Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Full-Duplex MIMO Relay-Assisted Interference Alignment Algorithm in K-user Interference Channels

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In this paper, we investigate the transceiver design schemes for the full-duplex multiple-input multiple-output relay-assisted K-user single-input multiple-output interference channels. Firstly, we propose an iterative optimized reference vector for IA (IORV-IA) algorithm in the perfect channel state information (CSI) scenario. The proposed IORV-IA algorithm not only achieves the alignment of interference signals at each receiver, but also iteratively optimizes the IA reference vector by orthogonalizing the directions of the interference signals and the desired signal. With the optimized IA reference vector, the relay processing matrix and the receiving filter vectors are designed to further improve the system performance. Considering that the relay cannot obtain perfect CSIs in practice due to many factors, and the performance of the IA scheme is very sensitive to this error. Furthermore, we propose a robust transceiver design scheme based on mean square error (MSE) in the imperfect CSI scenario, which minimizes the sum of MSEs in the worst case through iteration. The proposed algorithms are evaluated in terms of the average sum rate and bit error rate performance and the simulation results show the advantages of the proposed algorithms over existing centralized IA and centralized zero-forcing algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

Notes

  1. \(\textbf{G}_r\) is introduced to show the expression of \(\beta\).

References

  1. Siddiqui, M. U. A., Qamar, F., Ahmed, F., Nguyen, Q. N., & Hassan, R. (2021). Interference management in 5G and beyond network: Requirements, challenges and future directions. IEEE Access, 9, 68932–68965. https://doi.org/10.1109/ACCESS.2021.3073543

    Article  Google Scholar 

  2. Cisco. (2020). Cisco visual networking index: Global mobile data traffic forecast update 2018–2023. Technical Report.

  3. 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.

    Article  MathSciNet  MATH  Google Scholar 

  4. Gomadam, K., Cadambe, V. R., & Jafar, S. A. (2011). A distributed numerical approach to interference alignment and applications to wireless interference networks. IEEE Transactions on Information Theory, 57(6), 3309–3322.

    Article  MathSciNet  MATH  Google Scholar 

  5. Peters, S. W., & Heath, R. W. (2009). Interference alignment via alternating minimization (pp. 2445–2448).

  6. Jing, X., Mo, L., Liu, H., & Zhang, C. (2018). Linear space-time interference alignment for K-user MIMO interference channels. IEEE Access, 6, 3085–3095. https://doi.org/10.1109/ACCESS.2017.2787153

    Article  Google Scholar 

  7. Ghasemi, A., Motahari, A. S., & Khandani, A. K. (2022). Interference alignment for the K-user MIMO interference channel. IEEE Transactions on Information Theory, 68(3), 1401–1411. https://doi.org/10.1109/TIT.2021.3130753

    Article  MathSciNet  MATH  Google Scholar 

  8. Messaoud, L. A., & Merazka, F. (2022). PSO and CPSO based interference alignment for K-user MIMO interference channel (pp. 1–5).

  9. Jafar, S. A., & Shamai, S. (2008). Degrees of freedom region of the MIMO \(X\) channel. IEEE Transactions on Information Theory, 54(1), 151–170.

    Article  MathSciNet  MATH  Google Scholar 

  10. Liu, F., Wang, S., Li, C., & Xu, Y. (2021). Propagation delay based cyclic interference alignment for X channels with two transmitters. IEEE Communications Letters, 25(6), 1844–1847. https://doi.org/10.1109/LCOMM.2021.3060855

    Article  Google Scholar 

  11. Suo, L., Li, J., Li, H., Zhang, S., & Davidson, T. N. (2019). Achievable sum rate and degrees of freedom of opportunistic interference alignment in MIMO interfering broadcast channels. IEEE Transactions on Communications, 67(6), 4062–4073. https://doi.org/10.1109/TCOMM.2019.2903250

    Article  Google Scholar 

  12. Zhang, L., Gui, L., Mo, X., & Qi, M. (2021). Interference subspace alignment-based precoding design for multi-cell multi-user systems. IEEE Transactions on Broadcasting, 67(1), 106–118. https://doi.org/10.1109/TBC.2020.3028344

    Article  Google Scholar 

  13. Li, J., Feng, W., Yu, F. R., & Jiang, W. (2021). Two new kinds of interference alignment schemes for cellular K-user MIMO downlink networks. IEEE Transactions on Vehicular Technology, 70(11), 11827–11842. https://doi.org/10.1109/TVT.2021.3115806

