Low Complexity Interference Alignment for Distributed Large-Scale MIMO Hardware Architecture and Implementation for 5G Communication

  • Authors

    • Savitri Galih
    • . .
    • . .
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.33.23561
  • Distributed Massive MIMO, Interference Alignment, FPGA.
  • Massive MIMO or Large Scale MIMO is a promising solution for achieving superior data rates in 5G communication systems. However, it has limitation in term of scalability and coverage for users that has highly spatial separation. Distributed massive MIMO is expected to enhance these drawbacks. One main problem arises in this scheme is the MIMO interference channel condition that can be copied by interference alignment algorithm. The main consideration for interference alignment algorithm in distributed Massive MIMO is to achieve low complexity precoding to eliminate interference channel condition and to design efficient hardware architecture for its implementation. Previous research regarding IA for Distributed Massive MIMO indicate that the complexity issues is still not widely discussed. This paper proposed the low complexity IA scheme for large scale MIMO system based on limited interferer and the implementation of low cost interference alignment and wireless synchronization for distributed MIMO using software defined radio hardware. From the simulation result, it shows that limited interferer IA algorithm achieve acceptable BER performance, i.e. in order of 10-3. The hardware implementation of the IA precoding matrix computation is also discussed. Based on the experiment, it is show that the proposed algorithm and architecture achieved higher hardware performance compared to the linear IA.

     

     

  • References

    1. [1] Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014). Massive MIMO for next generation wireless systems. IEEE Communications Magazine, 52(2), 186-195.

      [2] Yang, S., & Hanzo, L. (2015). Fifty years of MIMO detection: The road to large-scale MIMOs. IEEE Communications Surveys and Tutorials, 17(4), 1941-1988.

      [3] Schmidt, D. A., Utschick, W., & Honig, M. L. (2010). Large system performance of interference alignment in single-beam MIMO networks. Proceedings of the IEEE Global Telecommunications Conference, pp. 1-6.

      [4] Cadambe, V. R., & Jafar, S. A. (2008). Interference alignment and degrees of freedom of the K-user interference channel. IEEE Transactions on Information Theory, 54(8), 3425-3441.

      [5] Shepard, C., Yu, H., Anand, N., Li, E., Marzetta, T., Yang, R., & Zhong, L. (2012). Argos: Practical many-antenna base stations. Proceedings of the ACM 18th Annual International Conference on Mobile Computing and Networking, pp. 53-64.

      [6] Suzuki, H., Kendall, R., Anderson, K., Grancea, A., Humphrey, D., Pathikulangara, J., Bengston, K., Matthews, J., & Russell, C. (2012). Highly spectrally efficient Ngara rural wireless broadband access demonstrator. Proceedings of the IEEE International Symposium on Communications and Information Technologies, pp. 914-919.

      [7] Marzetta, T. L. (2010). Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Transactions on Wireless Communications, 9(11), 3590-3600.

      [8] Rogalin, R., Bursalioglu, O. Y., Papadopoulos, H., Caire, G., Molisch, A. F., Michaloliakos, A., Balan, V., & Psounis, K. (2014). Scalable synchronization and reciprocity calibration for distributed multiuser MIMO. IEEE Transactions on Wireless Communications, 13(4), 1815-1831.

      [9] Mueller, A., Kammoun, A., Björnson, E., & Debbah, M. (2016). Linear precoding based on polynomial expansion: Reducing complexity in massive MIMO. EURASIP Journal on Wireless Communications and Networking, 2016(1), 1-22.

      [10] Chen, J., & Lau, V. K. (2014). Two-tier precoding for FDD multi-cell massive MIMO time-varying interference networks. IEEE Journal on Selected Areas in Communications, 32(6), 1230-1238.

      [11] El-Absi, M., El-Hadidy, M., & Kaiser, T. (2012). Antenna selection for interference alignment based on subspace canonical correlation. Proceedings of the IEEE International Symposium on Communications and Information Technologies, pp. 423-427.

      [12] Bresler, G., Cartwright, D., & Tse, D. (2014). Feasibility of interference alignment for the MIMO interference channel. IEEE Transactions on Information Theory, 60(9), 5573-5586.

      [13] Huang, X., Liang, C., & Ma, J. (2008). System architecture and implementation of MIMO sphere decoders on FPGA. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 16(2), 188-197.

      [14] Cerato, B., & Viterbo, E. (2009). Hardware implementation of a low-complexity detector for large MIMO. Proceedings of the IEEE International Symposium on Circuits and Systems, pp. 593-596.

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  • How to Cite

    Galih, S., ., ., & ., . (2018). Low Complexity Interference Alignment for Distributed Large-Scale MIMO Hardware Architecture and Implementation for 5G Communication. International Journal of Engineering & Technology, 7(4.33), 208-213. https://doi.org/10.14419/ijet.v7i4.33.23561