Skip to main content

Advertisement

Springer Nature Link
Log in

Software Defined Radio Based Non-orthogonal Multiple Access (NOMA) Systems

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

This paper focuses primarily on the study of the implementation of Non-orthogonal multiple access (NOMA) systems on Software defined radio (SDR) platforms, since NOMA has been recognized as a key enabling technology for the fifth generation (5G) wireless networks. A comprehensive review of the original birth, the latest trends, and the future research directions of NOMA is given in this paper. Specifically, several Successive Interference Cancellation (SIC) receivers are provided with mathematical analysis, such as the Ideal SIC receiver, Symbol-level SIC receiver, Codeword-level SIC receiver and Log likelihood ratio (LLR) based receivers. Furthermore, the bit error rate of two users’ signals is analyzed by implementing the NOMA system with and without the SIC using GNU Radio software. In addition, the performance of orthogonal multiple access (OMA) and NOMA systems is compared in terms of rate pairs (throughput), spectral efficiency and energy efficiency. Finally, the results reveal that the NOMA system performs better than OMA systems and it will be highlighted that SDR is a flexible platform to implement and test future wireless technologies.

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
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Availability of Data and Material

Not applicable.

Code Availability

www.gnuradio.org.in (It’s an open source software).

Abbreviations

3GPP:

3Rd Generation Partnership Project

ACM:

Adaptive coded modulation

ADC:

Analog to digital converter

AWGN:

Additive white Gaussian noise

BER:

Bit error rate

BTS:

Base station

CCSDS:

Consultative Committee for Space Data Systems (CCSDS)

CDMA:

Code-division multiple access

CSI:

Channel state information

DAC:

Digital to analog converter

EE:

Energy efficiency

FDMA:

Frequency division multiple access

GNU Radio:

A humorous recursive acronym meaning ‘GNU’s not Unix

GSM:

Global system for mobile

IHG-RA:

Interference hypergraph-based resource allocation

LDS-CDMA:

Low-density spreading CDMA

LLR:

Log likelihood ratio

LTE:

Long term evolution

MUSA:

Multi-user shared access

NOMA:

Non-orthogonal multiple access

OFDMA:

Orthogonal frequency division multiple access

OMA:

Orthogonal multiple access

OAI:

Open Air Interface

PDMA:

Pattern division multiple access

SIC:

Successive interference cancellation

SDR:

Software defined radio

SE:

Spectral efficiency

SCMA:

Sparse code multiple access

SDMA:

Spatial division multiple access

SM:

Spatial modulation

SNR:

Signal to noise ratio

TDMA:

Time-division multiple access

USRP:

Universal software radio peripheral

V2X:

Vehicle-to-everything

References

  1. Makki, B., et al. (2020). A survey of NOMA: Current status and open research challenges. IEEE Open Journal of the Communications Society, 1, 179–189.

    Google Scholar 

  2. Liaqat, M., et al. (2020). Power-domain non orthogonal multiple access (PD- NOMA) in cooperative networks: an overview. Wireless Networks, 26(1), 181–203.

    MathSciNet  Google Scholar 

  3. Faruque, S. (2019). Frequency division multiple access (FDMA) (pp. 21–33). Radio Frequency Multiple Access Techniques Made Easy. Springer: Cham.

    Google Scholar 

  4. Chi, K., et al. (2019). Energy provision minimization in wireless powered communication networks with network throughput demand: TDMA or NOMA? IEEE Transactions on Communications, 67(9), 6401–6414.

    Google Scholar 

  5. Zonzini, F., et al. (2019). Direct spread spectrum modulation and dispersion compensation for guided wave-based communication systems. In 2019 IEEE International Ultrasonics Symposium (IUS), IEEE.

  6. Fu, M., Yong, Z., & Yuanming, S. (2019). Intelligent reflecting surface for downlink non-orthogonal multiple access networks. In 2019 IEEE Globecom Workshops (GC Wkshps). IEEE.

  7. Wang, K., et al. (2019). 140-Gb/s PS-256-QAM Transmission in an OFDM System Using Kramers-Kronig Detection. IEEE Photonics Technology Letters, 31(17), 1405–1408.

    Google Scholar 

  8. Kizilirmak, R. C., & Bizaki, H. K. (2016). Non-orthogonal multiple access (NOMA) for 5G networks. Towards 5G Wireless Networks-A Physical Layer Perspective, 83, 83–98.

