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Interference Suppression and Receiving Performance Improvement for Local Cooperation with Channel Estimation Error

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Abstract

In the next-generation wireless communication systems, the local cooperation between different units may be deployed to satisfy communication requirements. In this case, the interference suppression between different units and the receiving performance improvement for each single unit should be considered. Multiple schemes have been utilized to solve these problems. However, these schemes ordinarily require sufficiently accurate information of channel, if this accuracy can not be maintained (e.g., channel estimation error can not be ignored), these schemes may not obtain the satisfactory performances. To overcome this disadvantage, in this paper, a novel scheme is proposed. The proposed scheme has several characteristics: (i) a low-complexity extra estimation is implemented to acquire more information of channel estimation error; (ii) with the help of channel estimation error information, each unit can separately execute a two-step process for interference suppression and receiving performance improvement; (iii) no exorbitant information interaction and high-overhead algorithm are needed between multiple units. Through characteristic analysis and numerical results, it is found the proposed scheme can achieve the satisfactory effect in the locally cooperative network.

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References

  1. 3GPP TS 21.205 (v15.0.0) (2018) Technical specifications and technical reports for a 5G based 3GPP system (Release 15)

  2. Yaacoub E, Alouini M-S (2020) A key 6G challenge and opportunityłconnecting the base of the pyramid: A survey on rural connectivity. Proc IEEE 108(4):533–582

    Article  Google Scholar 

  3. Liu Y, Wang X, Boudreau G, Sediq A, Abou-Zeid H (2021) A multi-dimensional intelligent multiple access technique for 5G beyond and 6G wireless networks. IEEE Trans Wireless Commun 20 (2):1308–1320

    Article  Google Scholar 

  4. Wan L, et al. (2018) 4G/5G spectrum sharing: efficient 5G deployment to serve enhanced mobile broadband and internet of things applications. IEEE Veh Technol Mag 13(4):28–39

    Article  Google Scholar 

  5. Sharma SK, Wang XB (2020) Toward massive machine type communications in ultra-dense cellular IoT networks: Current issues and machine learning-assisted solutions. IEEE Commun Surveys Tuts 22 (1):426–471. Firstquarter

    Article  Google Scholar 

  6. She CY, et al. (2021) A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning. Proc IEEE 109(3):204–246

    Article  Google Scholar 

  7. Bassoy S, Farooq H, Imran MA, Imran A (2017) Coordinated multi-point clustering schemes: A survey. IEEE Commun Surv Tuts 19(2):743–764. Secondquarter

    Article  Google Scholar 

  8. Ali MS, Hossain E, Kim DI (2018) Coordinated multipoint transmission in downlink multi-cell NOMA systems: Models and spectral efficiency performance. IEEE Wirel Commun 25(2):24–31

    Article  Google Scholar 

  9. Khoshnevisan M, et al. (2019) 5G industrial networks with coMP for URLLC and time sensitive network architecture. IEEE J Sel Areas Commun 37(4):947–959

    Article  Google Scholar 

  10. Hua M, Wu Q, Ng DWK, Zhao J, Yang L (2021) Intelligent reflecting surface-aided joint processing coordinated multipoint transmission. IEEE Trans Commun 69(3):1650–1665

    Article  Google Scholar 

  11. Park S-H, Simeone O, Shitz SS (2016) Time-asynchronous robust cooperative transmission for the downlink of c-RAN. IEEE Signal Process Lett 23(10):1444–1448

    Article  Google Scholar 

  12. Kim D, Yang Y, Sung KW, Kang J (2018) Cooperation strategies for partly wireless c-RAN. IEEE Commun Lett 22(6):1248–1251

    Article  Google Scholar 

  13. Flordelis J, Rusek F, Tufvesson F, Larsson EG, Edfors O (2018) Massive MIMO performance-TDD versus FDD: What do measurements say. IEEE Trans Wireless Commun 17(4):2247–2261

