Next-generation Wireless Communication Systems Research Articles

Advancements in MIMO Antennas for Enhanced Performance in 5G Smartphones Communication

In this review paper provides a comprehensive overview of recent advancements in multiple input multiple output (MIMO) antenna designs for 5G smartphones. There are various antenna configurations that are discussed along with benefit and limitations. The paper also examines key challenges such as antenna mutual coupling, isolation and the size constraints inherent in smartphones. Furthermore, the impact of MIMO antenna design on 5G smartphone performance characteristics such as gain, radiation efficiency and spatial multiplexing capability is also analyzed. Finally, future research directions and potential innovations in MIMO antenna technology for 5G smartphones are identified to address emerging requirements and opportunities in next-generation wireless communication systems. The comprehensive comparison of different MIMO antenna performance is also given.

Exploring and Analyzing a Hybrid PAPR Reduction Method for OFDM Optimization

Orthogonal Frequency Division Multiplexing (OFDM) is a effective modulation technique widely used in modern communication systems, including 5G and wireless networks because of its high spectral efficiency and robustness towards multipath fading. However, OFDM signals are characterized by a high Peak-to-Average Power Ratio (PAPR), which can severely impact the power efficiency and operational cost of these systems. This research investigates and analyse effectiveness of two conventional PAPR reduction methods that is Selective Mapping (SLM), and Partial Transmit Sequence (PTS) with incorporating their approach of PAPR reduction to develop a hybrid variant: SLM-PTS. This study utilized MATLAB simulations to implement and test each PAPR reduction technique on a standard OFDM system model. Parameters such as the number of subcarriers, oversampling factor, and modulation types were systematically varied to analyze the impact on PAPR, BER, and computational complexity. The effectiveness of each technique was measured using the Complementary Cumulative Distribution Function (CCDF) of PAPR values and BER performance under different channel conditions. Key findings reveal that hybrid techniques, particularly SLM & PTS, offer significant improvements in PAPR reduction compared to traditional methods alone, without a corresponding increase in BER or computational overhead. The research underscores the potential of hybrid PAPR reduction techniques to significantly enhance the efficiency and reliability of OFDM systems. These findings have important implications for the design and optimization of next-generation wireless communication systems, suggesting that hybrid approaches can provide a balanced solution to the longstanding issue of PAPR in OFDM transmissions. This study contributes valuable insights into the practical application of combined PAPR reduction strategies, offering a pathway toward more power-efficient and robust OFDM technologies. Keywords : OFDM, PAPR, CCDF, SLM and PTS

5G Channel Estimation using Deep Learning

The abstract focuses on the integration of 5G channel estimation and the vulnerability of deep learning models, specifically in the context of OFDM signals, while employing a student-teacher model architecture. Channel estimation is a crucial aspect of 5G communication systems, ensuring reliable data transmission in dynamic wireless environments. Simultaneously, the advent of deep learning introduces susceptibility to adversarial attacks, where malicious inputs can deceive the model's predictions. This paper explores the intricate relationship between 5G channel estimation and deep learning vulnerabilities, emphasising the application of a student-teacher model to enhance system robustness. By delving into the nuances of OFDM signals, the study aims to provide a comprehensive understanding of how these elements intertwine, offering insights into potential security enhancements for next-generation wireless communication systems.

Dual-polarized IRS-assisted wireless network: relative phase modulation

The metasurface is a promising technology that can help next-generation wireless communication systems not only improve the signal-to-noise ratio (SNR), but also increase security and mitigate interference. Further, introducing dual polarization (DP) in a metasurface can enhance its capabilities with polarization diversity, polarization multiplexing, and polarization-switched modulation. In this paper, we study a DP-metasurface-assisted single-user wireless communication system and propose a novel scheme that can improve the spectral efficiency (SE) and bit-error-rate (BER) performance compared to those of conventional schemes by exploiting the orthogonal property of dual-polarized waves. We employ the DP metasurface to increase the SNR at the receiver and create a specific phase difference between the polarized signals by controlling the transmit precoder and the phases of the metasurface reflecting elements representing some modulated bits. At the receiver, we use the recovered phase information to realign the modulated symbols in both polarizations, which are then added coherently. The simulation results demonstrate that the proposed scheme achieves significantly higher SE and BER performance than those of some closely related works.

