Generation Wireless Communication Research Articles

Design and Analysis of a 28 GHz T/R Front-End Module in 22-nm FD-SOI CMOS Technology

This article presents practical design considerations and methodologies for a 28-GHz front-end module (FEM) in 22-nm fully depleted silicon on insulator (FD-SOI) CMOS technology for the fifth generation (5G) wireless communication. The design adopts a gain-boosting technique that is comprehensively analyzed with a transformer-based stacked-FET power amplifier (PA). Then, the co-design of the transmit/receive (T/R) switch with the PA and low-noise amplifier (LNA) is investigated, and an electrostatic-discharge (ESD)-aware T/R switch incorporating PA circuitry is proposed to leverage the Tx- and Rx-mode performance. Moreover, the robustness of standalone PA and Tx-mode FEM is simulated and experimentally verified. Furthermore, the ground return paths and supply parasitic paths of the adopted single-ended LNA together with the proposed T/R switch are studied, properly simulated, and assessed. Finally, the proposed PA topology is first verified standalone, exhibiting 32-dB power gain ( G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ), an 18.2-dBm output 1-dB compression point (OP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1 dB</sub> ), and a 31.1% power-added efficiency (PAE) at OP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1 dB</sub> (PAE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1 dB</sub> ). Using this PA in the FEM yields a Tx-mode OP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1 dB</sub> /PAE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1 dB</sub> of 16 dBm/19.4%, and an average output power (Pout <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">avg</sub> )/PAE of 10.1 dBm/8.3% for a 100-MHz bandwidth 256-QAM single-carrier signal at an error-vector magnitude (EVM) of -30 dB. In the Rx mode, noise figure (NF) and input-referred third-order intercept point (IIP3) are 3.2 and -5.4 dBm, respectively. A 2-kV human-body model (HBM) ESD protection of the FEM is predicted in transient simulations and measured with transmission line pulse (TLP) tests.

Alternating Beamforming With Intelligent Reflecting Surface Element Allocation

Intelligent reflecting surface (IRS) has become a promising technology to aid next generation wireless communication systems. In this paper, we develop an alternating beamforming technique with a novel concept of IRS element allocation for multiple-input multiple-output systems when a base station supports multiple single antenna users aided with a single IRS. Specifically, we allocate each IRS element separately to each user, thus, in the beamforming stage allowing the IRS element only consider a single user at a time. In result to this separation, the complexity is vastly decreased. The proposed beamforming technique tries to maximize the minimum rate of all users with minimal complexity. In the numerical results, we show that the proposed technique is comparable to the convex optimization-based benchmark with sufficiently less complexity.

AI as an Essential Element of a Green 6G

Since the very beginning of global R&D activities on fifth generation wireless communications (5G), IEEEPAR energy-efficiency (EE) has been considered explicitly as one of the essential key performance indicators for wireless networks, and attracted much attention from academia and industry. The basic concepts, fundamental work, and various advanced techniques towards energy-efficient wireless communications were extensively studied and pursued in previous research efforts [items 1)–4) in the Appendix] The anticipated power consumption increase of 5G (due to the introduction of a massive number of antennas, much larger bandwidths, and much denser base stations) has forced standardization bodies like 3GPP to seriously consider the energy-savings capabilities needed to achieve a better EE performance. However, since the energy consumption of the actual hardware and software is closely related to the specific implementation schemes and operation scenarios, there is a lack of precise specifications for EE across standardization organizations.

Investigation of Ideal Number User Terminals with Spectrum Efficiency in Next Generation Wireless Communication Systems

Suppose that a multi-user multiple-input multiple-output (MIMO) system is developed from scratch to equally envelop a defined region with optimal spectrum efficiency (SE) in next generation wireless communication systems such as sixth-generation (6G) and beyond networks. What are the ideal number of user terminals U, number of base stations antennas, and used pilot reuse factor? The purpose of this paper is to address this specific issue. Three interference levels are specified for this. Based on these interference levels, signal-to-interference-and-noise ratios (SINRs) are extracted. Closed-form spectrum efficiency equations are thus obtained. As a function of the base station (BS) antenna number, simulations are carried out considering multiple pilot reuse factors and diverse processing schemes such as Maximum Ratio Combining (MRC) and Zero-Forcing (ZF). From the results, it is understood that U varies according to the processing schemes. Therefore, evaluating the results considering the fixed number of users K will not give an accurate result in determining the design parameters for the next generation communication systems. In general, these results are useful statements that spectrum efficiency is maximized when the ideal number of users U is used in multi-cell systems.

