a virtual MIMO multi-user system, the resources of two users are brought together. In order to achieve a low spatial correlation, two spaced antennas in the MS have been chosen and four spaced antennas elements in BS have been selected. Therefore, the resources of two users (U1 and U2) are brought together to form a 4 × 4 virtual MIMO multi-user system with the BS. The properties of the user_1 (U1) and user_2 (U2) will be analyzed and compared to those properties of virtual MIMO multi-user system formed by U1 and U2. In most cases, the maximum achievable rate is seen with virtual MIMO multi-user compared to single-user MIMO. So virtual MIMO multi-user is desirable for boosting system capacity than single-user MIMO.
- Dou, C. (2012) Performance Evaluations of Fading Effects in OFDM Systems Using Channel Transfer Function. 2012 18th Asia-Pacific Conference on Communications, Jeju, 908-913.
- Alimohammad, A., Fard, S.F. and Cockburn, B.F. (2011) Accurate Multiple-Input Multiple-Output Fading Channel Simulator Using a Compact and High Throughput Reconfigurable Architecture. IET Communications, 5, 844-852. https://doi.org/10.1049/iet-com.2009.0595
- Fischer, R.F.H. (2002) Precoding and Signal Shaping for Digital Transmission. Wiley-IEEE Press, New York. https://doi.org/10.1002/0471439002
- Cao, H., Li, J., Fang, X. and Wang, X. (2013) A Novel Pre-Processing and Adaptive Statistical Threshold for Sphere Detection in MIMO Systems. EURASIP Journal on Wireless Communications and Networking, 2013, Article Number: 275. https://doi.org/10.1186/1687-1499-2013-275
- Sanayei, S. and Nosratinia, A. (2004) Antenna Selection in MIMO Systems. IEEE Communications Magazine, 42, 68-73. https://doi.org/10.1109/MCOM.2004.1341263
- Yang, Y., Blum, R.S. and Sfar, S. (2009) Antenna Selection for MIMO Systems with Closely Spaced Antennas. EURASIP Journal on Wireless Communications and Networking, 2009, Article Number: 739828. https://doi.org/10.1155/2009/739828
- Xu, K. and Chizuni, D. (2007) A V-BLAST Based Virtual MIMO Transmission Scheme for Sensor Network Lifetime Maximization. 2007 IEEE 66th Vehicular Technology Conference, Baltimore, 30 September 2007-3 October 2007, 377-381. https://doi.org/10.1109/VETECF.2007.91
- Bejarano, O. and Knightly, E.W. (2013) IEEE 802.11ac: From Channelization to Multi-User MIMO. IEEE Communications Magazine, 51, 84-90. https://doi.org/10.1109/MCOM.2013.6619570
- Jayaweera, S.K. (2007) V-BLAST-Based Virtual MIMO for Distributed Wireless Sensor Networks. IEEE Transactions on Communications, 55, 1867-1872. https://doi.org/10.1109/TCOMM.2007.906389
- Brown, T., Carvalho, E.D. and Kyritsy, P. (2012) MIMO Transceivers. In: The MIMO Radio Channel with Matlab Examples, John Wiley & Sons, Ltd., Hoboken, 75-143. https://doi.org/10.1002/9781119944966.ch3
- Cho, Y.S., Kim, J., Yang, W.Y. and Kang, C.G. (2010) MIMO: Channel Capacity. In: MIMO-OFDM Wireless Communications with Matlab, John Wiley & Sons (Asia) Pte Ltd., Singapore, 263-280. https://doi.org/10.1002/9780470825631.ch9
- Webb, M., Yu, M. and Beach, M. (2011) Propagation Characteristics, Metrics, and Statistics for Virtual MIMO Performance in a Measured Outdoor Cell. IEEE Transactions on Antennas and Propagation, 59, 236-244. https://doi.org/10.1109/TAP.2010.2090643