    Article  Google Scholar 

  14. Fei ZS, Yang A, Xing CW, Yuan JH, Kuang JM (2013) Performance of superposition coding for downlink coordinated two-point system. IEEE Trans Veh Technol 62(8):4057–4064

    Article  Google Scholar 

  15. Wu WH, Wang K, Zeng WL, Ding Z, Xiao CS (2015) Cooperative multi-cell MIMO downlink precoding with finite-alphabet inputs. IEEE Trans Commun 63(3):766–779

    Article  Google Scholar 

  16. Mahboobi B, Mehrizi S, Ardebilipour M (2015) Multicast relay beamforming in CDMA networks: Nonregenerative approach. IEEE Commun Lett 19(8):1418–1421

    Article  Google Scholar 

  17. Lakshmana TR, Tolli A, Svensson T (2016) Improved local precoder design for JT-coMP with periodical backhaul CSI exchange. IEEE Commun Lett 20(3):566–569

    Article  Google Scholar 

  18. Kim H-J, Baek J-S, Oh J-M, Seo J-S (2012) Improved leakage-based precoding with vector perturbation for MU-MIMO systems. IEEE Commun Lett 16(11):1868–1871

    Article  Google Scholar 

  19. Wang LW, Liang QL (2018) Performance analysis of cooperative multicell precoding with global CSI and local individual CSI in the large dimensional regime. IEEE Trans Veh Technol 67(4):3229–3238

    Article  Google Scholar 

  20. Xu J, Ren PY, Xu CB, Zhang YZ (2017) Distributed cooperative two-cell zero-forcing precoding with local channel correlation. IEEE Trans Veh Technol 66(9):8086–8102

    Article  Google Scholar 

  21. Tran L-N, Juntti M, Bengtsson M, Ottersten B (2013) Beamformer designs for MISO broadcast channels with zero-forcing dirty paper coding. IEEE Trans Wireless Commun 12(3):1173–1185

    Article  Google Scholar 

  22. Zu KK, de Lamare RC, Haardt M (2013) Generalized design of low-complexity block diagonalization type precoding algorithms for multiuser MIMO systems. IEEE Trans Commun 61(10):4232–4242

    Article  Google Scholar 

  23. Yang Y, Wang WJ, Gao XQ (2018) Distributed RZF precoding for multiple-beam MSC downlink. IEEE Trans Aerosp Electron Syst 54(2):968–977

    Article  Google Scholar 

  24. Ma H, Mostafa A, Lampe L, Hranilovic S (2018) Coordinated beamforming for downlink visible light communication networks. IEEE Trans Commun 66(8):3571–3582

    Article  Google Scholar 

  25. Kaleva J, Tolli A, Juntti M, Berry RA, Honig ML (2018) Decentralized joint precoding with pilot-aided beamformer estimation. IEEE Trans Signal Process 66(9):2330–2341

    Article  MathSciNet  Google Scholar 

  26. Li Z, et al. (2019) Coordinated multi-point transmissions based on interference alignment and neutralization. IEEE Trans Wirel Commun 18(7):3347–3365

    Article  Google Scholar 

  27. Xu D, Yin W, Zhang Q, Zhao P (2020) Interference mitigation and receiving performance improvement strategies for local cooperation in the 5G system. IET Commun 14(11):1696–1703

    Article  Google Scholar 

  28. Cai Y, de Lamare RC, Yang L-L, Zhao M (2015) Robust MMSE precoding based on switched relaying and side information for multiuser MIMO relay systems. IEEE Trans Veh Technol 64(12):5677–5687

    Article  Google Scholar 

  29. Li Q, Zhang Q, Qin J (2017) Robust Tomlinson-Harashima precoding with Gaussian uncertainties for SWIPT in MIMO broadcast channels. IEEE Trans Signal Process 65(6):1399–1411

    Article  MathSciNet  Google Scholar 

  30. Zhao N, Yu FR, Sun H, Nallanathan A, Yin H (2013) A novel interference alignment scheme based on sequential antenna switching in wireless networks. IEEE Trans Wirel Commun 12(10):5008–5021

