Proposed Hybrid Precoding Algorithm Research Articles

Hybrid precoding design for MmWave multi‐user massive MIMO systems under high mobility

AbstractStudying hybrid precoding in a high mobility scenario is challenging task. Because the channel changes quickly with time and becomes double selective fading in the spatial domain. As a result, there is a difficulty to achieve perfect channel state information or estimate the channel under high mobility. In this paper, an applicable hybrid precoding based on amplitude and phase excitation beams for millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems is proposed under high speed railway. The proposed hybrid precoding uses the data from the locations of the mobile stations to build the amplitude and phase beam matrix. The proposed precoders and decoders are designed to maximize the mobile service. An optimization problem of mobile service maximization is formulated for designing hybrid precoders and decoders. To solve the optimization problem, a heuristic technique under power constraint is provided. The proposed hybrid precoding algorithm is compared with analog only beam steering algorithm, partially connected hybrid precoding algorithm and fully connected hybrid precoding algorithm. Results illustrated that the proposed precoding scheme outperforms the other precoding algorithms and handover success probability is enhanced under high mobility.

Channel Estimation and Hybrid Precoding for Distributed Phased Arrays Based MIMO Wireless Communications

Distributed phased arrays based multiple-input multiple-output (DPA-MIMO) is a newly introduced architecture that enables both spatial multiplexing and beamforming while facilitating highly reconfigurable hardware implementation in millimeter-wave (mmWave) frequency bands. With a DPA-MIMO system, we focus on channel state information (CSI) acquisition and hybrid precoding. As benefited from a coordinated and open-loop pilot beam pattern design, all the sub-arrays can perform channel sounding with less training overhead compared with the traditional orthogonal operation of each sub-array. Furthermore, two sparse channel recovery algorithms, known as joint orthogonal matching pursuit (JOMP) and joint sparse Bayesian learning with $\ell_2$ reweighting (JSBL-$\ell_2$), are proposed to exploit the hidden structured sparsity in the beam-domain channel vector. Finally, successive interference cancellation (SIC) based hybrid precoding through sub-array grouping is illustrated for the DPA-MIMO system, which decomposes the joint sub-array RF beamformer design into an interactive per-sub-array-group handle. Simulation results show that the proposed two channel estimators fully take advantage of the partial coupling characteristic of DPA-MIMO channels to perform channel recovery, and the proposed hybrid precoding algorithm is suitable for such array-of-sub-arrays architecture with satisfactory performance and low complexity.

A Spectral Efficient Hybrid Precoding Algorithm for MmWave MIMO Systems

Abstract Millimeter-wave MIMO will use hybrid precoding to improve the spectral efficiency. In this paper, we propose a spectral efficient hybrid precoding algorithm. In order to maximize the projection of hybrid precoding matrix on the optimal precoding matrix, we design the analog precoding matrix by selecting an optimal combination from the candidate matrix. Then, we regard the channel matrix and the obtained analog precoding matrix as an equivalent channel matrix, and use regularized zero-forcing to acquire the digital precoding matrix. Finally, we present simulation results of the proposed hybrid precoding algorithm and show that the algorithm approaches the optimal precoding.

Hybrid Precoding Processor for Millimeter Wave MIMO Communications

Millimeter wave (mmWave) multiple-input multiple-output system is one of the most important techniques to increase throughput for 5G communications. To overcome the severe pathloss in the mmWave channel, the hybrid analog/digital precoding technique jointly designs radio frequency (RF) beamforming vectors and a baseband precoding matrix to approach the optimal spectral efficiency with reduced RF chain power and baseband complexity. This brief presents a hybrid precoding algorithm based on multiple orthogonal beamforming codebooks and a local search scheme, which reduces computational complexity by 40% with negligible bit-error-rate performance loss compared with the state-of-the-art algorithms. The proposed hybrid precoding algorithm was also designed and implemented by using TSMC 90-nm CMOS process technology. The fabricated hybrid precoding processor chip achieves 11.1M/10.4M/6.9M/4.3M matrices per second for 1/2/3/4 data streams, respectively. Compared with a previous work, the designed processor increases throughput by 65%/55%/40%/7.5% for 1/2/3/4 data streams with only 28% of the core area.

