Radio Frequency Chains Research Articles

A New Design of Codebook for Hybrid Precoding in Millimeter-Wave Massive MIMO Systems

The precoding scheme based on codebooks is used to save the same set of codebook in advance at the transmitter and the receiver, then, the receiver selects the most appropriate precoding matrix from codebooks according to different channel state information (CSI). Therefore, the design of codebook plays an important role in the performance of the whole scheme. The symmetry-based hybrid precoder and combiner is a highly energy efficient structure in the millimeter-wave massive multiple-input multiple-output (MIMO) system, but at the same time, it also has the problems of high bit error rate and low spectral efficiency. In order to improve the spectral efficiency, we formulate the codebook design as a joint optimization problem and propose an iteration algorithm to obtain the enhanced codebook by combining the compressive sampling matching pursuit (CoSaMP) algorithm with the dictionary learning algorithm. In order to prove the validity of the proposed algorithm, we simulate and analyze the change of the spectral efficiency of the algorithm with the signal-to-noise ratio (SNR) and the number of radio frequency (RF) chains of different precoding schemes. The simulation results demonstrate that the spectral efficiency of the algorithm is obviously outstanding compared with that of the OMP-based joint codebook algorithm and the hybrid precoding algorithm with quantization algorithm under low SNR and different numbers of RF chains. Particularly, when SNR is lower than 0 dB, the proposed algorithm performs very close to the optimal unconstrained precoding algorithm.

Performance Evaluation of Offset Spatial Modulation Systems With Practical Channel Estimation

Offset spatial modulation (OSM) is an attractive multiple-input–multiple-output (MIMO) transmission scheme, which alleviates the switching frequency limitation of the radio frequency chain in the spatial modulation technology. In this article, we investigate the bit error performance of OSM in the presence of imperfect channel estimation toward a practical transmission scenario. More specifically, with the aid of union bound technique, a general performance analysis framework of the OSM system with channel estimation errors is proposed. Based on the above analysis framework, the upper bounds of bit error rate for the static and dynamic modes of OSM are both derived, respectively. Finally, simulation results demonstrate that the analytical bounds are tight for a wide range of signal-to-noise ratio (SNR) and variable system configurations.

Hardware-Impaired Rician-Faded Massive MIMO FD Relay: Analysis and Optimization

We consider two-way multi-pair full-duplex (FD) massive multi-input-multi-output (mMIMO) relaying, where multiple FD user-pairs exchange information via a shared FD relay. We derive a closed-form spectral efficiency (SE) lower bound by considering i) dynamic analog-to-digital converter (ADC) and digital-to-analog converter (DAC) architecture at the relay, where each antenna is connected to a different resolution ADC/DAC; and ii) low cost radio frequency (RF) chains at the relay and users. The dynamic ADC/DAC architecture allows us to judiciously choose ADC/DAC resolution to achieve high SE with low power consumption. We unlike, the most existing mMIMO relaying works, consider a correlated Rician fading channel, which captures realistic line-of-sight (LoS) signal propagation and spatial correlation between closely-packed relay antennas. We maximize the derived SE lower bound by first proposing its valid surrogate function, and then by using minorization-maximization approach. We investigate the impact of ADC/DAC and RF impairments, and show that the proposed optimization allows reduction in ADC/DAC resolution without compromising the SE.

Multi-cell, Multi-user, and Multi-carrier Secure Communication Using Non-Orthogonal Signals’ Superposition with Dual-Transmission for IoT in 6G and Beyond

Considering the advancements of the internet of things (IoT) in 6G and beyond communications, data transmission security in IoT devices has received extensive interest because of their significant features, such as low computational complexity, led by low power requirements. In such devices, the conventional cryptographic techniques may fail to provide secure communication. To fight this drawback, physical layer security (PLS) has remarkable potential to provide security solutions suitable for such applications. In this work, a highly effective PLS technique is proposed for providing secure communication against external and internal eavesdroppers in a downlink multi-cell, multi-user, and multi-carrier IoT communication system. In our proposed system, we considered two base stations, where each base station uses a single radio frequency (RF) chain to link two antennas that are used for the transmission of data. Further, we transmit the data in two rounds, and each round of transmission occurs through a single active antenna of each base station. A different antenna is used for each round of transmission to communicate with two single antenna IoT devices/users in the presence of a passive eavesdropper. In the proposed algorithm, frequency selective channel-based pre-coder matrices and the dual transmission approach are jointly employed. The dual-transmission is performed simultaneously from two base stations to provide security against internal and external eavesdroppers. The proposed system is suitable for IoT-based applications. Also, the potential capabilities of our proposed algorithm are proved by extensive mathematical and simulation analysis.