Hybrid TOA/AOA localization for indoor multipath-assisted next-generation wireless networks

The next-generation wireless communication systems (NGWCs) necessitate integrating effective communication and localization techniques. However, the multipath badly affects both communication and localization, especially in indoor NGWCs. Therefore, we propose a novel hybrid localization method based on time and angle-based ranging estimation to address this issue. This method employs an improved matrix enhancement matrix pencil algorithm (IMEMP) to obtain the time of arrival (TOA) and corresponding angle of arrival (AOA) of each path. Two distinct localization methods are presented: First arrival path-based maximum likelihood (ML) and scatterer-assisted. Both methods are designed to mitigate the adverse effects of serious non-line-of-sight (NLOS) scenarios. The proposed scatterer-assisted method demonstrates a noteworthy 20% improvement in performance compared to scenarios where only the first path is considered, particularly in specific areas. These findings highlight the potential of the proposed approach to enhance localization accuracy in challenging wireless environments, offering valuable insights for the advancement of NGWCs.

An efficient high performance reconfigurable canonical sign digit architecture for software defined radio

Software defined radios (SDRs) are highly motivated for wireless device modelling due to their flexibility and scalability over alternative wireless design options. The evolutionary structure of finite impulse response (FIR) filters was designed for a proposed reconfigurable canonical sign digit (CSD) approach. Considering the complex trade-off, this is accomplished with many FIR taps, which is a challenging assignment. On the baseband processing side, design is given with parameterization-controlled FIR filter tap selection. Optimal processing models to overcome the reconfigurable design issues associated with the SDR system for a multi-standard wireless communication system root cosine filter standard are often used to implement multiple FIR channelization topologies, each of which is tied to a particular in-phase and quadrature (IQ) symbol. Additionally, it demonstrates the viability of using a multi-modulation baseband modulator in the SDR system for next-generation wireless communication systems to maximise adaptability with the least amount of computational complexity overhead. The proposed multiplier-less FIR filter-based reconfigurable baseband modulator, according to the experimental results, offers a 6% complexity reduction and a 47% improvement in performance efficiency over the current SDR system.

An angle of arrival estimation method for intelligent metasurface using machine learning

Today, techniques for altering electromagnetic waves and the data they transport are increasingly crucial. These techniques have become increasingly important in several communication technologies, such as intelligent metasurface, with the rise and development of next-generation wireless communication systems. Since those technologies call for locating devices, angle of arrival (AoA) analysis becomes a crucial area for research. The AoA can now be shown in various ways, and some subspace methods have already achieved great precision. However, the extensive calculation required by those techniques is one of their key shortcomings. The author developed a novel radio frequency (RF) switching circuit design in this research and applied a novel machine-learning method to signal AoA. In single-wave settings, it was discovered that the proposed machine learning method performed satisfactorily with an average difference of 0.6 degrees.

Notice of Violation of IEEE Publication Principles: An Efficient Nonlinear Quantized Constant Envelope Precoding for Massive MU-MIMO Systems

