Communication Systems Based on Distributed MIMO and “Cell-Free” Massive MIMO
| Valérian Mannoni, research director at CNRS Laboratory of Signals and Systems CentraleSupélec, Université Paris-Saclay Project PERSEUS Director Valerian.MANNONI@cea.fr |
Wireless communication networks are rapidly evolving with the advent of 5G and ongoing research on 6G. In response to the increasing demand for capacity, coverage, and reliability, significant advancements have been made in multi-antenna architectures known as MIMO (Multiple-Input Multiple-Output). This technology simultaneously leverages the spatial, temporal, and frequency dimensions of signals, thereby enhancing spectral efficiency, transmission robustness, and quality of service for users. Among these advancements, distributed MIMO stands out by geographically distributing antennas to improve coverage and reduce interference. More recently, the concept of Cell-Free Massive MIMO has emerged, eliminating the traditional cellular structure in favor of global cooperation among all antennas to uniformly serve all users in a given area, regardless of their position.
Distributed MIMO: Definition and Key Principles. Distributed Multiple-Input Multiple-Output (D-MIMO) relies on spatially dispersed antennas that collaborate to transmit and receive signals. Unlike centralized MIMO, where all antennas are grouped at a single site, D-MIMO deploys antennas over a large area, all connected to a Central Unit (CU). This macro spatial diversity improves radio coverage by reducing white zones, optimizes intra-cell interference management, and enhances spectral capacity through more efficient spatial multiplexing. Additionally, this approach boosts communication robustness against fading phenomena. Its flexibility makes it adaptable to both small cell networks and large-scale deployments, from industrial environments to dense urban cellular networks with challenging propagation conditions.
Cell-Free Massive MIMO: Eliminating the Concept of Cells. Cell-Free Massive MIMO extends the distributed MIMO concept by eliminating the notion of cells altogether. Numerous access points (APs) are distributed within the coverage area, each equipped with a few antennas and connected to a central processing unit (CU) through high-capacity fronthaul links (fiber optics, coaxial cables, or wireless links). Cell-Free is a direct evolution of D-MIMO, aiming to enhance cooperation and ensure service fairness. The Cell-Free Massive MIMO (CF-mMIMO) approach provides homogeneous coverage with equitable service even at the edges, eliminates the need for handovers, and drastically reduces interference through joint radio resource management. The redundancy of antennas also improves network reliability and the capacity to handle a large number of simultaneous users. However, these gains require sophisticated algorithms for coordination and interference cancellation, as well as strict synchronization (time, frequency, and phase) between access points. A key differentiation from D-MIMO lies in the complete absence of cell management and the use of full centralized synchronization.
Practical Applications and Use Cases. D-MIMO and CF-mMIMO technologies have significant potential in various domains:
- 5G+ and 6G Networks: Significant improvement in capacity and coverage, particularly in dense urban environments. Large-scale CF-mMIMO deployment across an entire territory is unlikely.
- Factories of the Future and the Internet of Things (IoT): Optimized signal propagation in complex environments with metallic obstacles, enabling robust, low-latency, and highly reliable communications for real-time industrial process control and massive sensor management.
- Autonomous Vehicles: Optimized V2X (Vehicle-to-Everything) communications for better coordination and safety of connected vehicles.
- High-Density User Events: Optimization of ultra-broadband connections to ensure stable and efficient connections during concerts, sports events, or large-scale conferences.
Technical Challenges and Limitations. Despite the potential of distributed MIMO and Cell-Free systems, several technical challenges remain, some of which are addressed in the PEPR NF-PERSEUS project. These challenges notably involve antenna coordination, which requires advanced precoding and interference cancellation algorithms, as well as rigorous time, frequency, and phase synchronization to prevent performance degradation. Channel estimation management is crucial since imprecise estimation can lead to inter-user interference. Moreover, the energy consumption resulting from the large number of active antennas necessitates advanced optimization strategies, such as the dynamic deactivation of certain antennas during low-load periods. The backhaul infrastructure must also be adequately scaled to handle massive data flows, requiring high-capacity and low-latency links.
Promising approaches are emerging, particularly the use of reconfigurable intelligent surfaces (RIS). These passive surfaces dynamically modify the propagation of radio waves, thereby reducing energy requirements and improving link quality without the need for additional active antennas. RIS could complement D-MIMO and CF-mMIMO architectures by facilitating interference management and improving coverage. However, their integration with these systems still requires extensive research to ensure sustainable and cost-effective performance gains.
Conclusion. Distributed MIMO and Cell-Free Massive MIMO represent significant advancements in wireless network evolution, offering promising solutions to meet the growing demands for capacity, coverage, and reliability, particularly in high-density scenarios. While technical challenges remain substantial, research projects such as PEPR NF-PERSEUS and the integration of technologies like RIS suggest a future where these architectures will play a central role in 6G networks and beyond.
| References [1] Xiaohu You, Dongming Wang, Jiangzhou Wang, “Distributed MIMO and Cell-Free Mobile Communication,” Springer, 2020. [2] J. Zhang, S. Chen, Y. Lin, J. Zheng, B. Ai and L. Hanzo, “Cell-Free Massive MIMO: A New Next-Generation Paradigm,” in IEEE Access, vol. 7, pp. 99878-99888, 2019. [3] Obakhena, H.I., Imoize, A.L., Anyasi, F.I. et al., “Application of cell-free massive MIMO in 5G and beyond 5G wireless networks: a survey, ” J. Eng. Appl. Sci. 68, 13 (2021). [4] Kassam, J.; Castanheira, D.; Silva, A.; Dinis, R.; Gameiro, A., “A Review on Cell-Free Massive MIMO Systems, ” Electronics 2023, 12, 1001 [5] Huo, Y., Lin, X., Di, B., Zhang, H., Hernando, F. J. L., Tan, A. S., Mumtaz, S., Demir, Ö. T., & Chen-Hu, K., “Technology Trends for Massive MIMO towards 6G. Sensors, ” 2023 Basel (Switzerland), 23(13), 6062. [6] E. Bjornson, L. Van der Perre, S. Buzzi and E. G. Larsson, “Massive MIMO in Sub-6 GHz and mmWave: Physical, Practical, and Use-Case Differences,” in IEEE Wireless Communications, vol. 26, no. 2, pp. 100-108, April 2019. [7] Charbel Abdel Nour, Cédric Adjih, Karine Amis, Xavier Begaud, Matthieu Crussière, et al., “Deliverable D1 – Technical Report NF-PERSEUS 2023, ” CEA – Commissariat à l’énergie atomique et aux énergies alternatives. 2024, pp.1-86. ⟨cea-04564147⟩ |
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