Hybrid Analog and Digital Beamforming for mmWave OFDM Large-Scale Antenna Arrays (1711.08408v1)

Abstract: Hybrid analog and digital beamforming is a promising candidate for large-scale mmWave MIMO systems because of its ability to significantly reduce the hardware complexity of the conventional fully-digital beamforming schemes while being capable of approaching the performance of fully-digital schemes. Most of the prior work on hybrid beamforming considers narrowband channels. However, broadband systems such as mmWave systems are frequency-selective. In broadband systems, it is desirable to design common analog beamformer for the entire band while employing different digital beamformers in different frequency sub-bands. This paper considers hybrid beamforming design for systems with OFDM modulation. First, for a SU-MIMO system where the hybrid beamforming architecture is employed at both transmitter and receiver, we show that hybrid beamforming with a small number of RF chains can asymptotically approach the performance of fully-digital beamforming for a sufficiently large number of transceiver antennas due to the sparse nature of the mmWave channels. For systems with a practical number of antennas, we then propose a unified heuristic design for two different hybrid beamforming structures, the fully-connected and the partially-connected structures, to maximize the overall spectral efficiency of a mmWave MIMO system. Numerical results are provided to show that the proposed algorithm outperforms the existing hybrid beamforming methods and for the fully-connected architecture the proposed algorithm can achieve spectral efficiency very close to that of the optimal fully-digital beamforming but with much fewer RF chains. Second, for the MU-MISO case, we propose a heuristic hybrid percoding design to maximize the weighted sum rate in the downlink and show numerically that the proposed algorithm with practical number of RF chains can already approach the performance of fully-digital beamforming.

• The paper demonstrates that hybrid beamforming can closely approximate fully-digital performance in large-scale antenna arrays by leveraging mmWave channel sparsity.
• A novel heuristic algorithm is developed for fully- and partially-connected architectures to maximize spectral efficiency under practical RF constraints.
• The study addresses multiuser downlink optimization in OFDM channels, achieving high throughput with fewer RF chains and reduced power consumption.

Hybrid Analog and Digital Beamforming for mmWave OFDM Large-Scale Antenna Arrays

The paper Hybrid Analog and Digital Beamforming for mmWave OFDM Large-Scale Antenna Arrays by Foad Sohrabi and Wei Yu explores advanced beamforming strategies for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, especially focusing on hybrid analog and digital beamforming. Such systems are indicative of future wireless communications technologies, as they attempt to balance between the hardware complexity associated with fully-digital beamforming schemes and the potential advantages of employing large-scale antenna arrays.

Key Contributions

The paper provides a novel perspective on employing hybrid beamforming for frequency-selective channels, primarily within single-user (SU) MIMO and multiuser (MU) MISO systems. Recognizing the inadequacies and impracticalities of fully-digital strategies due to excessive power consumption and hardware complexity, the authors propose an innovative hybrid framework that operates close to the limits set by its fully-digital counterparts.

1. Asymptotic Analysis: The paper explores an asymptotic analysis indicating that hybrid beamforming can achieve optimal fully-digital beamforming performance when the number of antennas becomes very large. This analysis utilizes the sparsity characteristic of mmWave channels, providing insights into the covariance matrices across different subcarriers.
2. Algorithm Development: A heuristic algorithm is developed for hybrid beamforming, applicable to fully-connected and partially-connected architecture setups. It strides to maximize the spectral efficiency under practical antenna considerations, where the introduction of a frequency-selective hybrid beamforming design suggests significant promises in managing broad channels like OFDM systems.
3. Multiuser Downlink Scenario: A significant challenge that the paper addresses for mmWave systems is the downlink weighted sum rate maximization under per-subcarrier power constraints. This is managed through a coordinated design of the analog precoder by catering to the entire band of frequency-selective channels, driving home the hybrid structures’ impactful resource allocation capability.

Numerical Insights

Through extensive simulations, the paper convincingly demonstrates the proposed methods' potential efficacy. In a pragmatic scenario setups -- where RF chains are considerably lesser than the antennas -- it exhibits near-optimal throughput efficiencies. Such performance parallels those of fully-digital beamforming paradigms without the associated costs.

The results show that in a typical mmWave setting, employing the hybrid beamforming design, especially under fully-connected configuration, realized spectral efficiency very close to the theoretical maximum dictated by fully-digital designs. Decisively, the proposed strategy for handling various real-world considerations like low-resolution phase shifters affirms its comprehensive utility.

Implications and Future Directions

The implications of this research are manifold. Practically, the paper emphasizes crucial design considerations emerging from the hybrid beamforming domain, paving the way for less complicated yet highly efficient MIMO deployments. This focus manifests particularly in broadband OFDM systems where spectral efficiency and power constraints are consistent considerations.

From a theoretical perspective, the results open discussions on the potential reformulation of classic beamforming strategies across complex MIMO channels, including investigating architectures beyond the limitations of conventional RF constraints. Moreover, as networks continue to evolve towards 5G and beyond, understanding how hybrid approaches can be implemented under different hardware constraints with machine learning-based optimizations could serve as a rich avenue for further exploration.

In summarizing, this paper constitutes a pivotal step forward in wireless communication technologies, emphasizing the critical balance between complexity, cost, and efficiency, thereby fostering the evolution of mmWave systems into practical, high-performance deployments across diverse environments.