Notice of Violation of IEEE Publication Principles <BR><BR>"An Efficient Nonlinear Quantized Constant Envelope Precoding for Massive MU-MIMO Systems," <BR>by R. Liang, H. Li, W. Zhang, C. Liu and Y. Guo, <BR>in IEEE Systems Journal, Early Access <BR><BR>After a careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. <BR><BR>This paper contains content from the papers cited below. Credit notices were used, but due to the absence of quotation marks or offset text, the copied content is not clearly referenced or specifically identified. <BR><BR>"VLSI Design of a 3-bit Constant-Modulus Precoder for Massive MU-MIMO," <BR>by O. Castañeda, S. Jacobsson, G. Durisi, T. Goldstein and C. Studer, <BR>in the Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS), May 2018 <BR><BR>"Quantized Precoding for Massive MU-MIMO," <BR>by S. Jacobsson, G. Durisi, M. Coldrey, T. Goldstein and C. Studer, <BR>in IEEE Transactions on Communications, vol. 65, no. 11, pp. 4670-4684, November 2017 <BR><BR> <br/> Massive multiuser multiple-input&#x2013;multiple-output (MU-MIMO) systems are foreseen as the key technology in next-generation wireless communication systems. However, many radio-frequency (RF) chains will require high power consumption and lots of hardware cost. One of the practical solutions is using low-resolution discrete phase shifters (PSs) for each antenna and RF chain. This article designs a nonlinear quantized constant envelope precoding algorithm for MU-MIMO systems with low-resolution discrete PS at the base station. In this algorithm, the quantized constant envelope precoding problem is presented as a nonconvex optimization problem. The multiuser interference is minimized by solving the optimal precoded vector and the associated precoding factors. First, we consider relaxing the nonconvex constraint on the 1-bit quantized constant envelope precoding to a continuous set of convex constraints on the unit circle. Afterwards, the semidefinite relaxation method is used to tackle the equivalent 1-bit quantized precoding problem. We further extend the algorithm to provide multi-bit quantized constant envelop precoding. Finally, the simulations are carried out under various conditions and compared with the most advanced precoding methods. The results demonstrate that this algorithm achieves a comparable performance to the existing precoding methods. At the same time, the corresponding performance-complexity tradeoff is more conducive to the expansion of the proposed algorithm to the multibit case.

Coordinate Interleaved OFDM With Repeated In-Phase/Quadrature Index Modulation

Orthogonal frequency division multiplexing with index modulation (OFDM-IM), which transmits information bits through ordinary constellation symbols and indices of active subcarriers, is a promising multicarrier transmission scheme and has attracted the attention of researchers due to numerous benefits such as flexibility and simplicity. Nonetheless, OFDM-IM cannot satisfy the needs of future wireless communication services such as superior reliability, high data rates, and low complexity. In this article, we propose a novel OFDM-IM scheme named coordinate interleaved OFDM with repeated in-phase/quadrature IM (CI-OFDM-RIQIM), which provides superior error performance and enhanced spectral efficiency due to its diversity order of two and clever subcarrier activation pattern (SAP) detection mechanism, respectively. In addition, CI-OFDM-RIQIM is further extended to coordinate interleaved OFDM with in-phase/quadrature IM (CI-OFDM-IQIM) by doubling information bits transmitted by IM. Furthermore, log-likelihood ratio (LLR) based low-complexity detectors are designed for both proposed schemes. Theoretical analyses are performed and an upper bound on the bit error probability is derived. Comprehensive computer simulations under perfect and imperfect channel state information (CSI), are conducted to compare the proposed and reference schemes. It is shown that CI-OFDM-RIQIM and CI-OFDM-IQIM show superior results and can be considered promising candidates for next-generation wireless communication systems.

Toward Sub-Terahertz: Space-Time Coding Metasurface Transmitter for Wideband Wireless Communications.

A space-time coding metasurface (STCM) operating in the sub-terahertz band to construct new-architecture wireless communication systems is proposed. Specifically, a programmable STCM is designed with varactor-diode-tuned metasurface elements, enabling precise regulation of harmonic amplitudes and phases by adjusting the time delay and duty cycle of square-wave modulation signal loaded on the varactor diodes. Independent electromagnetic (EM) regulations in the space and time domains are achieved by STCM to realize flexible beam manipulations and information modulations. Based on these features, a sub-terahertz wireless communication link is constructed by employing STCM as a transmitter. Experimental results demonstrate that the STCM supports multiple modulation schemes including frequency-shift keying, phase-shift keying, and quadrature amplitude modulations in a wide frequency band. It is also shown that the STCM is capable of realizing wide-angle beam scanning in the range of ±45o , which offers an opportunity for user tracking during the communication. Thus, the STCM transmitter with high device density and low power consumption can provide low-complexity, low-cost, low-power, and low-heat solutions for building the next-generation wireless communication systems in the sub-terahertz frequency and even terahertz band.