Large Antenna Array with Hybrid Beamforming System for 5G Outdoor Mobile Broadband Communication Deployments

Millimeter wave (mmWave) communication requires large antenna arrays to increase the capability of cellular networks of the fifth generation with good beam-forming gains and a substantial reduction in path losses for both transmitting and receiving terminals. As large antenna arrays require one radio frequency chain per antenna element, the fully digital beamforming technique results in high cost and high-power consumption, and it is therefore not feasible. However, in analog solutions, adaptive gain control cannot be used as it reduces the likelihood of advanced processing and contributes to poor efficiency. Hybrid schemes are possible exciting solutions that overcome the deficiencies of pure digital or analog beam forming. The following are the three key contributions of the proposed work: a typical link budget specification for target data rate 3.10 Gbps in downlink and 0.6 Gbps in uplink is provided, micro strip patch antenna with a single element is designed to operate at 28 GHz and then converted into a standard linear array and a Kalman-based hybrid analog/digital precoding is used with a downlink rate of 4.64 Gbps/cell and an uplink rate of 1.84 Gbps/cell in multi-user environments. And the influence of both base station (BS) and 5G User equipment (UEs) beam steering capability is also explored. From the simulation result, it is evident that the proposed work offers a substantial increase in spectral efficiency approximately 9.28 bps/Hz at 20 dB with 10 channel paths.

Wideband Beam Tracking in THz Massive MIMO Systems

Terahertz (THz) massive multiple-input multiple-output (MIMO) has been considered as one of the promising technologies for future 6G wireless communications. It is essential to obtain channel information by beam tracking scheme to track mobile users in THz massive MIMO systems. However, the existing beam tracking schemes designed for narrowband systems with the traditional hybrid precoding structure suffer from a severe performance loss caused by the beam split effect, and thus cannot be directly applied to wideband THz massive MIMO systems. To solve this problem, in this paper we propose a beam zooming based beam tracking scheme by considering the recently proposed delay-phase precoding structure for THz massive MIMO. Specifically, we firstly prove the beam zooming mechanism to flexibly control the angular coverage of frequency-dependent beams over the whole bandwidth, i.e., the degree of the beam split effect, which can be realized by the elaborate design of time delays in the delay-phase precoding structure. Then, based on this beam zooming mechanism, we propose to track multiple user physical directions simultaneously in each time slot by generating multiple beams. The angular coverage of these beams is flexibly zoomed to adapt to the potential variation range of the user physical direction. After several time slots, the base station is able to obtain the exact user physical direction by finding out the beam with the largest user received power. Unlike traditional schemes where only one frequency-independent beam can be usually generated by one radio-frequency chain, the proposed beam zooming based beam tracking scheme can simultaneously track multiple user physical directions by using multiple frequency-dependent beams generated by one radio-frequency chain. Theoretical analysis shows that the proposed scheme can achieve the near-optimal achievable sum-rate performance with low beam training overhead, which is also verified by extensive simulation results.

Towards the assessment of realistic hybrid precoding in millimeter wave MIMO systems with hardware impairments

Hybrid processing in millimeter wave (mmWave) communication has been proposed as a solution to reduce the cost and energy consumption by reducing the number of radio-frequency (RF) chains. However, the impact of the inevitable residual transceiver hardware impairments (RTHIs), including the residual additive transceiver hardware impairments (RATHIs) and the amplified thermal noise (ATN), has not been sufficiently studied in mmWave hybrid processing. In this work, the hybrid precoder and combiner are designed, which include both digital and analog processing by taking into account the RATHIs and the ATN. In particular, a thorough study is provided to shed light on the degradation of the spectral efficiency (SE) of the practical system. The outcomes show the steady degradation of the performance by the ATN across all SNR values, which becomes increasingly critical for higher values of its variance. Furthermore, it is shown that RATHIs result in degradation of the system only in the high SNR regime. Hence, their impact in mmWave system operating at low SNRs might be negligible. Moreover, an increase concerning the number of streams differentiates the impact between the transmit and receive RATHIs with the latter having a more severe effect.

