Partial Nulling Regularized Block Diagonalization Using Unfair Channel Selection for Post-Coding with Low-Complexity
Source abstract
Abstract
A number of requirements for 5G mobile communication are satisfied by adopting multi-user multiple input multiple output (MU-MIMO) systems. The inter user interference (IUI) which is an inevitable problem in MU-MIMO systems becomes controllable when the precoding scheme is used. The proposed scheme, which is one of the precoding schemes, is built on regularized block diagonalization (RBD) precoding and utilizes the partial nulling concept, which is to leave part of the IUI at the same time. Diversity gain is obtained by leaving IUI, which is made by choosing the row vectors of the channel matrix that are not nullified. Since the criterion for choosing the row vectors of the channel is the power of the channel, the number of selected row vectors of the channel for each device can be unfair. The proposed scheme achieves performance enhancement by obtaining diversity gain. Therefore, the bit error rate (BER) performance is better and the computational complexity is lower than RBD when the same data rate is achieved. When the number of reduced data streams is not enough for most devices to achieve diversity gain, the proposed scheme has better performance compared to generalized block diagonalization (GBD). The low complexity at the receiver is achieved compared to GBD by using the simple way to remove IUI.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced MIMO Systems Optimization · Advanced Wireless Communication Techniques · Cooperative Communication and Network Coding
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea
Department of Computer Engineering, Sejong University, Seoul 05006, Korea
References (24)
Show source-provided references
1. Zhao, S., Li, Q., and Tian, M. (2020). Capacity-Maximized Transmitter Precoding for MU MIMO VLC Systems with Bounded Channel Uncertainties. IEEE Syst. J.10.1109/JSYST.2020.2984692 ↗
2. Multi-User Linear Precoding for Downlink Generalized Spatial Modulation Systems10.1109/LCOMM.2019.2947451 ↗
3. Siyari, P., and Krunz, M. (2019, January 10–12). Linear Precoding with Friendly Jamming in Overloaded MU-MIMO Wiretap Networks. Proceedings of the 2019 IEEE Conference on Communications and Network Security (CNS), Washington, DC, USA.10.1109/CNS.2019.8802693 ↗
4. Linear Precoding and Stream Combining for Rate Splitting in Multiuser MIMO Systems10.1109/LCOMM.2020.2969158 ↗
5. Flores, A.R., de Lamare, R.C., and Clerckx, B. (2019, January 20–24). Linearly Precoded Rate-Splitting Techniques with Block Diagonalization for Multiuser MIMO Systems. Proceedings of the 2019 IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, China.10.1109/ICCW.2019.8757102 ↗
6. Crâşmariu, V., Arvinte, M., Enescu, A., and Ciochină, S. (2016, January 27–28). Waterfilling Power Allocation Applied in Block-Diagonalization Multi-User MIMO Precoding Technique. Proceedings of the 2016 12th IEEE International Symposium on Electronics and Telecommunications (ISETC), Timisoara, Romania.10.1109/ISETC.2016.7781064 ↗
7. Nishimori, K., Kudo, R., Takatoti, Y., Ohta, A., and Tsunekawa, K. (2006, January 11–14). Performance Evaluation of 8×8 Multi-User MIMO-OFDM Testbed in an Actual Indoor Environment. Proceedings of the 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications, Helsinki, Finland.10.1109/PIMRC.2006.253924 ↗
8. Kashino, Y., Honma, N., Tsunezawa, M., and Nishimori, K. (2016, January 24–28). Channel capacity of multi-user full-duplex MIMO in actual outdoor environment. Proceedings of the 2016 International Symposium on Antennas and Propagation (ISAP), Okinawa, Japan.
9. Shifting the MIMO Paradigm10.1109/MSP.2007.904815 ↗
10. Generalized Design of Multi-User MIMO Precoding Matrices10.1109/LCOMM.2008.060709 ↗
11. Nishimoto, H., Kato, S., Ogawa, Y., Ohgane, T., and Nishimura, T. (2008, January 15–18). Imperfect Block Diagonalization for Multiuser MIMO Downlink. Proceedings of the 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, Cannes, France.
12. Sharma, P.K., Vijavsai, T., Harika, D.V.S.N.S., Aiavkumar, B., and Kalesha, B. (2018, January 29–31). Bit Error Rate Analysis of Pre-Coding Techniques in Different MIMO Systems. Proceedings of the 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India.10.1109/ICECA.2018.8474550 ↗
13. Song, W., Chen, X., Wang, L., and Gong, J. (2018, January 25–28). Frobenius Norm Based Low Complexity User Selection for Multiuser MIMO-OFDM System. Proceedings of the 2018 21st International Symposium on Wireless Personal Multimedia Communications (WPMC), Chiang Rai, Thailand.10.1109/WPMC.2018.8712926 ↗
14. Writing on dirty paper (Corresp.)10.1109/TIT.1983.1056659 ↗
15. Jang, S., Yang, J., Eom, S., and Kim, D.K. (2008, January 11–14). A Near Optimal Linear Precoding for Multiuser MIMO Throughput Maximization. Proceedings of the VTC Spring 2008—IEEE Vehicular Technology Conference, Singapore.10.1109/VETECS.2008.173 ↗
16. Zero-forcing Methods for Downlink Spatial Multiplexing in Multiuser MIMO Channels10.1109/TSP.2003.821107 ↗
17. On the Achievable Throughput of a Multiantenna Gaussian Broadcast Channel10.1109/TIT.2003.813523 ↗
18. Improving the Performance of the Zero-Forcing Multiuser MISO Downlink Precoder Through User Grouping10.1109/TWC.2015.2478878 ↗
19. Low-Complexity Lattice Reduction-Aided Regularized Block Diagonalization for MU-MIMO Systems10.1109/LCOMM.2012.041112.112185 ↗
20. Generalized Channel Inversion Methods for Multiuser MIMO Systems10.1109/TCOMM.2009.11.070404 ↗
21. Nishimoto, H., Iura, H., Taira, A., Okazaki, A., and Okamura, A. (2016, January 3–6). Block Lower Multi-Diagonalization for Multiuser MIMO Downlink. Proceedings of the 2016 IEEE Wireless Communications and Networking Conference, Doha, Qatar.10.1109/WCNC.2016.7564687 ↗
22. Khai, L.D. (2010, January 26–30). A Generalized Approach to Block Diagonalization for Multiuser MIMO Downlink. Proceedings of the 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Instanbul, Turkey.
23. Lee, W.-S., Ro, J.-H., You, Y.-H., Hwang, D., and Song, H.-K. (2020). An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems. Appl. Sci., 10.10.3390/app10134547 ↗
24. Strang, G. (2011). Linear Algebra and Its Applications, Brooks/Cole INDIA. [4th ed.].