Performance analysis of insertion loss incorporated hybrid precoding for massive MIMO

In this letter, we study the performance of a downlink multiuser massive multiple-input multiple-output (MIMO) system with sub-connected structure over limited feedback channels. Tight rate approximations are theoretically analyzed for the system with pure analog precoding and hybrid precoding. The effect of quantized analog and digital precoding is characterized in the derived expressions. Furthermore, it is revealed that the pure analog precoding outperforms the hybrid precoding using maximal-ratio transmission (MRT) or zero forcing (ZF) under certain conditions, and we theoretically characterize the conditions in closed form with respect to signal-to-noise ratio (SNR), the number of users and the number of feedback bits. Numerical results verify the derived conclusions on both Rayleigh channels and mmWave channels.

Hybrid precoding design can be challenging for broadband millimeter-wave (mmWave) massive MIMO due to the frequency-flat analog precoder in radio frequency (RF). Prior broadband hybrid precoding work usually focuses on fully-connected array (FCA), while seldom considers the energy-efficient partially-connected subarray (PCS) including the fixed subarray (FS) and dynamic subarray (DS). Against this background, this paper proposes a machine learning based broadband hybrid precoding for mmWave massive MIMO with DS. Specifically, we first propose an optimal hybrid precoder based on principal component analysis (PCA) for the FS, whereby the frequency-flat RF precoder for each subarray is extracted from the principle component of the optimal frequency-selective precoders for fully-digital MIMO. Moreover, we extend the PCA-based hybrid precoding to DS, where a shared agglomerative hierarchical clustering (AHC) algorithm developed from machine learning is proposed to group the DS for improved spectral efficiency (SE). Finally, we investigate the energy efficiency (EE) of the proposed scheme for both passive and active antennas. Simulations have confirmed that the proposed scheme outperforms conventional schemes in both SE and EE.

The performance of the hybrid beamforming system based on the full-connected structure is close to that of the full-digital one in millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. However, due to the high complexity of circuit wiring in practical applications, it has been greatly restricted. This paper investigates the hybrid (analog/digital) beamforming design of a multiuser mmWave massive MIMO system with sub-connected structure. For this system, we focus on a sum-rate maximization probelm. Considering the joint design of the receiver, and transmitter, a two-stage design method is adopted. In the analog stage, the analog beamformer, and combiner are designed by the proposed piecewise dual joint iterative approximation (PDJIA) method, which not only can obtain closed-form solutions but also has linear property. Based on the criterion of avoiding the loss of information, the problem of digital beamforming is solved by exploiting the baseband piecewise successive approximation (BPSA) method, which can effectively increase the number of users served. Simulation results show that the proposed scheme outperforms the state-of-the art MIMO hybrid beamforming design schemes, and more accurately approximates to that of the full-digital system.

SummaryMillimeter wave communication and massive MIMO technology are important ingredients for the future generation communication system. In this context, hybrid precoding (HP) is one of the most promising solutions, and it becomes utterly important in the case of the multi‐user scenario. In this paper, authors have analyzed the performance of the lattice reduction aided fully connected structured precoder for millimeter wave massive MIMO under multi‐user scenario. This paper deals with Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms for the lattice reduction (LR). And the presented results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE)‐based linear precoder with LLL algorithm‐based reduction‐based ZF (LLR‐ZF), LLR‐MMSE, KZ‐ZF, KZ‐MMSE, and Kalman filter‐based precoder. Here, the performance of the precoders has been evaluated based on spectral efficiency, energy efficiency diversity order, and bit error rate. This work conveys some important findings: (i) effectiveness of the lattice reduction aided precoder in multi‐user scenario; (ii) numerical results pointed out that at low SNR condition, KZ‐aided MMSE hybrid precoder provides 4‐dB performance than a Kalman filter‐based precoder; (iii) KZ‐MMSE hybrid precoder outperforms the other precoder.

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.

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.

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.

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.