    Google Scholar 

  9. Fu, Y., et al. (2019). Mode selection between index coding and superposition coding in cache-based NOMA networks. IEEE Communications Letters, 23(3), 478–481.

    Google Scholar 

  10. Mahady, I. A., et al. (2019). Sum-rate maximization of NOMA systems under imperfect successive interference cancellation. IEEE Communications Letters, 23(3), 474–477.

    Google Scholar 

  11. Meylani, L., Adit, K., & Sigit, A. M. (2019). Radio resource allocation with the fairness metric for low density signature OFDM in underlay cognitive radio networks. Sensors, 19(8), 1921.

    Google Scholar 

  12. Wen, L., et al. (2019). Uplink multi-carrier multiple access scheme LDS-IOTA. IET Communications, 13(14), 2163–2167.

    Google Scholar 

  13. Zhang, Y., et al. (2020). Bayesian receiver design for grant-free NOMA with message passing based structured signal estimation. IEEE Transactions on Vehicular Technology, 69(8), 8643–8656.

    Google Scholar 

  14. Almusawi, I., Walid, A.-H., & Yaseen Tahir, H. (2020). Wireless Nonorthogonal Chaotic Communications: Opportunities, Challenges, and Future Directions. In IMDC-SDSP 2020: Proceedings of the 1st International Multi- Disciplinary Conference Theme: Sustainable Development and Smart Planning, IMDC-SDSP 2020, Cyperspace, 28–30 June 202. European Alliance for Innovation.

  15. Yuan, W., et al. (2019). Iterative receiver design for FTN signaling aided sparse code multiple access. IEEE Transactions on Wireless Communications, 19(2), 915–928.

    Google Scholar 

  16. Sharma, S., et al. (2019). Joint power-domain and SCMA-based NOMA system for downlink in 5G and beyond. IEEE Communications Letters, 23(6), 971–974.

    Google Scholar 

  17. Chen, S., et al. (2019). Pattern division multiple access (PDMA). Multiple access techniques for 5G wireless networks and beyond (pp. 451–492). Cham: Springer.

    Google Scholar 

  18. Ding, Z., & Vincent Poor, H. (2020). A simple design of IRS-NOMA transmission. IEEE Communications Letters, 24(5), 1119–1123.

    Google Scholar 

  19. Yuan, W., et al. (2020). Distributed estimation framework for beyond 5G intelligent vehicular networks. IEEE Open Journal of Vehicular Technology, 1, 190–214.

    Google Scholar 

  20. Do, D.-T., et al. (2020). Joint full-duplex and roadside unit selection for NOMA-enabled V2X communications: Ergodic rate performance. IEEE Access, 8, 140348–140360.

    Google Scholar 

  21. Vaezi, M., Zhiguo, D., & Vincent Poor, H. (Eds.). (2019). Multiple access techniques for 5G wireless networks and beyond. Berlin, Germany: Springer.

    Google Scholar 

  22. Chen, C., Wang, B., & Zhang, R. (2018). Interference hypergraph-based resource allocation (IHG-RA) for NOMA-integrated V2X networks. IEEE Internet of Things Journal, 6(1), 161–170.

    Google Scholar 

  23. Tang, Z., & Jianhua, H. (2020). NOMA enhanced 5G distributed vehicle to vehicle communication for connected autonomous vehicles. In Proceedings of the ACM MobiArch 2020 The 15th Workshop on Mobility in the Evolving Internet Architecture.

  24. Duarte, L., et al. (2019). A software-defined radio for future wireless communication systems at 60 GHz. Electronics, 8(12), 1490.

    Google Scholar 

  25. Mitola, J. (1992). Software radios-survey, critical evaluation and future directions. In IEEE National Telesystems Conference (pp. 13/15–13/23).

  26. SDR Forum Version 2.0. (2020). Wireless Innovation Forum, Available: http://www.wirelessinnovation.org/.

  27. Yuan, Y., Zhifeng, Y., & Li, T. (2020). 5G non-orthogonal multiple access study in 3GPP. IEEE Communications Magazine, 58(7), 90–96.

    Google Scholar 

  28. Zhu, L., et al. (2019). Millimeter-wave communications with non-orthogonal multiple access for B5G/6G. IEEE Access, 7, 116123–116132.

    Google Scholar 

  29. Fu, S., et al. (2019). Joint transmission scheduling and power allocation in non- orthogonal multiple access. IEEE Transactions on Communications, 67(11), 8137–8150.

