Precoding Scheme Research Articles

Cross-Layer Optimization for Industrial Internet of Things in NOMA-Based C-RANs

This article investigates nonorthogonal multiple access (NOMA)-based cloud radio access networks (C-RANs), where edge caching is adopted to cut down the crowdedness of the fronthaul links. We aim to maximize the energy efficiency (EE) by jointly optimizing the power allocation, analog, and digital precoding, which turns out to be an intractable nonconvex optimization problem. To tackle this problem, we first select cluster heads using the selecting cluster-head (SCH) algorithm, where the analog precoding matrix can be resolved by means of maximizing the array gains. Then, the device grouping algorithm is proposed to group devices according to the equivalent channel correlations, and thus, the NOMA devices in the same beam are capable of sharing the same digital precoding vector. Finally, the joint digital precoding design and power allocation algorithm is proposed to decompose the resultant optimization problem into two subproblems and solve them iteratively by applying the Taylor expansion operation and the minimum mean square error (MMSE) detection. Simulation results validate that the proposed NOMA-based C-RANs with a hybrid precoding (HP) scheme can achieve higher spectral efficiency and EE than the traditional orthogonal multiple access (OMA)-based approach and two-stage HP scheme.

Precoding-enabled OFDM-ROF transmission system with self-pumping structure

Precoding-enabled orthogonal frequency division multiplexing (OFDM) is proposed in radio-over-fiber (ROF) system based on a flexible self-pumping structure. Different from the use of two lasers, one laser-driven Mach-Zehnder modulator generates multiple spectra and forms self-pumping structures by selecting signal and pump light, which can effectively reduce the system cost and eliminate the laser phase conversion noise. The signal-to-noise ratio (SNR) of OFDM-ROF fluctuates wildly induced by non-ideal frequency response of optical/electrical devices and channel fading effects, and the BER performance is severely deteriorated. Therefore, seven common channel-independent precoding techniques are used and evaluated for the OFDM-ROF systems. The analysis of the results shows that seven precoding techniques can equalize uneven SNR on data subcarriers. Meantime, constant amplitude zero autocorrelation sequence-based matrix transform (CAZACT), Zadoff-Chu matrix transform (ZCT), discrete Fourier transform (DFT) have significant advantages in reducing the peak-to-average power ratio (PAPR). When the received optical power (ROP) is −3dBm, the BERs of the system under the seven precoding schemes are all lower than the hard decision - forward error correction threshold (HD-FEC). In addition, receiver sensitivity and comb flatness gain can also be achieved by the precoded OFDM compared to the conventional OFDM.

MDL-AltMin: A Hybrid Precoding Scheme for mmWave Systems With Deep Learning and Alternate Optimization

The hybrid precoding structure composed of analog and digital precoders has received increasing attention in mmWave massive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiple-input multiple-output</i> (MIMO) systems because it can balance the energy consumption and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">spectral efficiency</i> (SE). However, it is challenging to obtain the optimal hybrid precoding scheme by joint optimization with lower computational complexity. This letter proposes a hybrid precoding scheme based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">model-driven deep learning and alternate minimization</i> (MDL-AltMin), which is implemented by alternately solving analog precoder and digital precoder. During the alternation, we design an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">analog precoding network</i> (AP-Net) to solve the phase shift network in analog precoder with the goal of maximizing SE. The digital precoder is solved by the Lagrange multiplier method. In each alternate optimization process, the criteria for convergence is to minimize the error between the hybrid precoder and the optimal fully digital precoder. The simulation results show that the SE of our proposed scheme is very close to the fully digital precoding scheme based on singular value decomposition with lower computational complexity.

A Family of Hybrid Precoding Schemes for Millimeter-Wave Massive MIMO Systems

For millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) systems, hybrid precoding/combining is a promising way to reduce hardware cost and power consumption by decreasing the number of radio-frequency (RF) chains without causing a significant spectral-efficiency loss. Most of the existing hybrid precoding schemes involve iterative searching or alternating optimization, so their computational complexity is high and they do not take advantage of parallel computing to improve the real-time performance. In this article, considering the scenarios where the number of data streams equals to the number of RF chains, we propose a family of hybrid precoding schemes by leveraging the equivalent channel and singular value decomposition for a better tradeoff between spectral efficiency and computational complexity. Simulation results with different system settings show that our proposed schemes are superior to other existing schemes in terms of system spectral efficiency.