Energy-Efficient Resources Allocation With Millimeter-Wave Massive MIMO in Ultra Dense HetNets by SWIPT and CoMP

Ultra-dense HetNets (UDN)-based Millimeter-Wave (mmWave) massive MIMO is considered a promising technology for 5th generation (5G) wireless communications systems since it can offer massively available bandwidth and improve energy efficiency (EE) substantially. However, in UDN, the power consumption of the system increases sharply with the increase of network density. In this paper, we investigate the optimization of the EE in the mmWave massive MIMO systems with UDN. To develop the functions of massive MIMO, we first propose a system model where the massive MIMO harvests electromagnetic energy from the environment employing simultaneous wireless information and power transfer (SWIPT) technology, implemented at the base station (BS). Then, the EE optimization problem is formulated for 5G mmWave massive MIMO systems within the UDN. Considering the nonconcave feature of the objective function, an iterative EE algorithm is developed, based on Dinkelbach method. To utilize the role of coordinated multi-point transmission and reception (CoMP) for improving the EE, a coordinated user(UE)-BS association algorithm-based CoMP with maximum energy efficiency (MaxEE) is proposed. The simulation results demonstrate that the proposed algorithm has a substantially faster convergence rate and is very effective, compared with existing methods.

A Survey on Advanced Multiple Access Techniques for 5G and Beyond Wireless Communications

This paper summarizes the ongoing research initiatives based on the advanced multiple access techniques towards the fifth generation (5G) wireless communication and beyond. Prior cellular network generations have embraced various multiple access techniques with a common feature that is to have orthogonal signals at the side of the receiver for different users. The diverse requirements of huge number of connections about latency and throughput is the need of the hour. Therefore, 5G wireless systems and beyond, are preferring the design method to shift towards non-orthogonal from orthogonal in multiple access techniques. The paper will mainly focus on the non-orthogonal multiple access techniques considering the types of its candidates in multiple domains which can help us in identifying the impacts on the designs of multiple access for 5G network and beyond. This survey aims to discover the obstacles and possibilities of utmost importance for multiple access designs for 5G networks.

A Low Complexity Detector for Massive MIMO Uplink Systems

Fifth generation wireless communication system is implemented by several mobile companies where important technologies are employed such as the massive multiple-input multiple-output (MIMO). Although it improves the spectrum and energy efficiencies, it is not a trivial to propose an efficient detector for massive MIMO systems because a large number of antennas increases the computational complexity. In this paper, approximate message passing (AMP) is exploited in the massive MIMO uplink (UL) data detection. Although the AMP method is suffering from a considerable performance in special cases, an efficient selection of the initial solution affects greatly the convergence rate, the bit-error-rate performance, and the computational complexity. In this paper, three efficient initialization methods of the AMP-based massive MIMO UL detector are proposed based on iterative methods, namely, the successive overrelaxation, the Gauss–Seidel, and the Jacobi. In addition, a stair matrix is exploited to achieve high convergence rate. Numerical results show that the proposed detector achieved a considerable performance improvement and complexity reduction in comparison with the traditional AMP-based detector.

Graph-Based Resource Allocation for Air-Ground Integrated Networks

With the combined advantages of satellite communications, aerial networks and terrestrial systems, a space-air-ground integrated network has gradually become a promising architecture for the next generation wireless communication. Due to heterogeneous characteristics of different layers, it is necessary to perform efficient resource allocation. Motivated by this fact, we propose a novel architecture of air-ground integrated networks (AGIN), which leverages civil aircrafts and ground base stations to support terrestrial users’ service. Aiming at maximizing the overall capacity of downlink transmission in an AGIN, we formulate the resource allocation problem as an optimization problem subject to both quality of service (QoS) and fairness requirements. To address the formulated problem, we propose a graph-based joint optimization algorithm for resource block (RB) and power allocation. Specifically, an improved Kuhn-Munkras (KM) algorithm based on graph theory is proposed for RB allocation, which guarantees the fairness. Meanwhile, a multi-level water-filling method is proposed for power allocation. By leveraging an alternating descent approach, a joint optimal solution can be obtained after a finite number of iterations. It is demonstrated through simulation results that the proposed joint optimization algorithm is converges fast and shows significant improvement in terms of the sum-rate, fairness, access latency, and system capacity.