Deep Convolutional and Recurrent Neural-Network-Based Optimal Decoding for RIS-Assisted MIMO Communication

The reconfigurable intelligent surface (RIS) is one of the most innovative and revolutionary technologies for increasing the effectiveness of wireless systems. Deep learning (DL) is a promising method that can enhance system efficacy using powerful tools in RIS-based environments. However, the lack of extensive training of the DL model results in the reduced prediction of feature information and performance failure. Hence, to address the issues, in this paper, a combined DL-based optimal decoding model is proposed to improve the transmission error rate and enhance the overall efficiency of the RIS-assisted multiple-input multiple-output communication system. The proposed DL model is comprised of a 1-dimensional convolutional neural network (1-D CNN) and a gated recurrent unit (GRU) module where the 1-D CNN model is employed for the extraction of features from the received signal with further process over the configuration of different layers. Thereafter, the processed data are used by the GRU module for successively retrieving the transmission signal with a minimal error rate and accelerating the convergence rate. It is initially trained offline using created OFDM data sets, after which it is used online to track the channel and extract the transmitted data. The simulation results show that the proposed network performs better than the other technique that was previously used in terms of bit error rate and symbol error rate. The outcomes of the model demonstrate the suitability of the proposed model for use with the next-generation wireless communication system.

Sum-Rate Maximization for RIS-Assisted Integrated Sensing and Communication Systems With Manifold Optimization

Integrated sensing and communication (ISAC) is a key enabler for next-generation wireless communication systems to improve spectral efficiency. However, the coexistence of sensing and communication functionalities can cause harmful interference. In this paper, we propose to use a reconfigurable intelligent surface (RIS) in conjunction with ISAC to address this issue. The RIS is composed of a large number of low-cost elements that can adjust the amplitude and phase shift of impinging signals, thus providing a relatively high beamforming gain. To maximize the sum-rate of the communication system, we jointly optimize the beamformer at the base station (BS) and the phase shifts at the RIS, subject to a threshold on the interference power, the unit-norm constraint of the transmit power, and the unit modulus constraint of the RIS phase shifts. To efficiently tackle this NP-hard problem, we first reformulate the problem into a more tractable form using the fractional programming (FP) technique. Then, we exploit the geometrical properties of the constraints and adopt an alternating manifold-based optimization to compute the optimal active beamformer and the RIS phase shifts, respectively. Simulation results demonstrate that the proposed RIS-assisted design significantly reduces the mutual interference and improves the system sum-rate for the communication system.

6G TECHNOLOGY: PERSPECTIVES, PROBLEMS AND SOLUTIONS

The standardization procedure of the fifth generation communication has already been completed and global spread has launched. To maintain the competitive advantage of wireless communication, researchers conceptualize next-generation (6th generation, 6G) wireless communication systems aimed at founding the stratification of communication needs of the 2030s. This article highlights the most promising research areas in the recent literature on the overall trends of the 6G project to support this view. It discusses the development and analysis of 6G wireless communication technology, which is projected to be implemented in the near future. Networks based on 6G wireless technology seem to be the most promising and developing field in the field of wireless technology. The article indicates the emergence and development of 6G to lead to a new wave of developments in the field of the Internet of Things (IoT). It touches upon the services applied during the implementation of the previous generation (5th generation, 5G) technologies and the emerging problems. It also reviews the benefits and challenges associated with the development of 6G wireless communication, which is designed to provide a better communication system in the future and to get many new perspectives.

Reconfigurable VO2 metasurfaces with hybrid electro-optical control: manipulating THz radiation with 0.3 W/cm2 light.

