Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally? (1507.05994v1)

Abstract: Massive MIMO can greatly increase both spectral and transmit-energy efficiency. This is achieved by allowing the number of antennas and RF chains to grow very large. However, the challenges include high system complexity and hardware energy consumption. Here we investigate the possibilities to reduce the required number of RF chains, by performing antenna selection. While this approach is not a very effective strategy for theoretical independent Rayleigh fading channels, a substantial reduction in the number of RF chains can be achieved for real massive MIMO channels, without significant performance loss. We evaluate antenna selection performance on measured channels at 2.6 GHz, using a linear and a cylindrical array, both having 128 elements. Sum-rate maximization is used as the criterion for antenna selection. A selection scheme based on convex optimization is nearly optimal and used as a benchmark. The achieved sum-rate is compared with that of a very simple scheme that selects the antennas with the highest received power. The power-based scheme gives performance close to the convex optimization scheme, for the measured channels. This observation indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF chains and performing antenna selection using simple algorithms.

• The paper demonstrates that antenna selection in massive MIMO systems nearly matches optimal sum-rate performance while reducing hardware complexity.
• Experimental results using linear and cylindrical arrays reveal that convex optimization significantly outperforms random selection in varied channel conditions.
• The findings suggest that adaptive antenna deployment can enhance energy efficiency and simplify system design for 5G and future networks.

Insightful Overview of "Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?"

The paper "Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?" presents a detailed investigation into the performance and contributions of antennas in massive MIMO systems within real-world propagation environments. The authors examine the heterogeneity of antenna contributions and explore whether reducing the number of active RF chains through antenna selection could maintain system performance while reducing complexity and energy consumption.

Key Contributions and Numerical Results

1. Challenge Addressed: The complexity and hardware energy consumption of implementing a large number of antennas in massive MIMO systems is significant. The paper explores antenna selection as a potential solution, hypothesizing that not all antennas contribute equally in real-world environments.
2. Methodology: The authors conducted experiments using two measured channel setups at 2.6 GHz: a 128-element linear array and a cylindrical array. They compared theoretical performance in ideal i.i.d. Rayleigh fading channels against performance in real-world measured channels, using sum-rate maximization as the criterion for selecting antennas.
3. Results:
   • Antenna selection based on convex optimization approaches near-optimal sum-rate performance.
   • Antenna selection can achieve a significant reduction in the number of RF chains needed (up to more than half), with minimal performance loss.
   • The convex optimization-based scheme drastically improves the DPC capacity and ZF sum-rate compared to random selection in measured channels.
   • A simple power-based selection scheme also demonstrated competitive results, particularly in environments where user channels are less correlated (e.g., NLOS scenarios).
4. Impact of User Configuration and Channel Conditions: The paper highlighted varying performance benefits based on user proximity and propagation conditions (LOS vs. NLOS). In scenarios with well-separated users and NLOS conditions, the benefits of adaptive antenna selection were more pronounced.

Implications and Speculation on Future Developments

The implications of this research are twofold:

• Practical Implications: By demonstrating that a significant number of RF transceivers can be turned off with negligible performance loss, the paper suggests a path forward in reducing the implementation complexity and energy consumption in massive MIMO systems. This is crucial for feasible deployment in future communications networks, including 5G and beyond.
• Theoretical Implications: The findings underline the necessity of developing improved channel models that better reflect real-world propagation environments, as existing i.i.d. Rayleigh models do not capture the full range of antenna contributions observed in practice.

Looking forward, the results encourage further exploration into intelligent and adaptive antenna deployment strategies that optimize both energy efficiency and spectral efficiency. Additionally, future research could investigate the combination of antenna selection with other techniques, such as dynamic beamforming and user scheduling, to further enhance system performance in complex and dynamic environments.

The paper provides a solid foundation for these discussions and reiterates the importance of experimental validation of theoretical models in the evolution of massive MIMO technology.