Novel Architecture for Wireless Power Transfer in Unmanned Arial Vehicles

There has been a rapid growth in research towards developing smart, low-cost, and high-performance unmanned aerial vehicles (UAVs) for enabling wireless data transfer and communication. The practical applications of UAVs in healthcare, surveillance, agriculture and other domains is increasing at a faster pace. Mass production of these UAVs is essential to meet the growing communication requirements. Plans towards standardization and global deployment of Internet-of-Things (IoT) technologies and fifth generation (5G) wireless communication are in progress. Functional diversity is established by the UAVs in enabling wireless communication with IoT and 5G technologies. The different UAVs used in wireless communication is studied and a hierarchical architecture is proposed to facilitate integrating these technologies into next-generation networks. The principles of aerodynamics, wireless communication, power transfer, area of coverage, delay, meteorological impacts and other design parameters and their tradeoffs is analyzed.

Lightweight porous silica foams with extreme-low dielectric permittivity and loss for future 6G wireless communication technologies

In the next generation wireless communication systems operating at near terahertz frequencies, dielectric substrates with the lowest possible permittivity and loss factor are becoming essential. In this work, highly porous (98.9% ± 0.1%) and lightweight silica foams (0.025 ± 0.005 g/cm3), that have extremely low relative permittivity (εr = 1.018 ± 0.003 at 300 GHz) and corresponding loss factor (tan δ< 3 × 10−4 at 300 GHz) are synthetized by a template-assisted sol-gel method. After dip-coating the slabs of foams with a thin film of cellulose nanofibers, sufficiently smooth surfaces are obtained, on which it is convenient to deposit electrically conductive planar thin films of metals important for applications in electronics and telecommunication devices. Here, micropatterns of Ag thin films are sputtered on the substrates through a shadow mask to demonstrate double split-ring resonator metamaterial structures as radio frequency filters operating in the sub-THz band.

Spectral Efficiency Improvement and Power Control Optimization of Massive MIMO Networks

Higher requirements must be put forward about wireless signal transmission in harsh environments. Energy loss mitigation, channel estimation, noise interference reduction demands high quality of service in wireless communication. In the fifth generation wireless communication, massive multiple-input multiple-output (MIMO) networks have been used and play a significant role to fulfill the requirements. Cell-Free massive MIMO networks are recognized as possible solution in the future wireless communication. Spectral efficiency (SE) is a very important index in assessing massive MIMO networks. This article tries to optimize both SE and power control of cell-free massive MIMO networks. Both uplink and downlink transmission are included in the study. The optimization model contains both SE and power control of massive MIMO networks. To tackle the model, a novel ensemble method is developed inspired by ensemble learning. The ensemble method is built up on the neighborhood field optimization method. The goodness of the developed ensemble method is verified by comparing with genetic algorithm, gradient descent method and Newton method. Extensive simulations are performed to study the optimization of SE and power control. Different wireless sensors are taken into consideration to simulate different requirements of massive MIMO networks. The results demonstrate the effectiveness of the proposed method for applying in massive MIMO networks.

A Survey on Deep Learning for Ultra-Reliable and Low-Latency Communications Challenges on 6G Wireless Systems

The sixth generation (6G) wireless communication network presents itself as a promising technique that can be utilized to provide a fully data-driven network evaluating and optimizing the end-to-end behavior and big volumes of a real-time network within a data rate of Tb/s. In addition, 6G adopts an average of 1000+ massive number of connections per person in one decade (2030 virtually instantaneously). The data-driven network is a novel service paradigm that offers a new application for the future of 6G wireless communication and network architecture. It enables ultra-reliable and low latency communication (URLLC) enhancing information transmission up to around 1 Tb/s data rate while achieving a 0.1 millisecond transmission latency. The main limitation of this technique is the computational power available for distributing with big data and greatly designed artificial neural networks. The work carried out in this paper aims to highlight improvements to the multi-level architecture by enabling artificial intelligence (AI) in URLLC providing a new technique in designing wireless networks. This is done through the application of learning, predicting, and decision-making to manage the stream of individuals trained by big data. The secondary aim of this research paper is to improve a multi-level architecture. This enables user level for device intelligence, cell level for edge intelligence, and cloud intelligence for URLLC. The improvement mainly depends on using the training process in unsupervised learning by developing data-driven resource management. In addition, improving a multi-level architecture for URLLC through deep learning (DL) would facilitate the creation of a data-driven AI system, 6G networks for intelligent devices, and technologies based on an effective learning capability. These investigational problems are essential in addressing the requirements in the creation of future smart networks. Moreover, this work provides further ideas on several research gaps between DL and 6G that are up-to-date unknown.