Higher Spectral Efficiency for mmWave MIMO: Enabling Techniques and Precoder Designs

Millimeter wave (mmWave) communications can support huge data rate growth and wide bandwidth in the new 5G era, and a hybrid precoding architecture can effectively handle the high hardware cost and energy consumption problems. A crucial goal is to optimize the system's spectral efficiency (SE) by effectively designing the digital precoder and the analog precoder. In this article, we review the conventional hybrid precoding schemes in mmWave systems, and then investigate several novel systems with index modulation (IM) techniques as well as their hybrid precoder designs. With the advantages of IM, higher SE can be achieved with limited radio frequency chains in mmWave systems. Simulation results demonstrate that two types of IM-aided systems both outperform conventional mmWave systems, which proves that IM is an enabling technique in practical SE-driven mmWave systems. Finally, we discuss the limiting factors and outlook of IM-aided mmWave systems in beyond-5G wireless communications.

A novel committee machine hybrid precoding and combining algorithm for mmWave massive MU-MIMO systems

Millimeter-wave (mmWave) massive multi-user multiple input multiple output (MU-MIMO) systems employ hybrid analog-digital precoding/combining design, to reduce the number of radio-frequency (RF) chains without large sum-rate performance loss. Committee machines combine several expert algorithms to yield better reliable estimates to those of its constituent experts. However, several committee machines approach mainly rely on the ‘quality’ of the joint support-set of expert algorithms combine by committee machine. In this paper, we present hybrid analog-digital precoder and combiner designs for mmWave massive MU-MIMO systems by exploiting the intersection of the estimated support-sets, namely, common support-set of ‘expert’ algorithms in a committee machine methodology. With S denoting the sparsity level, the proposed algorithms perform two essential tasks to identify in which subspace, generated by not more than S columns of the matrix of array response vectors, the optimal hybrid analog-digital precoders or combiners lie: Firstly, the selection of the committee machine common support set, which accepts the section where both the ‘experts’ agree. Secondly, if some column indices of the optimal hybrid analog-digital precoders or combiners do not lie in the current common support-set for the correct spanning space, −the algorithm searches over the matrix of array response vectors and selects column indices that exhibit the highest correlation with the signal residual, to acquire the remaining support. We derive the theoretical analysis for performance enhancement of the proposed algorithm. Simulation results demonstrate that the proposed design allows mmWave massive MU-MIMO systems to approach their unconstrained performance limits, and exhibits substantial sum-rate performance improvement over existing regularized channel diagonalization based schemes and the beam steering solution.

Hybrid Beamforming for Multi-Carrier Dual-Function Radar-Communication System

This paper investigates a hybrid beamforming design for dual-function radar-communication (DFRC) systems. Comparing with fully digital beamforming, much less radio frequency (RF) chains are needed and hence, both hardware cost and energy consumption can be reduced. The hybrid transmit/receive beamformers are designed by maximizing the sum-rate under constraints of power as well as similarity between the designed beamformer and the reference one that has good beampattern property. Particularly, both single-user and multi-user scenarios are addressed by introducing different hybrid beamforming designs. For the single-user case, we devise an alternating optimization method under the alternating direction method of multipliers (ADMM) framework. For the multi-user scenario, we introduce a two-stage procedure based on weighted mean-square error minimization (WMMSE). Numerical simulations are provided to demonstrate the effectiveness of the proposed schemes.

Adaptive Cross Entropy-Based Kalman Filter Hybrid Precoding For Frequency Selective mmWave MIMO Channel: Time Domain approach

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.

3D Metallic Plate Lens Antenna based Beamspace Channel Estimation Technique for 5G Mmwave Massive MIMO Systems

Beamspace channel estimation mechanism for massive MIMO (multiple input multiple output) antenna system presents a major process to compensate the 5G spectrum challenges caused by the proliferation of information from mobile devices. However, this estimation is required to ensure the perfect channel state information (CSI) for lower amount of Radio Frequency (RF) chains for each beam. In addition, phase shifter (PS) components used in this estimation need high power to select the beam in the desired direction. To overcome these limitations, in this work, we propose Regular Scanning Support Detection (RSSD) based channel estimation mechanism. Moreover, we utilise a 3D lens antenna array having metallic plate and a switch in our model which compensates the limitation of phase shifters. Simulation results show that the proposed RSSD based channel estimation surpasses traditional technique and SD based channel estimation even in lower SNR area which is highly desirable in the millimeter wave (mmWave) massive MIMO systems.