    Article  Google Scholar 

  14. Qu, X., & Kang, C. G. (2014). A closed-form solution to implement interference alignment and cancellation for a gaussian interference multiple access channel. IEEE Transactions on Wireless Communications, 13(2), 710–723. https://doi.org/10.1109/TWC.2013.122613.130151

    Article  Google Scholar 

  15. Jeon, Y.-S., Lee, N., & Tandon, R. (2018). Degrees of freedom and achievable rate of wide-band multi-cell multiple access channels with no CSIT. IEEE Transactions on Communications, 66(4), 1772–1786. https://doi.org/10.1109/TCOMM.2017.2783625

    Article  Google Scholar 

  16. U, V. M., & Selvaprabhu, P. (2022). A novel tri-staged ria scheme for cooperative cell edge users in a multi-cellular MIMO IMAC. IEEE Access, 10, 117141–117156. https://doi.org/10.1109/ACCESS.2022.3219254

    Article  Google Scholar 

  17. Tian, Y., & Wang, Z. (2020). Interference alignment in relay-aided networks with imperfect CSIT. Wireless Personal Communications, 114, 1085–1105. https://doi.org/10.1007/s11277-020-07410-2

    Article  Google Scholar 

  18. Jiang, X., Zheng, B., Zhu, W., Wang, L., & Hou, X. (2020). The average achievable rate of multi-antenna two-way relay networks with interference alignment. China Communications, 17(6), 121–130. https://doi.org/10.23919/JCC.2020.06.010

    Article  Google Scholar 

  19. Kim, H., & No, J. (2019). Achievable degrees of freedom of relay-aided MIMO cellular networks using opposite directional interference alignment. IEEE Transactions on Communications, 67(7), 4750–4764.

    Article  Google Scholar 

  20. Fadoul, M. M., & Leow, C. Y. (2020). Joint nullspace projection-based interference mitigation for full-duplex relay-assisted multicell networks. IEEE Systems Journal, 14(2), 2392–2399. https://doi.org/10.1109/JSYST.2020.2966797

    Article  Google Scholar 

  21. Ghari, S. M., Ghari, P. M., Fazel, M. S., Brante, G., & Imran, M. A. (2020). Interference alignment for one-hop and two-hops MIMO systems with uncoordinated interference. IEEE Transactions on Communications, 68(2), 902–914. https://doi.org/10.1109/TCOMM.2019.2955441

    Article  Google Scholar 

  22. Liu, W., Liu, K., Tian, L., Zhang, C., & Yang, Y. (2022). Joint interference alignment and subchannel allocation in Ultra-Dense Networks. IEEE Transactions on Vehicular Technology, 71(7), 7287–7296. https://doi.org/10.1109/TVT.2022.3163532

    Article  Google Scholar 

  23. Lu, H., Xie, X., Shi, Z., & Yang, H. (2020). Fairness enhancement for opportunistic interference alignment algorithm with low latency communications. IEEE Systems Journal, 14(4), 5002–5013. https://doi.org/10.1109/JSYST.2020.2969481

    Article  Google Scholar 

  24. Morales-spedes, M., Dobre, O. A., & Garc-Armada, A. (2020). Semi-blind interference aligned NOMA for downlink MU-MISO systems. IEEE Transactions on Communications, 68(3), 1852–1865. https://doi.org/10.1109/TCOMM.2019.2960334

    Article  Google Scholar 

  25. Ji, M., Chen, J., Lv, L., & Tang, H. (2021). Nonorthogonal multiple access enabled two-way relay system using signal alignment. IEEE Systems Journal, 16, 5765–5776. https://doi.org/10.1109/JSYST.2021.3124301

    Article  Google Scholar 

  26. Garg, N., Rudraksh, A., Sharma, G., & Ratnarajah, T. (2021). Improved rate-energy trade-off for SWIPT using chordal distance decomposition in interference alignment networks. IEEE Transactions on Green Communications and Networking, 6, 917–929. https://doi.org/10.1109/TGCN.2021.3115268

    Article  Google Scholar 

  27. Li, D., Zhang, D., & Zhang, G. (2020). Degrees of freedom for half-duplex and full-duplex multi-user cognitive radios. IEEE Transactions on Vehicular Technology, 69(3), 2812–2827. https://doi.org/10.1109/TVT.2020.2964878

    Article  Google Scholar 

  28. Xu, X., Wang, Y., Feng, W., & Yao, Y. (2021). An enhanced MAX-SINR strategy with interference leakage power constraint in multiuser multiantenna swipt systems. IEEE Access, 9, 127833–127840. https://doi.org/10.1109/ACCESS.2021.3105402