Analysis of 5G Non-Orthogonal Technology Application on Smart Grid

Fifth generation (5G) wireless communication networks are being deployed worldwide at present, which not only enhances transmission ability with wide bandwidth for wireless mobile communication, but also enables 5G to promote a new digital, network and intelligence for all industry. Power communication has unique requirement and feature for itself, and with more and more power and other energy terminal devices need to access network, the current air access technology is difficult to satisfy the requirements. The 5G had carried out many key technology researches, including air interface and network technology, which establish solid basement for 5G standard and 5G+industry application. The article focuses on 5G Non-Orthogonal Multiple-Access (NOMA) technology, especially PDMA, and illustrates technology application scheme with power collection requirement as an example. It can be seen that NOMA can enhance network capability greatly for power communication, and improve transmission cover ability.

Integration of Sub-6-GHz and mm-Wave Bands With a Large Frequency Ratio for Future 5G MIMO Applications

The integration of sub-6-GHz and millimeter-wave (mm-wave) bands has become an important issue for future fifth generation (5G) wireless communications owing to their large frequency ratios. This paper proposes a compact-size dual-function antenna operating at 3.5 GHz and the mm-wave band (28 GHz) for 5G mobile applications using a frequency reconfigurability technique. The proposed antenna comprises a microstrip patch linked with a meandered radiating structure through a radio frequency PIN diode to achieve frequency reconfigurability between the two bands. A significant size reduction up to 15.3 mm × 7.2 mm × 0.508 mm for the proposed antenna was achieved using a meandered line structure and truncated ground plane. To enhance the functionality, 8 × 8 multiple-input multiple-output (MIMO) with possible long- and short-edge antenna placement configurations were demonstrated. The system exhibited satisfactory MIMO characteristics with wide decoupling -10 dB bandwidths of 7.4% and 4.8% at the low- and high-frequency bands, respectively, without utilizing any external decoupling structure. The simulated results were validated using fabricated prototypes, and good agreement was observed. Additionally, a safety analysis based on the specific absorption rate and power density at the prescribed frequency bands was conducted using a realistic human model, and the results were found to be in accordance with the safety guidelines. Owing to the integration of sub-6-GHz and mm-wave bands in a single compact structure with a large frequency ratio and good MIMO performance, the proposed antenna system is suitable for future 5G mobile handheld devices.

Power allocation for NOMA in D2D relay communications

Non-orthogonal multiple access (NOMA) is considered as one of the key technologies for the fifth generation (5G) wireless communications. The integration of NOMA and device-to-device (D2D) communications has recently attracted wide attention. In this paper, a relaying D2D communications assisted with cooperative relaying systems using NOMA (DRC-NOMA) is considered. We analyze the ergodic sum-rate for the proposed system and then derive the closed-form expressions. In addition, an optimal power allocation strategy maximizing the ergodic sum-rate is proposed based on these analysis results. Numerical results show the good agreement between the results of analysis and Monte Carlo method. The proposed DRC-NOMA has a great improvement of the ergodic sum-rate in the small regime of average channel gain of D2D pair.

Análisis de la técnica UFMC en un canal multitrayecto y usando estimación de canal

UFMC (Universal Filtered Multi-Carrier) is a novel multi-carrier transmission technique that aims to replace the OFDM (Orthogonal Frequency Division Multiplexing) modulation technique for fifth generation (5G) wireless communication systems. UFMC, being a generalization of OFDM and FBMC (Filter Bank Multicarrier), combines the advantages of these systems and at the same time avoids their main disadvantages. Using a Matlab simulation, this article presents an analysis of the robustness of UFMC against fading effects of multipath channels without using a CP (cyclic prefix). The behavior of the UFMC system is analyzed in terms of the PSD (Power Spectral Density), BER (Bit Error Rate) and MSE (Mean Square Error). The results show that UFMC reduces the out-band side lobes produced in the PSD of the processed signal. Also, it is shown that the pilot-assisted channel estimation method applied in OFDM systems can also be applied in UFMC systems.