Investigation of the Impact of Zero-Forcing Precoding on the Variation of Massive MIMO Transmitters’ Performance With Channel Conditions

In this letter, the impact of two variants of zero-forcing (ZF) precoding (conventional and minimax) on the performance of massive multiple-input-multiple-output (MIMO) transmitters is investigated through simulations and experiments. In massive MIMO transmitters, the average-power levels across the radio frequency (RF) chains depend on the choice of precoder and the channel conditions. Compared to the conventional ZF precoder, the minimax variant results in significantly less variations in the average-power levels across the RF chains and, consequently, in less disparity between their operating characteristics. Thus, the minimax precoder, albeit requiring more computational resources, reduces the variation of the transmitter's performance with the channel conditions. Experiments performed using the two ZF variants, in conjunction with digital predistortion, on a two-user four-chain MIMO transmitter under 200 different channel realizations revealed that the minimax variant allows for up to 10 dB and 8% reductions in the adjacent-channel power ratio and root normalized mean-square error, respectively, in each chain.

A Signal Processing Framework for Agile RF Beamforming: From RF-Chain-Free to Hybrid Beamformers

In conventional hybrid beamforming approaches, the number of radio-frequency (RF) chains is the bottleneck on the achievable spatial multiplexing gain. Recent studies have overcome this limitation by increasing the update-rate of the RF beamformer. This paper presents a framework to design and evaluate such approaches, which we refer to as agile RF beamforming, from theoretical and practical points of view. In this context, we consider the impact of the number of RF-chains, phase shifters' speed, and resolution to design agile RF beamformers. Our analysis and simulations indicate that even an RF-chain-free transmitter, which its beamformer has no RF-chains, can provide a promising performance compared with fully-digital systems and significantly outperform the conventional hybrid beamformers. Then, we show that the phase shifter's limited switching speed can result in signal aliasing, in-band distortion, and out-of-band emissions. We introduce performance metrics and approaches to measure such effects and compare the performance of the proposed agile beamformers using the Gram-Schmidt orthogonalization process. Although this paper aims to present a generic framework for deploying agile RF beamformers, it also presents extensive performance evaluations in communication systems in terms of adjacent channel leakage ratio, sum-rate, power efficiency, error vector magnitude, and bit-error rates.

Energy-Efficient Hybrid Symbol-Level Precoding for Large-Scale mmWave Multiuser MIMO Systems

We address the symbol-level precoding design problem for the downlink of a multiuser millimeter wave (mmWave) multiple-input multiple-output (MIMO) wireless system where the transmitter is equipped with a large-scale antenna array. The high cost and power consumption associated with the massive use of radio frequency (RF) chains prohibit fully-digital implementation of the precoder, and therefore, we consider a hybrid analog-digital architecture where a small-sized baseband precoder is followed by two successive networks of analog on-off switches and variable phase shifters according to a fully-connected structure. We jointly optimize the digital baseband precoder and the states of the switching network on a symbol-level basis, i.e., by exploiting both the channel state information (CSI) and the instantaneous data symbols, whereas the phase-shifting network is designed only based on the CSI due to practical considerations. Our approach to this joint optimization is to minimize the Euclidean distance between the optimal fully-digital and the hybrid symbol-level precoders. Remarkably, the use of a switching network allows for power-savings in the analog precoder by switching some of the phase shifters off according to the instantaneously optimized states of the switches. Our numerical results indicate that, on average, up to 50 percent of the phase shifters can be switched off. We provide an analysis of energy efficiency by adopting appropriate power dissipation models for the analog precoder, where it is shown that the energy efficiency of precoding can substantially be improved thanks to the phase shifter selection approach, compared to the fully-digital and the state-of-the-art hybrid symbol-level schemes.