    Article  Google Scholar 

  31. Wang J, Bengtsson M, Ottersten B, Palomar DP (2013) Robust MIMO precoding for several classes of channel uncertainty. IEEE Trans Signal Process 61(12):3056–3070

    Article  Google Scholar 

  32. Bing JL, Gopal L, Rong Y, Chiong CWR, Zang Z (2021) Robust transceiver design for multi-hop AF MIMO relay multicasting from multiple sources. IEEE Trans Veh Technol 70(2):1565–1576

    Article  Google Scholar 

  33. Zhao M-M, Cai Y, Zhao M-J, Xu Y, Hanzo L (2020) Robust joint hybrid analog-digital transceiver design for full-duplex mmWave multicell systems. IEEE Trans Commun 68(8):4788–4802

    Article  Google Scholar 

  34. Li X, Wang W, Zhang M, Zhou F, Dhahir NA (2020) Robust secure beamforming for SWIPT-Aided relay systems with full-duplex receiver and Imperfect CSI. IEEE Trans Veh Technol 69(2):1867–1878

    Article  Google Scholar 

  35. Wang D, Wang F (2019) Wireless MIMO switching with imperfect CSI in frequency and time division duplex. IEEE Trans Wirel Commun 18(5):2579–2590

    Article  Google Scholar 

  36. Cirik AC, Biswas S, Taghizadeh O, Ratnarajah T (2018) Robust transceiver design in Full-Duplex MIMO cognitive radios. IEEE Trans Veh Technol 67(2):1313–1330

    Article  Google Scholar 

  37. Geng X, An B, Liu F, Cao F (2015) Robust THP transceiver design for MIMO interference channel. IEEE Commun Lett 19(9):1640–1643

    Article  Google Scholar 

  38. Bogale TE, Vandendorpe L, Chalise BK (2012) Robust transceiver optimization for downlink coordinated base station systems: Distributed algorithm. IEEE Trans Signal Process 60(1):337–350

    Article  MathSciNet  Google Scholar 

  39. Lutkepohl H (1997) Handbook of matrixes. USA: Wiley Press

  40. Proakis JG, Salehi M (2008) Digital communications. USA: McGraw-Hill Press 5th edn

  41. Faruque S (2015) Radio Frequency PropagationMade Easy. Basel, Switzerland: Springer International Publishing

  42. Baum DS, Hansen J., Salo J. (2005) An interim channelmodel for beyond- 3G systems: Extending the 3GPP spatial channel model (SCM). In: Proc. IEEE 61st Veh. Technol. Conf., pp 3132–3136

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Authors and Affiliations

  1. Key Laboratory of Grain Information Processing and Control, Henan University of Technology, Ministry of Education, Zhengzhou, China

    Datong Xu, Mingyang Cui & Pan Zhao

  2. Department of Communications Engineering, College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China

    Datong Xu, Mingyang Cui & Pan Zhao

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  1. Datong Xu
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  2. Mingyang Cui
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  3. Pan Zhao
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Correspondence to Datong Xu.

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The research reported in this paper was supported by the Key Scientific Research Project of Colleges and Universities in Henan Province under grant no. 20A510006, the Ph.D. Programs Foundation of Henan University of Technology under grant no. 2018BS073, the Open Foundation of Key Laboratory of Grain Information Processing & Control, (Henan University of Technology), Ministry of Education under grant no. KFJJ-2020-115, the Key Science-Technology Project of Henan Province under grant no. 212102310296, and the Key Science-Technology Project of Henan Province under grant no. 212102210169.

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Xu, D., Cui, M. & Zhao, P. Interference Suppression and Receiving Performance Improvement for Local Cooperation with Channel Estimation Error. Mobile Netw Appl 27, 1734–1745 (2022). https://doi.org/10.1007/s11036-022-01927-5

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