Hybrid Precoder Design for Millimeter Wave Massive MU-MIMO Systems with Low-Resolution Phase Shifters

Hybrid precoding schemes have recently gained a great attention for millimeter wave (mmWave) massive multiple-input-multiple-output (massive MIMO) communication systems because of offered cost and low-power consumption advantages. The singular value decomposition (SVD) method which is exploited in the design of hybrid precoding causes several problems on system design, especially on bit allocation, precoding and equalizing processes. On the other hand, the previous works show that generalized triangular decomposition (GTD) method can present asymptotically optimal performance in conventional MIMO systems. In the light of this, we propose the use of GTD method for designing hybrid precoding operating in mmWave massive MIMO systems. The proposed design is analyzed via performed simulation studies including different system configurations. Moreover, the archived results are compared with the standard orthogonal matching pursuit (OMP) algorithm based hybrid precoding scheme. The simulation results show that the proposed hybrid precoding scheme can reach up to the performance of optimal precoding scheme.

Millimeter wave (mmWave) communications have been regarded as a key technology for the next generation cellular systems since the huge available bandwidth can potentially provide the rates of multiple gigabits per second. In mmWave multiple-input multiple-output (MIMO) systems, the conventional precoding is infeasible due to the hardware cost and power consumption. Therefore, hybrid precoding is considered as a promising technology to provide a compromise between hardware complexity and system performance. In this paper, we investigate the designs of the hybrid precoder and combiner in mmWave MIMO systems. We adopt the hierarchical strategy to design a hybrid precoder to maximize the spectral efficiency. In particular, we focus on the optimization of analog precoder and propose a novel iterative algorithm. Then, based on the optimal analog precoder, we compute the digital precoder to improve the spectral efficiency. For practical implementation, the proposed hybrid precoder design can be used in wideband systems with orthogonal frequency division multiplexing modulation. The simulation results and mathematical analysis show that the proposed algorithm can achieve near-optimal performance with low complexity for mmWave MIMO systems.

This paper investigates hybrid precoding for millimeter-wave (mmWave) multi-group multicasting systems with the consideration of max-min fairness. We formulate it as the optimization problem of maximizing the minimum signal-to-interference-plus-noise ratio among all users subject to a total transmit power constraint and constant modulus constraints. The problem is nonconvex and hard to solve due mainly to the nonlinear coupling of the digital precoder and the analog precoders. By resorting to the recently proposed penalty dual decomposition (PDD) method, the max-min hybrid precoding problem reduces to repeatedly solving four subproblems, each of which admits simple solution. Numerical results validate the effectiveness of the proposed max-min fairness hybrid precoding algorithm.

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.

Hybrid precoding has been recognized as a promising technology for millimeter wave-based massive MIMO systems. As an improved scheme for conventional hybrid precoding structures, the adaptively-connected structure requires low hardware cost and has attractive system performance. In this paper, we propose an adaptive hybrid precoding (AHP) scheme for multi-user massive MIMO systems. The hybrid precoder design is formulated as minimizing the difference between the hybrid precoder and the full digital precoder, and a rough design and revision based AHP (RDR-AHP) algorithm is developed to seek for a near-optimal solution. The proposed RDR-AHP algorithm is achieved by a three-step process including rough design of baseband precoder based on singular value unification, stepwise design of radio frequency precoder and baseband precoder revision. Simulation results demonstrate that the proposed scheme achieves higher spectral efficiency than existing schemes with same hardware cost in millimeter wave channel.

Large-scale antenna arrays which provide high beamforming gain are commonly used to combat the serious path-loss in millimeter wave (mmwave) systems. Traditionally, the beamforming is completely implemented at the baseband or the digital domain, which, however, causes high hardware cost and power consumption. The hybrid precoding method which can effectively avoids these problems is, therefore, more attractive. However, the design of hybrid precoder is challenging due to the constant modules of phase shifters. To solve this problem, we propose a novel hybrid precoding approach from the perspective of geometric construction in this paper. The new method can significantly reduce the number of RF chains meanwhile still achieve an almost optimal performance in terms of sum rate. The proposed algorithm is compared with the popular orthogonal matching pursuit algorithm (OMP) via numerical simulations, and shows that our proposal can increase the system spectral efficiency with reduced computational complexity.

