Energy-Efficient Hybrid Analog and Digital Precoding for mmWave MIMO Systems with Large Antenna Arrays (1507.04592v1)

Abstract: Millimeter wave (mmWave) MIMO will likely use hybrid analog and digital precoding, which uses a small number of RF chains to avoid energy consumption associated with mixed signal components like analog-to-digital components not to mention baseband processing complexity. However, most hybrid precoding techniques consider a fully-connected architecture requiring a large number of phase shifters, which is also energyintensive. In this paper, we focus on the more energy-efficient hybrid precoding with sub-connected architecture, and propose a successive interference cancelation (SIC)-based hybrid precoding with near-optimal performance and low complexity. Inspired by the idea of SIC for multi-user signal detection, we first propose to decompose the total achievable rate optimization problem with non-convex constraints into a series of simple sub-rate optimization problems, each of which only considers one sub-antenna array. Then, we prove that maximizing the achievable sub-rate of each sub-antenna array is equivalent to simply seeking a precoding vector sufficiently close (in terms of Euclidean distance) to the unconstrained optimal solution. Finally, we propose a low-complexity algorithm to realize SICbased hybrid precoding, which can avoid the need for the singular value decomposition (SVD) and matrix inversion. Complexity evaluation shows that the complexity of SIC-based hybrid precoding is only about 10% as complex as that of the recently proposed spatially sparse precoding in typical mmWave MIMO systems. Simulation results verify the near-optimal performance of SIC-based hybrid precoding.

• The paper decomposes the complex total rate optimization into sub-rate problems for each sub-antenna array using a SIC-based approach.
• The paper demonstrates that optimizing the precoding vector via Euclidean distance minimization achieves near-optimal performance with only about 10% of the complexity.
• The paper highlights energy efficiency and reduced hardware demands in mmWave MIMO systems, indicating practical benefits for next-generation 5G applications.

Energy-Efficient Hybrid Analog and Digital Precoding for mmWave MIMO Systems with Large Antenna Arrays

The paper, "Energy-Efficient Hybrid Analog and Digital Precoding for mmWave MIMO Systems with Large Antenna Arrays," outlines advancements in hybrid precoding techniques aimed at enhancing the energy efficiency in millimeter wave (mmWave) MIMO systems. Given the exponentially increasing demand for higher spectral efficiency in next-generation 5G systems, mmWave MIMO, which leverages wide bandwidth and compact high-frequency antenna arrays, is a pivotal technology. However, the high energy consumption and hardware complexity intrinsic to current hybrid precoding techniques necessitate innovative solutions, such as the one proposed in this research.

Problem Statement

The research identifies the challenge in existing hybrid precoding methods, especially those employing a fully-connected architecture. This architecture demands a substantial number of energy-intensive RF chains and phase shifters, rendering it less practical in terms of energy efficiency. The paper pivots towards a sub-connected architecture to address these issues, while also recognizing the complexities introduced by this architectural shift.

Proposed Solution

The cornerstone of this research is the development of a successive interference cancelation (SIC)-based hybrid precoding technique within a sub-connected architecture. The proposed methodology decomposes the total achievable rate optimization problem into simpler sub-rate optimization problems. The authors draw a parallel to SIC used in multi-user signal detection, demonstrating that optimizing the sub-rate for each sub-antenna array can be simplified to finding a precoding vector close to the unconstrained optimal solution based on Euclidean distance.

Key Contributions

1. Decomposition Approach: The total rate optimization problem with non-convex constraints is deconstructed into manageable sub-rate optimization problems for each sub-antenna array.
2. Optimization Equivalence: It's proven that maximizing each sub-rate can be achieved by locating a precoding vector minimal in Euclidean distance to the optimal unconstrained solution.
3. Algorithm Development: The authors propose a low-complexity algorithm to realize SIC-based hybrid precoding, eliminating the need for complex operations like singular value decomposition and matrix inversion.

Computational Complexity

A notable highlight is the rigorous complexity evaluation, positioning the SIC-based hybrid precoding as only approximately 10% as complex as the spatially sparse precoding prevalent in extant literature. This significant reduction in complexity is attributed to the avoidance of SVD and matrix inversion, achieved through the use of the power iteration algorithm accelerated by Aitken’s method. This nuanced approach reduces the computational overhead substantially, making it more feasible for practical implementation.

Simulation and Results

The simulation results are compelling, indicating near-optimal performance of the SIC-based hybrid precoding. Specifically, it achieves about 99% of the rate compared to the unconstrained optimal solution in sub-connected architectures and surpasses traditional analog precoding methods. Furthermore, the SIC-based technique's performance remains competitive with spatially sparse precoding under fully-connected architectures but with considerably lower power and phase shifter requirements. The potential for scaling performance through the addition of more antennas rather than increasing RF chains suggests a favorable trade-off in terms of energy consumption versus performance enhancement.

Implications and Future Work

The practical implications of this research extend beyond mere theoretical interest. The SIC-based hybrid precoding opens pathways for more energy-efficient mmWave MIMO systems, crucial for the deployment of future 5G networks. Additionally, the reduced complexity and energy requirements make this approach more adaptable and scalable. Future research directions highlighted by the authors encompass extending the hybrid precoding method to broadband systems and addressing the limited feedback scenario, which involves imperfect channel state information and phase shifter quantization.

Conclusion

In conclusion, this paper makes a significant contribution to the field of energy-efficient wireless communications by proposing a novel SIC-based hybrid precoding technique for mmWave MIMO systems within a sub-connected architecture. The approach mitigates the energy and complexity constraints inherent in fully-connected hybrid precoding methods. This work not only enhances spectral efficiency and performance but also sets a foundation for future enhancements and practical deployment in 5G and beyond.