A Distortion Nullforming Precoder in Massive MIMO Systems With Nonlinear Hardware

In this letter, we propose a novel nullforming precoding scheme to cancel the distortion from multiple-input–multiple-output (MIMO) base stations with nonlinear hardware towards victims that operate either in the same or adjacent frequency bands. The proposed precoder is based first on the design of a nullforming scheme within the same band which steers nulls towards the direction of victims. Then, its power allocation is updated to achieve per-antenna constant envelope (CE) precoding without destructing the nullforming of the desired signal. It is shown analytically that in line-of-sight channels, single-user transmission, CE precoders have the property that the radiation pattern of nonlinear distortion has the same spatial characteristics as that of the in-band desired signal. As a result, the designed nulls are towards the desired directions for both in-band and out-of-band frequencies. Finally, numerical results corroborate the effectiveness of the proposed precoder.

Interference Management Strategies for Multiuser Multicell MIMO VLC Systems

This paper investigates different precoding strategies for rate splitting multiple access (RSMA) in the downlink of multi-cell visible light communication (VLC) networks. Since classical Shannon capacity formula does not hold for VLC, we first provide a lower bound on the channel capacity for RSMA in such interfering networks. Then, we formulate a spectral efficiency maximization problem to jointly find the optimal rate-splitting and transmit precoding. Beside that, since cell-edge users suffer from additional inter-cell interference, we propose to design the precoders of different RSMA signals utilizing coordinated beamforming (CB). Subsequently, aiming to improve the performance of the CB design for RSMA, while maintain a reduced complexity, we introduce two enhanced precoding strategies for RSMA. To the best of the authors’ knowledge such a contribution has not been considered before in the open literature. It is shown in the paper that the formulated optimization problem is non-convex and a sub-optimal, yet, a low complexity solution can be obtained efficiently using semi-definite relaxation combined with successive convex approximation. Through analytical results, we illustrate the flexibility and superiority of the proposed precoding strategies for RSMA over conventional coordinated space division multiple access and non-orthogonal multiple access for different scenarios and network loads.

Statistical Channel Model and Systematic Random Linear Network Coding Based QoS Oriented and Energy Efficient UWSN Routing Protocol

Considering the significance of an energy efficient, delay tolerant and reliable communication protocol for underwater acoustic wireless sensor network (UWSN), this paper proposes a novel systematic random linear network coding (SRLNC) based transmission system examined over a robust statistical UWSN channel model. The derived statistical channel model deals with both the small-scale fading primarily caused by scattering and small wavelength changes and large-scale fading introduced due to node dislocation in the underwater acoustic medium. The proposed SRLNC transmission-based routing approach has been applied over the proposed underwater acoustic (statistical) channel model, and respective performance assessment has been conducted in terms of throughput, energy efficiency, delay and computational complexity by varying network condition parameters. The contributions such as low coefficient vector and Galois filed, low redundant message requirements, computationally efficient pre-coding scheme, iterative buffer flush and enhanced FEC based decoding make the SRLNC based routing protocol sufficiently robust to enable reliable, energy-efficient and delay resilient communication over UWSN. The proposed SRLNC based UWSN routing protocol and its efficacy over dynamic channel conditions affirm that it can be a potential solution for QoS-oriented mission critical underwater communication purposes.

Energy Efficiency Enhancement in Massive MIMO Using P-ZF Precoding Scheme with Power Control

Energy Efficiency Enhancement in Massive MIMO Using P-ZF Precoding Scheme with Power Control

Two-stage deep learning-based hybrid precoder design for very large scale massive MIMO systems

Wireless networking is approaching a new era, which necessitates new frequency ranges and novel strategies. With recent circuit growth, communications over the Terahertz (THz) band is proving to be a viable option because of the tremendous bandwidth and low cost. On the other hand, THz signals suffer from significant direction loss, necessitating the use of precoding. In this paper, Deep Learning (DL) based precoding techniques for upcoming 6G networks were examined, along with their complexities. Based on the signal-to-noise ratio (SNR) and spectral efficiency (SE), the proposed DL-based precoding scheme is compared to traditional model-based precoding schemes. The proposed DL-based precoding technique is ideal for 6G networks, according to simulation results. Furthermore, the proposed DL-based precoding technique has lower computational complexity, making it suitable for parallel processing and high-speed data transmission.