Developing novel channel estimation and hybrid precoding in millimeter-wave communication system using heuristic-based deep learning

In this letter, we propose a hybrid analog–digital precoder design to enhance the physical layer security of millimeter-wave (mmWave) multiple-input single-output (MISO) systems with partial channel knowledge. We derive a closed-form expression for the average signal-to-interference-and-noise ratio (SINR) of the eavesdropper (Eve) as a function of the hybrid precoder. Using the average SINRs of Eves, we derive a secrecy rate lower bound. Then, we propose a low-complexity artificial-noise-aided (AN-aided) hybrid precoder design to maximize the secrecy rate lower bound. Numerical results show that the proposed AN-aided hybrid precoder achieves comparable performance to that of the fully digital precoder, with much lower hardware complexity. Moreover, the proposed AN-aided hybrid precoder outperforms the existing hybrid precoder design. Effect of finite-resolution phase shifters on the proposed precoder is also investigated.

This paper investigates the hybrid precoding design for millimeter wave multiple-input multiple-output systems with finite-alphabet inputs. The precoding problem is a joint optimization of analog and digital precoders, and we treat it as a matrix factorization problem with power and constant modulus constraints. This paper presents three main contributions. First, we present a sufficient condition and a necessary condition for hybrid precoding schemes to realize unconstrained optimal precoders exactly when the number of data streams N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> satisfies N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> = min{rank(H), N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rf</sub> }, where H represents the channel matrix and N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rf</sub> is the number of radio frequency chains. Second, we show that the coupled power constraint in our matrix factorization problem can be removed without loss of optimality. Third, we propose a Broyden-Fletcher-Goldfarb-Shanno-based algorithm to solve our matrix factorization problem using gradient and Hessian information. Several numerical results are provided to show that our proposed algorithm outperforms existing hybrid precoding algorithms.

The mmWave cell-free massive MIMO (CFmMIMO), combining the advantages of wide bandwidth in the mmWave frequency band and the high- and uniform-spectral efficiency of CFmMIMO, has recently emerged as one of the enabling technologies for 6G. In this paper, we propose a novel framework for energy-efficient mmWave CFmMIMO systems that uses low-resolution digital–analog converters (DACs) and phase shifters (PSs) to introduce lowcomplexity hybrid precoding. Additionally, we propose a heuristic pilot allocation scheme that makes the best effort to slash some interference from copilot users. The simulation results show that the proposed hybrid precoding and pilot allocation scheme outperforms the existing schemes. Furthermore, we reveal the relationship between the energy and spectral efficiencies for the proposed mmWave CFmMIMO system by modeling the whole network power consumption and observe that the introduction of low-resolution DACs and PSs is effective in increasing the energy efficiency by compromising the spectral efficiency and the network power consumption.

Economical and energy-efficient analog/digital hybrid beamforming has been widely considered as a promising approach for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. While most hybrid beamforming techniques consider a fully-connected structure with a large number of phase shifters (PSs), the partially-connected structure has drawn more attention recently since it requires much less PSs and can further improve energy-efficiency. However, the impractical assumption of infinite or high resolution of PSs in existing solutions frustrates the real-world deployment of hybrid beamforming designs, and low- resolution PSs are typically adopted to reduce the hardware complexity and power consumption. In an effort to achieve maximum hardware efficiency, this paper focuses on the partially-connected architecture with one-bit (binary) PSs and considers the problem of joint hybrid precoder and combiner design for such mmWave MIMO systems. We propose to successively design the analog beamformers associated with each pair of sub- array, aiming at conditionally maximizing the spectral efficiency. A novel binary analog precoder and combiner optimization algorithm is proposed under a rank-1 approximation of the interference-included equivalent channel with polynomial complexity in the number of antennas. Then, the digital precoder and combiner are computed based on the obtained effective baseband channel to further enhance the spectral efficiency. Simulation results demonstrate the advantages of proposed hardware-efficiency hybrid precoder and combiner design.