New Trends and Advancement in Next Generation Mobile Wireless Communication (6G): A Survey

As the commercial implementations of 5G networks have been initiated in different regions of the world, the focus of the researchers is bending towards the next generation of wireless communication. This research study intends to investigate the requisites of the fast establishment of the theoretical and practical measures for sixth generation (6G) wireless communication. To this end, this paper first outlined the existing research works that have considered different aspects of 6G, and then based on this existing works, the future vision is established. Then, the 6G vision is based on four types of connectivity and is summarized as “Wherever you think, everything follows your heart.” To fill the gap between the market requirements after one decade and the limited capabilities of 5G, different specifications of 6G that make it an appropriate replacement are discussed. Furthermore, different candidate technologies that can potentially realize the 6G communication are studied, followed by discussion on different challenges in the realization and possible research directions to cope with these challenges. By exploring the vision of future, its specification, and key candidate technologies, this paper attempts to summarize the general 6G framework. In addition, with mentioned challenges in realization of 6G, the aim of this paper is to guide the researcher and attract their interest to consider them.

Dual-Determination of Modulation Types and Signal-to-Noise Ratios Using 2D-ASIQH Features for Next Generation of Wireless Communication Systems

In order to pursue rapid development of the new generation of wireless communication systems and elevate their security and efficiency, this paper proposes a novel scheme for automatic dual determination of modulation types and signal to noise ratios (SNR) for next generations of wireless communication systems, fifth-generation (5G) and beyond. The proposed scheme adopts unique signatures depicted in two-dimensional asynchronously sampled in-phase-quadrature amplitudes' histograms (2D-ASIQHs)-based images and applies the support vector machines (SVMs) tool. Along with the estimation of the instantaneous SNR values over 0-35 dB range, the determination of nine modulation types that belong to different modulation categories i.e., phase-shift keying (Binary-PSK, Quadrature-PSK, and 8-PSK), amplitude-shift keying (2-ASK and 4-ASK) and quadrature-amplitude modulation (4-QAM, 16-QAM, 32-QAM, and 64-QAM) could be achieved by this scheme. The application of this scheme has been simulated using a channel model that is impaired by additive white Gaussian noise (AWGN) and Rayleigh fading, covering a broad range of SNRs of 0-35 dB. The performance of this dual-determination scheme shows high modulation recognition accuracy and low mean SNR estimation error. Therefore, it can be a better alternative for designers of next generation wireless communication systems.

PAPR reduction of MIMO-OFDM using galaxy inspired swarm-based PTS strategy

Multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is a striking scheme, which has procured noteworthy importance as an auspicious contender for not only 4th generation but 5th generation wireless communication also. However, the mountainous problem regarding MIMO-OFDM is its considerably high peak to average power ratio (PAPR). In this literature, partial transmit sequence (PTS) mechanism is instigated on MIMO-OFDM system. Its effectiveness verification is displayed with assorted simulation results. Results reveals that PTS strategy not only refine but boost the potential of the MIMO-OFDM-based system, moreover, it has hitherto been indicated that with rise in sub-blocks, that are mostly non-overlapping, PAPR performance enhances. Further, the phase factors of MIMO-OFDM-based system are optimised by evolutionary techniques which drives its inspiration from galaxies called galaxy inspired swarm-based optimisation (GSO).

Possible adoption of various machine learning techniques in cognitive radio - a survey

The concept of cognitive radio (CR) system is the need for next generation wireless communication technology in terms of providing intelligence and superior performance to a wireless device. The CR is mainly an intelligent system which is aware of its environment and is well capable to adapt in accordance with the changing environment and user needs. The concept of adaptation of the communication system can be realised well with machine learning capability inculcated within the system. It is a well-known fact that, the key strengths of any machine learning paradigm is its ability to adapt with respect to the dynamic changing system parameters. In this paper, an attempt has been made to compile various applications of machine learning techniques for different activities of CR cycle. Further, this note reviews the work on development of machine learning techniques for spectrum sensing of CR in order to make the CR system as a whole practically feasible and robust, thus mitigating its existing computational limitations due to the use of conventional techniques.