Privacy-Preserving Channel Estimation in Cell-Free Hybrid Massive MIMO Systems

We consider a cell-free hybrid massive multiple-input multiple-output (MIMO) system with K users and M access points (APs), each with N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sub> antennas and N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> <; N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sub> radio frequency (RF) chains. When K <; <; MN <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sub> , efficient uplink channel estimation and data detection with reduced number of pilots can be performed based on low-rank matrix completion. However, such a scheme requires the central processing unit (CPU) to collect received signals from all APs, which may enable the CPU to infer the private information of user locations. We therefore develop and analyze privacy-preserving channel estimation schemes under the framework of differential privacy (DP). As the key ingredient of the channel estimator, two joint differentially private noisy matrix completion algorithms based respectively on Frank-Wolfe iteration and singular value decomposition are presented. We provide an analysis on the tradeoff between the privacy and the channel estimation error. In particular, we show that the estimation error can be mitigated while maintaining the same privacy level by increasing the payload size with fixed pilot size; and the scaling laws of both the privacy-induced and privacy-independent error components in terms of payload size are characterized. Simulation results are provided to further demonstrate the tradeoff between privacy and channel estimation performance.

Multicarrier Directional Modulation Symbol Synthesis Using Time-Modulated Phased Arrays

In this letter, we present a new approach of using time-modulated phased arrays to synthesize multicarrier directional modulation (DM) symbols for physical-layer security. In particular, the modulated waveform synthesis is achieved with the careful design of the switching time sequences, instead of in digital baseband; thus, reducing the peak-to-average power ratio of signals going through the radio frequency (RF) chain, and only a single RF chain is required here. The operation principle and synthesis approach are elaborated and demonstrated. In addition, the efficacy of the proposed DM approach is validated via the bit-error-rate (BER) metric.

Coordinate Interleaved Orthogonal Design With Media-Based Modulation

In this work, we propose a new multiple-input multiple-output (MIMO) concept, which is called coordinate interleaved orthogonal design with media-based modulation (CIOD-MBM). The proposed two novel CIOD-MBM schemes provide improved data rates as well as diversity gain while enabling hardware simplicity using a single radio frequency (RF) chain. Moreover, using the equivalent channel model, a reduced complexity can be obtained for maximum likelihood (ML) detection of the proposed system. Using computer simulations, it is shown that CIOD-MBM schemes provide remarkably better performance against the conventional MBM and CIOD systems.

Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance

We investigate the performance of multi-user multiple-antenna downlink systems in which a base station (BS) serves multiple users via a shared wireless medium. In order to fully exploit the spatial diversity while minimizing the passive energy consumed by radio frequency (RF) components, the BS is equipped with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> RF chains and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> antennas, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M &lt; N$ </tex-math></inline-formula> . Upon receiving pilot sequences to obtain the channel state information (CSI), the BS determines the best subset of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> antennas for serving the users. We propose a joint antenna selection and precoding design (JASPD) algorithm to maximize the system sum rate subject to a transmit power constraint and quality of service (QoS) requirements. The JASPD algorithm overcomes the non-convexity of the formulated problem via a doubly iterative algorithm, in which an inner loop successively optimizes the precoding vectors, followed by an outer loop that tests all valid antenna subsets. Although approaching (near) global optimality, the JASPD suffers from a combinatorial complexity, which may limit its application in real-time network operations. To overcome this limitation, we propose a learning-based antenna selection and precoding design algorithm (L-ASPA), which employs a deep neural network (DNN) to establish underlaying relations between key system parameters and the selected antennas. The proposed L-ASPD algorithm is robust against the number of users and their locations, the transmit power of the BS, as well as the small-scale channel fading. With a well-trained learning model, it is shown that the L-ASPD algorithm significantly outperforms baseline schemes based on the block diagonalization and a learning-assisted solution for broadcasting systems and achieves a better effective sum rate than that of the JASPA under limited processing time. In addition, we observed that the proposed L-ASPD algorithm can reduce the computation complexity by 95% while retaining more than 95% of the optimal performance.

Low-Complexity Hybrid Precoding Algorithm Based on Log-Det Expansion for GenSM-Aided MmWave MIMO System

Generalized spatial modulation (GenSM) aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) system has been recently considered as a new efficient technique due to the combination of numerous antennas and reduced number of radio frequency (RF) chains. However, the present hybrid precoding schemes for GenSM-aided system are still troubled by high computational complexity and performance loss in spectral efficiency (SE). In this paper we propose low-complexity hybrid precoding schemes based on Martin's expansion for logarithmic determinant (log-det) form in analytical SE lower bound. Digital and analog precoders are herein optimized separately, which means complicated alternating minimization iteration is omitted. Besides, we can adjust algorithmic complexity adaptively corresponding to different demand levels for users. Finally the numerical simulations show that the proposed methods outperform other GenSM-aided mmWave MIMO schemes and can achieve a better tradeoff between complexity and SE.