    Google Scholar 

  30. Zhai, D., et al. (2019). Delay minimization for massive Internet of Things with non-orthogonal multiple access. IEEE Journal of Selected Topics in Signal Processing, 13(3), 553–566.

    Google Scholar 

  31. Yang, G., Xinyue, X., & Ying-Chang, L. (2020). Intelligent reflecting surface assisted non-orthogonal multiple access. In 2020 IEEE wireless communications and networking conference (WCNC), IEEE.

  32. Do, D.-T., & Van Nguyen, M.-S. (2019). Device-to-device transmission modes in NOMA network with and without Wireless Power Transfer. Computer Communications, 139, 67–77.

    Google Scholar 

  33. Li, Z., & Braun, T. (2017). Passively track WiFi users with an enhanced particle filter using power-based ranging. IEEE Transactions on Wireless Communications, 16(11), 7305–7318.

    Google Scholar 

  34. Rempe, D., et al. (2017). A cognitive radio TV prototype for effective TV spectrum sharing. In 2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), IEEE.

  35. Karra, K., Kuzdeba, S., & Petersen, J. (2017). Modulation recognition using hierarchical deep neural networks. In 2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), IEEE.

  36. Su, Y., et al. (2017). Implementation of a cross-layer sensing medium-access control scheme. Sensors, 17(4), 816.

    Google Scholar 

  37. Park, Y., et al. (2017). Enabling sensor network to smartphone interaction using software radios. ACM Transactions on Sensor Networks, 13(1), 2.

    Google Scholar 

  38. Pham, T. H., Fahmy, S. A., & McLoughlin, I. V. (2017). An end-to- end multi-standard OFDM transceiver architecture using FPGA partial reconfiguration. IEEE Access, 5, 21002–21015.

    Google Scholar 

  39. He, D., Chan, S., & Guizani, M. (2017). Drone-assisted public safety networks: The security aspect. IEEE Communications Magazine, 55(8), 218–223.

    Google Scholar 

  40. Kocian, A., et al. (2017). A unified message-passing algorithm for MIMO–SDMA in software-defined radio. EURASIP Journal on Wireless Communications and Networking, 1, 4.

    Google Scholar 

  41. Cai, H., et al. (2018). A software-defined radio for wireless brain implants network. In Proceedings of the 24th annual international conference on mobile computing and networking, ACM.

  42. Kunze, S., Weinberger, A., & Poeschl, R., (2018). Concept for a software defined radio based system for detection, classification and analysis of radio signals from civilian unmanned aerial systems. In 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC) (pp. 1–4), Meloneras.

  43. Sadhu, B., Paidimarri, A., Ferriss, M., Yeck, M., Gu, X., & Valdes-Garcia, A., (2018). A SoftwareDefined phased array radio with mmWave to software vertical stack integration for 5G experimentation. In: 2018 IEEE/MTT-S international microwave symposium—IMS (pp. 1323–1326) Philadelphia, PA.

  44. Li, K., et al. (2018). Security mechanisms to defend against new attacks on software-defined radio. In 2018 international conference on computing, networking and communications (ICNC) (pp. 537–541) Maui, HI.

  45. El-Darymli, K., Hansen, N., Dawe, B., Gill, E. W., & Huang, W. (2018). Design and implementation of a high-frequency software-defined radar for coastal ocean applications. IEEE Aerospace and Electronic Systems Magazine, 33(3), 14–21.

    Google Scholar 

  46. Reddy, B. S. K. (2018). Experimental Validation of Timing, Frequency and Phase Correction of Received Signals Using Software Defined Radio Testbed. Wireless Personal Communications, 101(4), 2085–2103.

    Google Scholar 

  47. Abdullahi, A. B, et al. (2019). Real time multiuser-MIMO beamforming/steering using NI-2922 universal software radio peripheral. In Future of information and communication conference Springer, Cham.

  48. Salam, A., Mehmet, C. V., & Irmak, S. (2019). Di-Sense: In situ real-time permittivity estimation and soil moisture sensing using wire wireless underground communications. Computer Networks, 151, 31–41.

    Google Scholar 

  49. Reddy, B. S. K. (2019). Experimental validation of spectrum sensing techniques using software-defined radio. Nanoelectronics, circuits and communication systems (pp. 97–103). Singapore: Springer.

    Google Scholar 

  50. Arfi, A. B., Jouzdani, M., Helaoui, M., & Ghannouchi, F. M. (2019). A novel high-pass delta–sigma modulator-based digital-IF transmitter with enhanced performance for SDR applications. IEEE Transactions on Circuits and Systems II: Express Briefs, 66(11), 1795–1799.