In this paper, we delve into the maximized spectral efficiency (SE) of millimeter-wave (mmWave) multicell multiuser massive MIMO Systems for uplink transmission with low-resolution phase shifters (LRPSs). Millimeter-wave massive multiple-input multiple-output (mMIMO) is an important technology for upcoming cellular networks which will provide higher bandwidth and throughput than current wireless systems and networks. LRPSs are commonly used to minimize power consumption, maximize spectral efficiency and diminish the complexity of hybrid precoder and combiner. In this paper, we consider a hybrid analog-digital precoder and combiner design with LRPSs for mmWave multi-cell multiuser mMIMO systems for uplink transmission to spectral efficiency in terms of iterations. The proposed technique outperforms when compared to traditional optimization approaches concerning spectral efficiency and bit error rate (BER). We show through simulation results that our designs with LRPSs outperform standard iteration procedures.

The hybrid precoding technique targeted at reducing the number of RF chains without obvious performance loss becomes a promising candidate in 5G communication. In this paper, an energy efficient hybrid precoding is proposed for the mmWave MIMO systems, in which phase modulation array (PMA) based analog precoding is adopted instead of phase shifters to reduce the power consumption and improve the energy efficiency. Specifically, PMA, consisting of delay lines and switches, enables to control phase and amplitude simultaneously, thus imposes additional constraint on the analog precoding. On this basis, the hybrid precoding problem is formulated for the PMA-based mmWave systems. Furthermore, an enhanced orthogonal constraint algorithm and an alternating optimization algorithm are proposed for the full-connected and sub-connected hybrid precoders, respectively. In addition, a more realistic situation, that there exists a minimum switch-on duration when the RF switch turns on, is considered for the proposed PMA-based hybrid precoder. Finally, simulation results have verified that, the PMA-based precoding can achieve higher spectral efficiency and energy efficiency when compared with the phase shifters based counterparts. More importantly, the proposed PMA-based hybrid precoder can significantly reduce the number of radio frequency chains, resulting in low energy consumption for its application in 5G green communication.

When wireless transmission is performed over the bandwidth in the order of a gigahertz, high-resolution analog-to-digital converters (ADCs), and the large number of radio frequency chains significantly increase the power consumption. To address this issue, one promising technique is to use low-resolution, even one-bit ADCs. Another promising technique is to apply a hybrid precoding architecture to reduce the number of RF chains. In this paper, we propose to combine those techniques to reduce the hardware costs in multi-input multi-output system. Our objective is to optimize the hybrid precoder with the aim of increasing the achievable rate. To this end, we first derive an expression for the achievable rate in flat fading channels based on the Bussgang theorem, which is able to reformulate the nonlinear quantitative process as a linear function with identical first- and second-order statistics. To solve the non-convex hybrid precoding design problem, we treat the hybrid precoding design as a matrix factorization problem, which can be solved with an efficient alternating minimization algorithm. That is, we solve the digital precoder and the analog precoder in an alternative way in two separate subproblems. To find the optimal precoder in the first subproblem, we first prove the optimal structure of the digital precoding matrix. With it, we transfer the digital precoding design to a power allocation problem, the closed-form solution of which is then optimally found by using Karush–Kuhn–Tucker conditions. In the second subproblem, due to the non-convex modulus-norm constraint, it is challenging to directly solve the analog precoder. To resolve this problem, we propose to optimize the phases in the analog precoding matrix and adopt the subgradient algorithm to find the local optimal solution. Our simulation results show that the proposed hybrid precoding design effectively improves the achievable rates.

In Millimetre Wave (mmWave) Multiple-Inputs Multiple-Output (MIMO) systems, hybrid precoders are introduced the reduced number of Radio Frequency (RF) chains. In the existing hybrid precoder using Phase Shifter (PS) network consume high energy, the cost of hardware and the performance loss in the system is high. In this paper, Adaptive Cross-Entropy (ACE) based Kalman Hybrid Precoder for the frequency selective mmWave MIMO channel in time domain approach is proposed. ACE based kalman hybrid precoder is designed and develops for Switch and Inverter (SI) based architecture. In addition, Kalman based digital precoder is develop and compare with MMSE digital precoder. Simulation results show the ACE based kalman hybrid precoding for SI architecture is provide the low energy consumption, and higher Spectral Efficiency (SE) compares to the existing Two-Stage (TS) hybrid precoder, Antenna Selection (AS) and Cross-Entropy (CE) based hybrid precoders.