Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3616390.3618284acmconferencesArticle/Chapter ViewAbstractPublication PagesmobicomConference Proceedingsconference-collections
research-article

Spatial User Clustering and Power Control for Downlink MIMO-NOMA Systems

Published: 30 October 2023 Publication History

Abstract

The proliferation of Internet of Things (IoT) devices and the attractive underlying market has motivated the integration of IoT into the fifth generation (5G) of wireless communication. As the number of connected devices continues to increase, wireless communication networks are facing challenges in terms of throughput and massive connectivity. To tackle these challenges, this paper investigates the utilization of Massive Multi-Input Multi-Output (mMIMO) over millimeter-wave (mmWave) frequency bands as well as Non-Orthogonal Multiple Access (NOMA), which is considered a key technology enabling multiple users to share the same frequency/time/code resource. Specifically, it is performed to separate users served through the same beam in IoT scenarios where the number of active users exceeds the number of Radio Frequency (RF) chains at the Base Station (BS). By incorporating NOMA on top of MIMO, the system's spectral efficiency can be increased due to the introduction of additional degrees of freedom. We propose two joint user clustering and power control algorithms to address the aforementioned challenges. The proposed algorithms take into account the spatial channel correlation between users to maximize the number of allocated users while considering their Quality of Service (QoS) requirements. Extensive simulations illustrate that the proposed techniques improve the efficiency of wireless resource utilization, especially when there is a large set of active users and a limited number of RF chains.

References

[1]
3GPP. 2020. 5G; NR; Physical layer procedures for data. Technical Specification (TS) 38.214. 3rd Generation Partnership Project (3GPP). https://www.etsi.org/deliver/ etsi_ts/138200_138299/138214/16.02.00_60/ts_138214v160200p.pdf Version 16.2.0.
[2]
Jeffrey G. Andrews, Stefano Buzzi, Wan Choi, Stephen V. Hanly, Angel Lozano, Anthony C. K. Soong, and Jianzhong Charlie Zhang. 2014. What Will 5G Be? IEEE Journal on Selected Areas in Communications 32, 6 (2014), 1065--1082. https: //doi.org/10.1109/JSAC.2014.2328098
[3]
Zahid Aslam, Yoann Corre, Emil Björnson, and Erik Larsson. 2019. Performance of a dense urban massive MIMO network from a simulated ray-based channel. EURASIP Journal on Wireless Communications and Networking 2019 (05 2019). https://doi.org/10.1186/s13638-019--1425--1
[4]
Victor Boutin, Hakim Mellah, ConstantWetté, and Brunilde Sansò. 2021. Simulating Large-Scale 5G Networks. In 2021 IEEE 4th 5G World Forum (5GWF). 293--298. https://doi.org/10.1109/5GWF52925.2021.00058
[5]
Abbas Dehghani Firouzabadi, Hakim Mellah, Orestes Manzanilla-Salazar, Reza Khalvandi, Vincent Therrien, Victor Boutin, and Brunilde Sansò. 2023. PIoT:APerformance IoT Simulation System for a Large-Scale City-Wide Assessment. IEEE Access 11 (2023), 56273--56286. https://doi.org/10.1109/ACCESS.2023.3282729
[6]
Xiang Gao, Ove Edfors, Fredrik Rusek, and Fredrik Tufvesson. 2015. Massive MIMO Performance Evaluation Based on Measured Propagation Data. IEEE Transactions on Wireless Communications 14, 7 (2015), 3899--3911. https://doi. org/10.1109/TWC.2015.2414413
[7]
Pekka Kyösti, Mar Francis De Guzman, Katsuyuki Haneda, Nuutti Tervo, and Aarno Pärssinen. 2022. How Many Beams Does Sub-THz Channel Support? IEEE Antennas and Wireless Propagation Letters 21, 1 (2022), 74--78. https://doi.org/10. 1109/LAWP.2021.3118464
[8]
Gilwon Lee and Youngchul Sung. 2018. A New Approach to User Scheduling in Massive Multi-User MIMO Broadcast Channels. IEEE Transactions on Communications 66, 4 (2018), 1481--1495. https://doi.org/10.1109/TCOMM.2017.2786670
[9]
Filippo Malandra, Hakim Mellah, Abbas Dehghani Firouzabadi, Constant Wetté, and Brunilde Sansò. 2023. A Layered and Grid-Based Methodology to Characterize and Simulate IoT Traffic on Advanced Cellular Networks. IEEE Internet of Things Magazine 6, 1 (2023), 134--140. https://doi.org/10.1109/IOTM.001.2200156
[10]
Thomas L. Marzetta. 2010. Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas. IEEE Transactions on Wireless Communications 9, 11 (2010), 3590--3600. https://doi.org/10.1109/TWC.2010.092810.091092
[11]
Xiaoxu Meng, Yongyu Chang, Yafeng Wang, and Jingzhou Wu. 2018. Multi-user Grouping Based Scheduling Algorithm in Massive MIMO Uplink Networks. In 2018 IEEE 4th International Conference on Computer and Communications (ICCC). 409--413. https://doi.org/10.1109/CompComm.2018.8780961
[12]
Zhanyuan Xie and Wei Chen. 2020. Pilot-Efficient Scheduling for Large-Scale Antenna Aided Massive Machine-Type Communications: A Cross-Layer Approach. IEEE Transactions on Communications 68, 7 (2020), 4262--4276. https: //doi.org/10.1109/TCOMM.2020.2987889
[13]
Siming Zhang, Angela Doufexi, and Andrew Nix. 2016. Evaluating realistic performance gains of massive multi-user MIMO system in urban city deployments. In 2016 23rd International Conference on Telecommunications (ICT). 1--6. https://doi.org/10.1109/ICT.2016.7500454

Index Terms

  1. Spatial User Clustering and Power Control for Downlink MIMO-NOMA Systems

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      MobiWac '23: Proceedings of the Int'l ACM Symposium on Mobility Management and Wireless Access
      October 2023
      142 pages
      ISBN:9798400703676
      DOI:10.1145/3616390
      Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 30 October 2023

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. keywords{non-orthogonal multiple access
      2. massive connectivity
      3. massive multiple-input multiple-output
      4. power control}
      5. user clustering

      Qualifiers

      • Research-article

      Funding Sources

      • ANR

      Conference

      MSWiM '23
      Sponsor:

      Acceptance Rates

      Overall Acceptance Rate 83 of 272 submissions, 31%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • 0
        Total Citations
      • 43
        Total Downloads
      • Downloads (Last 12 months)43
      • Downloads (Last 6 weeks)1
      Reflects downloads up to 02 Sep 2024

      Other Metrics

      Citations

      View Options

      Get Access

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media