    Google Scholar 

  51. Arya, K. V., & Gore, R. (2019). Internet of Things using software-defined network and cognitive radio network. In Sensing techniques for next generation cognitive radio networks. IGI Global (pp. 312–328).

  52. Do, P. V., Hernandez, J., Lu, Z., Garcia, D. E., & Mann, S. (2020). High dynamic range (HDR) signal processing on software-defined radio. In 2020 IEEE Sensors (pp. 1–4), Rotterdam, Netherlands. https://doi.org/10.1109/SENSORS47125.2020.9278809.

  53. Ashleibta, A., et al. (2020). SoftwaredefinedradiobasedTestbedforlarge scale body movements. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2902267.

    Article  Google Scholar 

  54. Mann, S., Do, P. V., Lu, Z., & Lau, J. K. K. (2020). Sequential wave imprinting machine (SWIM) implementation using SDR (Software-Defined Radio). In 2020 seventh international conference on software defined systems (SDS) (pp. 123–130), Paris, France. https://doi.org/10.1109/SDS49854.2020.9143940.

  55. Wu, P., Sun, B., Su, S., Wei, J., Zhao, J., & Wen, X. (2020). Automatic modulation classification based on deep learning for software-defined radio. Mathematical Problems in Engineering, 2020(2678310), 13. https://doi.org/10.1155/2020/2678310.

    Article  Google Scholar 

  56. Verdecia-Pena, R., & Alonso, J. I. (2020). An enhanced Software Defined Radio Platform for evaluation of Decode & Forward Relay Nodes. In URSI2020. Accepted.

  57. de Rugeles, J. J., Guillen, E. P., & Cardoso, L. S. (2020). A technical review of wireless security for the Internet of Things: Software defined radio perspective. arXiv preprint arXiv:2009.10171.

  58. Bargarai, F., et al. (2020). Management of wireless communication systems using artificial intelligence-based software defined radio. (pp 107–133).

  59. Carvalho, D., Aragão, A. J., Ferrari, A., Sanches, B., & Noije, W., (2020). Software-defined radio assessment for microwave imaging breast cancer detection. In 2020 IEEE Nordic circuits and systems conference (NorCAS) (pp. 1–6), Oslo, Norway. https://doi.org/10.1109/NorCAS51424.2020.9265007.

  60. Mohammadali, M., et al. (2019). Full-duplex non-orthogonal multiple access for next generation wireless systems. IEEE Communications Magazine, 57(5), 110–116.

    Google Scholar 

  61. Alavi, F., et al. (2019). Robust energy-efficient design for MISO non-orthogonal multiple access systems. IEEE Transactions on Communications, 67(11), 7937–7949.

    Google Scholar 

  62. Vaezi, M., Schober, R., Ding, Z., & Poor, H. V. (2019). Non-orthogonal multiple access: Common myths and critical questions. IEEE Wireless Communications, 26(5), 174–180. https://doi.org/10.1109/MWC.2019.1800598.

    Article  Google Scholar 

  63. Gui, G., Sari, H., & Biglieri, E. (2019). A new definition of fairness for non-orthogonal multiple access. IEEE Communications Letters, 23(7), 1267–1271. https://doi.org/10.1109/LCOMM.2019.2916398.

    Article  Google Scholar 

  64. Liu, Y., Qin, Z., Cai, Y., Gao, Y., Li, G. Y., & Nallanathan, A. (2019). UAV communications based on non-orthogonal multiple access. IEEE Wireless Communications, 26(1), 52–57. https://doi.org/10.1109/MWC.2018.1800196.

    Article  Google Scholar 

  65. Yan, X., et al. (2019). The application of power-domain non-orthogonal multiple access in satellite communication networks. IEEE Access, 7, 63531–63539. https://doi.org/10.1109/ACCESS.2019.2917060.

    Article  Google Scholar 

  66. Stoica, R., De Abreu, G. T. F., Hara, T., & Ishibashi, K. (2019). Massively concurrent non-orthogonal multiple access for 5G networks and beyond. IEEE Access, 7, 82080–82100. https://doi.org/10.1109/ACCESS.2019.2923646.

    Article  Google Scholar 

  67. Yi, W., Liu, Y., Nallanathan, A., & Elkashlan, M. (2019). Clustered millimeter-wave networks with non-orthogonal multiple access. IEEE Transactions on Communications, 67(6), 4350–4364. https://doi.org/10.1109/TCOMM.2019.2897632.