Massive Multiple-Input Multiple-Output (MIMO) is an extension of the conventional MIMO in the wireless systems which improves both of the access density and the spectral efficiency by adding a massive number of antenna array at the base station (BS). Massive MIMO increases the spectral efficiency by using the beamforming. Besides, the beamforming in massive MIMO improves the energy efficiency by focusing the energy in the desired direction instead of the omnidirectional propagation. In this paper, we propose and discuss different beamforming objectives in both the uplink and the downlink channels. These proposed objectives can be either use the beamforming of the desired signal without nulling the interference or use the beamforming with interference nulling. The beamforming with nulling objectives have better performance than those without nulling but this leads to a higher computational complexity as well. The results of this paper show and compare the performance of these objective including the spectral efficiency and energy efficiency as well as the computational complexity. Index Terms— Beamforming, Interefernce nulling, Energy efficiency, Massive MIMO, Spectral efficiency.

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.

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.

Massive multiple-input multiple-output (massive MIMO) and the millimeter wave (mmWave) communication are known to be among the key technologies for the fifth generation (5G) mobile networks. The implementation of massive MIMO with the mmWave architecture requires the utilization of hybrid precoding technique with a low dimensional digital precoder and a high dimensional analog precoder. In this paper, we investigate the hybrid precoding design problem for the case of cooperative multicell multiuser massive MIMO system. This problem is formulated with the consideration of the user and base station (BS) association problem, and we propose an iterative algorithm to solve the formulated problem. The precoding problem is solved using the Eigen precoding algorithm whereas the Lagrangian based approach is proposed for the solution of the association problem. Simulation results show that our proposed solution can achieve higher energy efficiency and convergence rate.

The concept of generalized spatial modulation (GenSM) aided millimeter wave (mm-wave) multiple-input multiple-output (MIMO) has recently attracted substantial research interest, as it benefits from the large bandwidth of mm-wave MIMO, while maintaining a reduced number of radio frequency (RF) chains. However, due to the lack of precoding design, the preceding GenSM-aided mm-wave MIMO schemes suffered from severe performance loss. Inspired by the reduced-RF-chain structure making implementation cost low while maintaining the benefit of GenSM, in this paper, we incorporate the technique of hybrid precoding into GenSM-aided mm-wave MIMO, where a hybrid digital and analog precoding regime is proposed to enhance the system's achievable rate. Moreover, a closed-form expression is proposed to provide an accurate approximation to the spectral efficiency (SE) achieved by the proposed scheme. The proposed expression is further simplified in the region of high signal-to-noise ratio (SNR). By exploiting the proposed SE expressions as low-complexity cost functions, two algorithms, i.e. the gradient ascent algorithm and the high-SNR approximation algorithm, are exploited to optimize the hybrid precoders in terms of SE maximization. Finally, numerical simulations are provided to substantiate the superior SE performance achieved by the proposed scheme over other GenSM-aided mm-wave MIMO schemes as well as the state-of-the-art mm-wave MIMO systems.

International audience

SummaryThe hybrid precoding problem is considered a Frobenius norm reduction problem for the narrowband channel in a millimeter wave (mmWave) with multiple inputs and outputs (mmWave MIMO). This work proposes a hybrid distributed online and alternating convex optimization (HDO‐ACO) algorithm to improve hybrid precoding (HP), interpreted as a trace minimization problem. HDO‐ACO alternately determines the digital and analog precoders to reduce the trace by keeping the other constant. Initially, HDO‐ACO uses Lagrange's method to determine the digital precoding subproblem. Then, it uses the integrated distributed online convex optimization and alternating minimization algorithm in the analog precoder design. In the HP method, the digital and analog precoders are iteratively updated until the highest number of iterations or convergence is reached. But this hybrid precoding method requires an initial analog precoding matrix input to begin the iteration. The algorithms converge gradually and fall into a suboptimal solution when the initial analog precoding matrix is set randomly. Hence, an initial value acceleration‐based heuristic approach is used in the HDO‐ACO alternating minimization algorithm that calculates the initial feasible value of an alternating minimization method using channel conditions. The simulation results of the proposed HDO‐ACO algorithm are presented under bit error rate (BER), spectral efficiency (SE), and convergence behavior by comparing it with modified block coordinate descent–HP (MBCD‐HP), manifold optimization–alternating minimization (MO‐AltMin), and semi‐definite relaxation‐based alternating optimization (SDR‐AO). The proposed HDO‐ACO attains maximum SE and less BER than other hyper‐precoding designs.