Multi-User Holographic MIMO Surfaces: Channel Modeling and Spectral Efficiency Analysis

The multi-user Holographic Multiple-Input and Multiple-Output Surface (MU-HMIMOS) paradigm, which is capable of realizing large continuous apertures with minimal power consumption, has been recently considered as an energy-efficient solution for future wireless networks, offering increased flexibility in impacting electromagnetic (EM) wave propagation according to the desired communication, localization, and sensing objectives. The tractable channel modeling in MU-HMIMOS wireless systems is one of the most critical research challenges, mainly due to the coupling effect induced by the excessively large number of closely spaced patch antennas. In this paper, we focus on this challenge for the downlink of multi-user MIMO communications and extend an EM-compliant channel model to multi-user case, which is expressed in the wavenumber domain using the Fourier plane wave approximation. Based on the presented channel model, we investigate the spectral efficiency of maximum-ratio transmission and Zero-Forcing (ZF) precoding schemes. We also introduce a novel hardware efficient ZF precoder, leveraging Neumann series (NS) expansion to replace the required matrix inversion operation, which is very hard to be computed in the conventional way due to the extremely large number of patch antennas in the envisioned MU-HMIMOS communication systems. In comparison with the conventional independent and identical Rayleigh fading channels that ignore antenna coupling effects, the proposed EM-compliant channel model captures the mutual couplings induced by the very small antenna spacing. Our extensive performance evaluation results demonstrate that our theoretical performance expressions approximate sufficiently well the simulated achievable spectral efficiency with the considered linear precoding schemes, even for the highly correlated cases, thus verifying the effectiveness and robustness of the presented analytical framework. In addition, it is verified that the proposed NS-based ZF precoder achieves similar performance to conventional ZF, while requiring lower hardware complexity, thus, providing a hardware efficient solution for practical design of MU-HMIMOS communications systems.

Massive MIMO Precoding Methods That Minimize the Variation in Average Power and Active Impedance With Channel Conditions

This article investigates the impact of precoding on the performance of massive multiple-input multiple-output (mMIMO) transmitters exhibiting nonnegligible antenna crosstalk. For this, a new metric, called the average active impedance, is introduced to quantify the extent of load modulation as a function of the antenna S-parameters and the employed precoding. The new metric is then used to investigate the load modulation under conventional precoding schemes. It is shown that these precoders yield large disparities in average-power levels across the radio frequency (RF) chains, which results in substantial performance variations with channel conditions. Based on this investigation, we propose three new precoding schemes that yield equal average-power (EP) levels across all RF chains, independent of the channel conditions. Numerical simulations and experiments conducted on an mMIMO transmitter prototype confirmed that the proposed schemes improve the transmitter’s resilience to the variation in channel conditions.

Phosphor-Free Golden Light LED Array for 5.4-Gbps Visible Light Communication Using MIMO Tomlinson-Harashima Precoding

Visible light communication (VLC) based on light-emitting diodes (LEDs) is supposed as a candidate in 6G networks because it can provide illumination and wireless communication simultaneously. As the widespread use of LEDs, the concern of light pollution and biological safety has arisen. In this paper, we propose a Si-substrate golden light LED array as a new illumination source, using high-efficacy red and yellow LEDs, which has the merits of no phosphor, no blue light, and low color temperature. Based on the golden light LED array and a 2 × 2 PIN array, a 2 × 4 high-speed multiple-input and multiple-output (MIMO) VLC system is demonstrated. Joint MIMO Tomlison-Harashima precoding (THP) scheme is first proposed and conducted for eliminating the combination of inter-symbol interference (ISI) and inter-channel interference (ICI) for carrierless amplitude and phase (CAP) modulation VLC system. Experimental results indicate that MIMO-THP performs well in interference cancellation. The Q factor is improved by 6 dB compared with conventional pure MIMO feedforward equalizer. The overall data rate exceeds 5.4 Gbit/s.