    Article  Google Scholar 

  68. Tuan, H. D., Nasir, A. A., Nguyen, H. H., Duong, T. Q., & Poor, H. V. (2019). Non-orthogonal multiple access with improper gaussian signaling. IEEE Journal of Selected Topics in Signal Processing, 13(3), 496–507. https://doi.org/10.1109/JSTSP.2019.2901993.

    Article  Google Scholar 

  69. He, Q., Hu, Y., & Schmeink, A. (2019). Closed-form symbol error rate expressions for non-orthogonal multiple access systems. IEEE Transactions on Vehicular Technology, 68(7), 6775–6789. https://doi.org/10.1109/TVT.2019.2917579.

    Article  Google Scholar 

  70. Reddy, B. S. K. (2020). Experimental validation of non-orthogonal multiple access (NOMA) technique using software defined radio. Wireless Personal Communications, 115(3), 1–14.

    Google Scholar 

  71. New, W. K., Leow, C. Y., Navaie, K., & Ding, Z. (2020). Robust non-orthogonal multiple access for aerial and ground users. IEEE Transactions on Wireless Communications, 19(7), 4793–4805. https://doi.org/10.1109/TWC.2020.2987315.

    Article  Google Scholar 

  72. Kara, F. (2020). Wireless powered cooperative relaying systems with non-orthogonal multiple access. arXiv preprint arXiv:2009.13973.

  73. Khorov, E., Kureev, A., Levitsky, I., & Akyildiz, I. F. (2020). Prototyping and experimental study of non-orthogonal multiple access in Wi-Fi networks. IEEE Network, 34(4), 210–217. https://doi.org/10.1109/MNET.011.1900498.

    Article  Google Scholar 

  74. Granada, I., Crespo, P. M., & Garcia-Frías, J. (2020). Rate compatible modulation for non-orthogonal multiple access. IEEE Access, 8, 224246–224259. https://doi.org/10.1109/ACCESS.2020.3043529.

    Article  Google Scholar 

  75. Yue, X., Liu, Y., Yao, Y., Li, X., Liu, R., & Nallanathan, A. (2020). Secure communications in a unified non-orthogonal multiple access framework. IEEE Transactions on Wireless Communications, 19(3), 2163–2178. https://doi.org/10.1109/TWC.2019.2963181.

    Article  Google Scholar 

  76. Nguyen, H. V., et al. (2020). A survey on non-orthogonal multiple access: From the perspective of spectral efficiency and energy efficiency. Energies, 13(16), 4106.

    Google Scholar 

  77. Jain, M., et al. (2020). Performance analysis of NOMA assisted mobile ad hoc networks for sustainable future radio access. IEEE Transactions on Sustainable Computing. https://doi.org/10.1109/TSUSC.2020.2987427.

    Article  Google Scholar 

  78. Saito, Y., Benjebbour, A., Kishiyama, Y., & Nakamura, T. (2013). System level performance evaluation of downlink non-orthogonal multiple access (NOMA). In IEEE PIMRC 2013.

  79. Ali, U., et al. (2020). Performance analysis of discrete wavelet transform for downlink non-orthogonal multiple access in 5G networks. IET Communications, 14(10), 1666–1674.

    Google Scholar 

  80. Chen, X., et al. (2015). Consideration on successive interference canceller (SIC) receiver at cell-edge users for non-orthogonal multiple access (NOMA) with SUMIMO. In 2015 IEEE 26th annual international symposium on personal, indoor, and mobile radio communications (PIMRC), IEEE.

  81. Li, P.-R., Ding, Z., & Feng, K.-T. (2019). Enhanced receiver based on FEC code constraints for uplink NOMA with imperfect CSI. IEEE Transactions on Wireless Communications, 18(10), 4790–4802.

    Google Scholar 

  82. Cheng, J., et al. (2020). Power allocation and receiver design for D2D assisted cooperative relaying downlink systems using NOMA. IEEE Access, 8, 210663.

    Google Scholar 

  83. Tezuka, H., et al. (2020). Link-level Performance Evaluation of an ULNOMA system with TDD constructed by hardware. In 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), IEEE.

  84. Saito, S., et al. (2019). Performance analysis of OAM-MIMO using SIC in the presence of misalignment of beam axis. In 2019 IEEE international conference on communications workshops (ICC Workshops), IEEE.