    Article  Google Scholar 

  29. Xie, Z., et al. (2020). Secured green communication scheme for interference alignment based networks. Journal of Communications and Networks, 22(1), 23–36. https://doi.org/10.1109/JCN.2019.000057

    Article  Google Scholar 

  30. Wang, D., Zhang, S., Cheng, Q., & Zhang, X. (2021). Joint interference alignment and power allocation based on Stackelberg game in device-to-device communications underlying cellular networks. IEEE Access, 9, 81651–81659. https://doi.org/10.1109/ACCESS.2021.3086148

    Article  Google Scholar 

  31. Liu, W., Tian, L., & Sun, J.-X. (2020). Interference alignment for MIMO downlink heterogeneous networks. IEEE Access, 8, 35090–35104. https://doi.org/10.1109/ACCESS.2020.2974584

    Article  Google Scholar 

  32. Liu, W., Li, L., Jiao, L., Dai, H., & Zheng, G. (2021). Joint interference alignment and probabilistic caching in MIMO small-cell networks. IEEE Transactions on Vehicular Technology, 70(9), 9400–9407. https://doi.org/10.1109/TVT.2021.3099157

    Article  Google Scholar 

  33. Shibao, I., et al. (2022). An adaptive interference alignment scheme based on the dynamic selection of desired transmitters for unmanned ship network. Wireless Networks, 28, 1–13. https://doi.org/10.1007/s11276-022-02964-4

    Article  Google Scholar 

  34. Ding, T., Yuan, X., & Liew, S. C. (2017). On the degrees of freedom of the symmetric multi-relay MIMO Y channel. IEEE Transactions on Wireless Communications, 16(9), 5673–5688. https://doi.org/10.1109/TWC.2017.2712770

    Article  Google Scholar 

  35. Chen, S., & Cheng, R. S. (2013). On the achievable degrees of freedom of a \(K\)-user MIMO interference channel with a MIMO relay. IEEE Transactions on Wireless Communications, 12(8), 4118–4128.

    Article  Google Scholar 

  36. Liu, Z., & Sun, D. (2015). Relay-assisted opposite directional interference alignment: Feasibility condition and achievable degrees of freedom. IEEE Communications Letters, 19(1), 66–69.

    Article  Google Scholar 

  37. Li, X., Sun, Y., Zhao, N., Yu, F. R., & Xu, Z. (2015). A novel interference alignment scheme with a full-duplex MIMO relay. IEEE Communications Letters, 19(10), 1798–1801.

    Article  Google Scholar 

  38. Hong, S., Brand, J., Choi, J. I., Jain, M., & Levis, P. (2014). Applications of self-interference cancellation in 5G and beyond. IEEE Communications Magazine, 52(2), 114–121.

    Article  Google Scholar 

  39. Chalise, B. K., & Vandendorpe, L. (2009). MIMO relay design for multipoint-to-multipoint communications with imperfect channel state information. IEEE Transactions on Signal Processing, 57(7), 2785–2796. https://doi.org/10.1109/TSP.2009.2018610

    Article  MathSciNet  MATH  Google Scholar 

  40. Shen, H., Li, B., Tao, M., & Wang, X. (2010). MSE-based transceiver designs for the MIMO interference channel. IEEE Transactions on Wireless Communications, 9(11), 3480–3489. https://doi.org/10.1109/TWC.2010.091510.091836

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by Sichuan Science and Technology Program (No.2019YJ0230), the National Natural Science Foundation of China (No. 61461026) and the Project of the Science and Technology Department in Sichuan Province (Grant No. 2021ZYD0004).

Funding

Declared that in acknowledgement.

Author information

Author notes

  1. Li Hao and Kejun Jia contributed equally to this work.

Authors and Affiliations

  1. The Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, 610031, China

    Lijun Bai & Li Hao

  2. College of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, 643002, China

    Lijun Bai

  3. School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China

    Kejun Jia

Authors
  1. Lijun Bai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Hao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kejun Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Li Hao.

Ethics declarations

Conflict of interest

These no potential competing interests in our paper. And all authors have seen the manuscript and approved to submit to the journal. We confirm that the content of the manuscript has not been published or submitted for publication elsewhere.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bai, L., Hao, L. & Jia, K. Full-Duplex MIMO Relay-Assisted Interference Alignment Algorithm in K-user Interference Channels. Wireless Pers Commun 131, 13–37 (2023). https://doi.org/10.1007/s11277-023-10395-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-023-10395-3

Keywords

Search

Navigation