Massive MIMO Hybrid Precoding for LEO Satellite Communications With Twin-Resolution Phase Shifters and Nonlinear Power Amplifiers

The massive multiple-input multiple-output (MIMO) transmission technology has recently attracted much attention in the non-geostationary, e.g., low earth orbit (LEO) satellite communication (SATCOM) systems since it can significantly improve the energy efficiency (EE) and spectral efficiency. In this work, we develop a hybrid analog/digital precoding technique in the massive MIMO LEO SATCOM downlink, which reduces the onboard hardware complexity and power consumption. In the proposed scheme, the analog precoder is implemented via a more practical twin-resolution phase shifting (TRPS) network to make a meticulous tradeoff between the power consumption and array gain. In addition, we consider and study the impact of the distortion effect of the nonlinear power amplifiers (NPAs) in the system design. By jointly considering all the above factors, we propose an efficient algorithmic approach for the TRPS-based hybrid precoding problem with NPAs. Numerical results show the EE gains considering the nonlinear distortion and the performance superiority of the proposed TRPS-based hybrid precoding scheme over the baselines.

A Novel Precoding Technique to Reduce PAPR of UCA-OAM Systems

Orbital angular momentum (OAM) multiplexing, which improves channel capacity without requiring additional spectrum resources, is a key technology for future communication systems. However, a uniform circular array (UCA)-based OAM transmission system, which uses an inverse discrete Fourier transform and a discrete Fourier transform to realize OAM mode multiplexing and demultiplexing, has a high peak average power ratio (PAPR) problem. This letter proposes a precoding scheme based on the conjugate symmetric discrete orthogonal transform that reduces the PAPR of UCA-OAM systems with misaligned transceivers. Simulation results indicate that the proposed scheme greatly reduces the PAPR of the system without losing the bit error rate (BER) performance in misaligned transceivers.

Estimation of Channel for Millimeter-Wave Hybrid Massive MIMO Systems using Orthogonal Matching Pursuit (OMP)

In a millimeter-wave (mm-Wave) large MIMO system, hybrid precoding is a critical component for lowering radio-frequency hardware costs as compared to the traditional full-digital precoding strategy. Knowledge of channels is required for hybrid precoding. Though, estimation of the channel is problematic for the mm-Wave system because of the usage of a massive array of antenna and hybrid architecture with analog precoding. Due to the extremely directed nature of wireless propagation, wireless channels have spatial sparsity. In this paper, we exploit this spatial sparsity nature of wireless channels to develop orthogonal matching pursuit technique-based estimation of channels for hybrid millimeter-wave (mm-Wave) wireless systems. Genie (Ideal) channel estimation is also performed in which we presume that actual angle of departures (AoD) and angle of arrivals (AoA) are known to us. Finally, the simulation results reveal that suggested OMP algorithm-based channel estimation has a significant advantage over conventional approaches like least-squares channel estimation.

Spectral-efficient hybrid precoding for multi-antenna multi-user mmWave massive MIMO systems with low complexity

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems allow for a data transmission rate of gigabits per second owing to the large bandwidth available in the mmWave spectrum and the antenna gains provided by the massive MIMO system. However, hybrid precoding with high complexity and low spectral efficiency cannot address the challenge of high cost and power consumption of RF chains of multi-user systems. In this paper, we propose a low-complexity hybrid precoding scheme for downlink multi-antenna multi-user mmWave massive MIMO systems, aiming to enhance the sum spectral efficiency (SSE) performance. We first extend the dimension of the analog precoding matrix into a square matrix and find the optimal analog combiner by selecting some of the discrete Fourier transform (DFT) bases, which enhances the equivalent baseband channel matrix gain. Then, we directly aggregate the channel gain through the equal gain transmission (EGT) method to ensure the frequency efficiency performance. Finally, we propose an improved BD scheme to design the digital precoder and combiner to reduce the inter-user interference. We consider both the mmWave channel and the Rayleigh channel to evaluate the performance of the proposed algorithm. The simulation results verify that the proposed scheme enjoys near-optimal achievable sum spectrum efficiency and BER performance in both the mmWave channel and Rayleigh channel and performs even better in Rayleigh channel than in the mmWave channel.