Doubling Phase Shifters for Efficient Hybrid Precoder Design in Millimeter-Wave Communication Systems

Hybrid precoding is a cost-effective approach to support directional transmissions for millimeter-wave (mmWave) communications, but its precoder design is highly complicated. In this paper, we propose a new hybrid precoder implementation, namely the double phase shifter (DPS) implementation, which enables highly tractable hybrid precoder design. Efficient algorithms are then developed for two popular hybrid precoder structures, i.e., the fully- and partially-connected structures. For the fully-connected one, the RF-only pre-coding and hybrid precoding problems are formulated as a least absolute shrinkage and selection operator problem and a low-rank matrix approximation problem, respectively. In this way, computationally efficient algorithms are provided to approach the performance of the fully digital one with a small number of radio frequency (RF) chains. On the other hand, the hybrid precoder design in the partially-connected structure is identified as an eigenvalue problem. To enhance the performance of this cost-effective structure, dynamic mapping from RF chains to antennas is further proposed, for which a greedy algorithm and a modified K-means algorithm are developed. Simulation results demonstrate the performance gains of the proposed hybrid precoding algorithms over existing ones. It shows that, with the proposed DPS implementation, the fully-connected structure enjoys both satisfactory performance and low design complexity while the partially-connected one serves as an economic solution with low hardware complexity.

Energy-Efficient Hybrid Precoding With Low Complexity for mmWave Massive MIMO Systems

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) utilizes large antenna arrays and is considered a promising technology for fifth-generation (5G) and beyond wireless communication systems. However, the high-power consumption of the radio-frequency (RF) chains makes it infeasible. To solve this problem, hybrid precoding is proposed, which is a combination of analog and digital precoding. The fully connected architecture hybrid precoding still requires a large number of phase shifters (PSs). The sub-connected architecture can greatly reduce the required power consumption, and however, it cannot obtain a satisfactory achievable rate. To avoid the high energy consumption and obtain a high resolution, we propose a novel partly connected architecture in this paper. In addition, we propose an energy-efficient successive interference cancelation (SIC) hybrid precoding based on the partly connected architecture, which transforms the problem of maximizing the total achievable rate with non-convex constraints into a series of sub-rate optimization problems. Furthermore, a low-complexity energy-efficient SIC hybrid precoding based on the partly connected architecture is developed, which uses the partial singular value decomposition (SVD) to realize the sub-rate optimization and significantly reduce the complexity. Theoretical analysis demonstrates the superiority of the proposed hybrid precoding in terms of complexity. The simulation results indicate that the proposed hybrid precoding algorithms enjoy better energy efficiency and achievable rate performance than some recently proposed hybrid precoding algorithms.

Joint Design of Analog and Digital Codebooks for Hybrid Precoding in Millimeter Wave Massive MIMO Systems

Hybrid precoding has been regarded as a promising technology for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems due to the low hardware cost and power consumption. This paper focuses on digital and analog codebooks design to efficiently quantize the hybrid precoders with arbitrary-resolution analog phase shifters in frequency-division duplex systems. We formulate the codebooks design as a joint optimization problem and propose an iteration algorithm to obtain the enhanced codebooks based on dictionary learning methods. Moreover, this paper shows that the optimal precoders for all data streams exhibit a hidden joint sparsity structure caused by the limited number of scattering clusters with low angular spreads of mmWave MIMO channels. Exploiting the structure, a jointly sparse precoding is proposed as the pursuit method for the proposed codebooks design algorithm. The simulation results demonstrate that the near-optimal performance can be achieved by the joint utilization of the proposed hybrid precoding algorithm and codebooks even when the low-resolution phase shifters are used.

Hybrid RF-Baseband Precoding for Cooperative Multiuser Massive MIMO Systems With Limited RF Chains

Massive multiple-input multiple-output (massive MIMO) has been studied to improve the throughput in cellular communication systems via spatial degrees of freedom and array gain. However, in massive MIMO systems, due to the hardware cost considerations, it is infeasible to install a radio frequency (RF) chain for each antenna. To deploy massive MIMO within reasonable hardware cost, hybrid precoding is proposed in which the signal is processed by a low-dimensional digital baseband precoder and a high-dimensional analog RF precoder. On the other hand, cooperative transmission is another way to enhance system throughput, in which base stations (BSs) can jointly transmit to a user. In this paper, we first investigate the hybrid precoder design for cooperative multiuser massive MIMO systems. We propose hybrid precoding algorithms for two performance metrics: weighted sum rate and max-min fairness. We also propose a low complexity user pairing for both precoder designs. Numerical results show that the proposed hybrid precoding algorithms outperform existing hybrid precoding algorithms for non-cooperative transmissions, and perform closely compared with existing digital precoding algorithms for cooperative transmissions, when the number of users does not exceed the total number of RF chains of the BSs in cooperative (i.e., the largest possible channel rank). In summary, this paper provides a hybrid precoder design guideline for existing and developing cellular communication systems, including Long Term Evolution-Advanced and the fifth generation cellular systems.