  85. Surendra Raju, M., Ramesh, A., & Chockalingam, A. (2003). BER analysis of QAM with transmit diversity in Rayleigh fading channels. In ÂT IEEE Globecom (pp. 641–645).

  86. Durmaz, M. A., et al. (2019). Non-orthogonal multiple access system implementation in software defined radios. In 2019 27th signal processing and communications applications conference (SIU), IEEE.

  87. Castro, O. E. L. (2020). Network GPRS prototype based on SDR and OpenBTS, as an IoT-lab Testbed. In 2020 seventh international conference on software defined systems (SDS), IEEE.

  88. Gawłowicz, P., Zubow, A., & Bayhan, S. (2020). Demo abstract: Cross-technology communication between LTE-U/LAA and WiFi. In IEEE INFOCOM 2020-IEEE conference on computer communications workshops (INFOCOM WKSHPS), IEEE.

  89. OpenAirInterface.org. [Online]. (2020). Available: http://www.openairinterface.org/.

  90. Kaltenberger, F., et al. (2020). OpenAirInterface: Democratizinginnovation in the 5G Era. Computer Networks, 176, 107284.

    Google Scholar 

  91. Dreibholz, T. (2020). Flexible 4g/5g testbed setup for mobile edge computing using openairinterface and open source mano. In Workshops of the international conference on advanced information networking and applications. Springer, Cham.

  92. Abeywickrama, S., et al. (2020). Intelligent reflecting surface: Practical phase shift model and beamforming optimization. arXiv preprint arXiv:2002.10112.

  93. Wang, H., & Fapojuwo, A. O. (2019). Design and performance evaluation of successive interference cancellation-based pure ALOHA for Internet-of-Things networks. IEEE Internet of Things Journal, 6(4), 6578–6592.

    Google Scholar 

  94. Orlandić, M., Fjeldtvedt, J., & Johansen, T. A. (2019). A parallel FPGA implementation of the CCSDS-123 compression algorithm. Remote Sensing, 11(6), 673.

    Google Scholar 

  95. Dai, J., et al. (2019). Optimisation design of systematic fountain codes on fading channels. IET Communications, 13(20), 3369–3376.

    Google Scholar 

  96. Raza, W., Nasir, H., & Javaid, N. (2020). Unification of RF energy harvesting schemes under mixed Rayleigh–Rician fading channels. AEU- International Journal of Electronics and Communications, 123, 153244.

    Google Scholar 

  97. Reddy, B. S. K. (2020). Experimental validation of non-orthogonal multiple access (NOMA) technique using software defined radio. Wireless Personal Communications, 116, 1–14.

    Google Scholar 

  98. Reddy, B. S. K. (2019). Experimentalvalidationoftiming,frequencyand phase correction of received signals using software defined radio Testbed. Wireless Personal Communications, 101(4), 2085–2103.

    Google Scholar 

  99. Özdogan, Ö., Björnson, E., & Larsson, E. G. (2019). Massive MIMO with spatially correlated Rician fading channels. IEEE Transactions on Communications, 67(5), 3234–3250.

    Google Scholar 

Download references

Funding

No funding was used for this manuscript.

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, CMR Engineering College, Hyderabad, Telangana, 501401, India

    Bathula Siva Kumar Reddy

  2. Department of ECE, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, 500090, India

    Kiran Mannem & K. Jamal

Authors
  1. Bathula Siva Kumar Reddy
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Kiran Mannem
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. K. Jamal
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

In our contribution, the power domain NOMA with two users’ data using software defined radio (SDR) with the help of GNU Radio is implemented and analyzed. To the best of authors’ knowledge, most of the survey papers presented about NOMA and SDR separately, however, this paper presents a detailed survey about the implementation of NOMA techniques on SDR platform and the major challenges required to implement NOMA. The OMA and NOMA systems are analyzed in terms of rate pairs, energy efficiency, spectral efficiency, channel gains and bit error rate. Moreover, the major research works done during 2017 to 2020 is presented in brief detail and references also provided for further analysis.

Corresponding author

Correspondence to Bathula Siva Kumar Reddy.

Ethics declarations

Conflict of interest

All authors declare that they have no conflict of interest.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Reddy, B.S.K., Mannem, K. & Jamal, K. Software Defined Radio Based Non-orthogonal Multiple Access (NOMA) Systems. Wireless Pers Commun 119, 1251–1273 (2021). https://doi.org/10.1007/s11277-021-08260-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08260-2

Keywords