Hybrid Precoding Based on Partial Connection for Millimeter-Wave Massive MIMO System

Aiming at poor system performance in existing partially connected hybrid precoding schemes, in this paper, we propose a partially connected hybrid precoding scheme based on alternating optimization with the auxiliary precoder. In particular, the spectral efficiency optimization problem is transformed into a sub-optimization problem under certain constraints. For each sub-optimization problem, we use the singular value decomposition method to optimize the analog precoder and digital precoder alternately, and optimal solutions are provided for both digital and analog precoders in each alternate iteration. Moreover, we design a heuristic algorithm to calculate the initial analog precoder as the starting point for alternating optimization, which speeds up the convergence speed. The simulation results show that the proposed algorithm is at least 16.2% higher than the existing two traditional partially connected algorithms at 20 dB received SNR with almost no increase in complexity.

Low-Complexity Precoding by Exploiting Spatial Sparsity in Massive MIMO Systems

A massive multi-input-multi-output (MIMO) system can bring substantial improvement in spectral and energy efficiency for wireless communication systems. The high array gain and fine spatial resolution allow the utilization of relatively simple processing at the base station, such as the near-optimal regularized zero-forcing (RZF) precoding. Nevertheless, such precoding schemes require computing the inverse and multiplication of matrices, which leads to a large burden for baseband processing when the system dimension grows large. To take full advantage of the spatial sparsity of massive MIMO channels in the finite scattering environment, we propose a virtual channel precoding strategy that directly utilizes the sparse virtual channel representation (VCR) in precoding. Furthermore, we develop a virtual channel RZF precoding algorithm based on the pre-conditioned conjugate gradient method, namely PCG-VC-RZF, which can directly use the sparse virtual channel matrix while avoiding the complex computation of the Gram matrix. The computational complexity and transmission delay are shown to be reduced tremendously by the proposed algorithm when operating in a large-dimension system. We further provide a beam selection strategy for improving the performance of the proposed approach under a complexity constraint. The simulation results verify the efficiency of the proposed precoding scheme.

Performance Evaluation of Spectral Efficiency for Uplink and Downlink Multi-Cell Massive MIMO Systems

Massive multiple-input and multiple-output (MIMO) systems have become the most persuasive technology for 5G as it increased the energy efficiency gigantically as compared to other wireless communication systems. Being the most vibrant research technology in the communication sector, this research work is based on the optimal model development of energy-efficient massive MIMO systems. The proposed model is a realistic model that augmented the spectral efficiency (SE) of massive MIMO systems where a multi-cell model scenario is considered. Channel estimation is carried out at the base stations (BSs) based on uplink (UL) transmission while the minimum mean-squared error (MMSE), Element-wise MMSE, and Least-square (LS) estimators are used for the estimation. We analyze the achievable SE of the UL based on the MMSE channel estimator with different receive combining schemes. Moreover, the downlink (DL) transmission model is also modelled with different precoding schemes by taking the same vectors used in combining schemes. The simulation results show a significant improvement in spectral efficiency by developing UL and DL transmission models and also realized that the average sum of SE per cell can be improved by optimized MMSE channel estimation, installing multiple BS antennas, and serving multiple UEs per cell. The findings of this work specify that the massive MIMO system can be developed by optimizing the channel estimation for the augmentation of SE in UL and DL transmissions. Conclusively, it can be summarized that some complex computations of MMSE channel estimators can enhance the average sum of SE per cell as per the results verified in this model.

The Improved Precoding Method in the VLC-Based Intelligent Transportation System

Visible light communication (VLC) transmission system, combined with lighting and communication, has a great application value in the field of intelligent transportation. To efficiently improve the performance of VLC-based intelligent transportation system, an improved precoding scheme is proposed and experimentally verified. Partial data-carrying subcarrier (PDS)-precoding scheme can balance the signal-to-noise ratio (SNR) and combat frequency selective fading (FSF) in the VLC-based intelligent transportation system. For ∼3.52 Gb/s DMT-VLC system with 1.9-m free space transmission, the OCT-based PDS-precoding signal shows almost the same BER performance as full data-carrying subcarriers precoding ones. Compared with the conventional scheme, the BER is reduced from 2e-3 to 8.14e-5 by using the proposed PDS-precoding. PDS-precoding is a nice choice to degrade the unbalanced damage for data-carrying subcarriers (SCs) in the bandwidth-limited VLC-based intelligent transportation system.