Dynamicallyprogrammable metasurfaces capable of manipulating terahertz (THz) wavefronts in various manners depending on external controls are highly desired for next-generation wireless communication systems and new tools for THz diagnostics. Such metasurfaces may utilize the insulator-to-metal transition in V O 2, which can be induced both electrically and optically. Optical control is especially convenient for individual addressing to each meta-atom, but it is hampered by the high optical switching threshold of V O 2. We experimentally realize V O 2-based THz metasurfaces with hybrid electro-optical control when the metasurface is brought close to the transition point by an almost-threshold current, and then is easily switched by unfocused continuous-wave light. We were able to control the metasurface THz transmission by 0.4W/c m 2 near-IR light, while purely optical switching required tightly focused light with an intensity of >3×105 W/c m 2. After correcting for the fact that a tightly focused spot dissipates heat easier, we estimate that the optical switching threshold reduction due to the electric current alone is ∼2 orders of magnitude. Finally, coating the metasurface with Au nanoparticles further reduced the threshold by 30% due to plasmonic effects.

Metasurfaces for next-generation wireless communication systems.

Tailored time variations, nonlinearities and active elements can endow metasurfaces with unique opportunities for next-generation wireless communication systems, enriching the growing platform of reconfigurable intelligent surfaces.

Frequency-Selective Surface Based on Negative-Group-Delay Bismuth–Mica Medium

Negative group delay may be observed in dispersive media with anomalous dispersion in a certain frequency range. The fact that an outgoing wave packet precedes an incoming one does not violate the causality principle but is only a consequence of a waveform reshaping. This effect is observed in media such as photonic crystals, hyperbolic and epsilon-near-zero metamaterials, undersized waveguides, subwavelength apertures, side-by-side prisms, and resonant circuits at various frequencies. The current work is devoted to the design of a simple negative-group-delay medium with tunable properties in the THz frequency range. This medium consists of a bismuth-based frequency-selective surface on a dielectric substrate and may be tuned both statically and dynamically. While a geometry variation defines a main form of an effective permittivity dispersion and group delay/group velocity spectra, an external voltage allows one to adjust them with high precision. For the configuration proposed in this work, all frequency regions with noticeable change in group delay/group velocity lie within atmospheric transparency windows, which are to be used in 6G communications. This medium may be applied to THz photonics for a tunable phase-shift compensation, dispersion management in systems of THz signal modulation, and for encoding in next-generation wireless communication systems.

A Novel Collision Avoidance Strategy with D2D Communications for UAV Systems

In recent years, safety operation issues related to the autonomous flight of unmanned aerial vehicles (UAVs) have become popular research and development topics worldwide. Among all UAV applications, multiple UAV-related applications are emerging due to the integration of UAVs into 6G networks, which is an important topic for next-generation wireless communication systems. For multiple UAV applications, flight safety among UAVs is the most significant issue. Therefore, collision avoidance for UAVs has become an emerging topic in UAV-related research. In the past, although many UAV collision avoidance methods have been proposed, there is still a probability of other problems, such as no possible avoidance route and unmanaged UAVs that are without centralized control, which both result in an unpredictable risk of collisions. In this study, we investigate the current existing methods and propose novel collision avoidance methods based on the elastic collision principle. To verify the performance of the proposed methods, we also conduct simulations in this paper to demonstrate their effectiveness. From the simulation results, it can be seen that the proposed methods can effectively perform collision avoidance for multiple UAVs. Specifically, using the proposed methods, all UAVs can reach their destination points within reasonable time resources without any collision, validating the effectiveness of the proposed methods.

Multi Frequency Controllable In-Band Suppressions in a Broad Bandwidth Microstrip Filter Design for 5G Wi-Fi and Satellite Communication Systems Utilizing a Quad-Mode Stub-Loaded Resonator

The key elements used for receiving and processing signals in communication systems are the bandpass filters. Initially, a common operating mechanism was applied for the design of broadband filters, i.e., by cascading low-pass filters or high-pass filters using multiple line resonators with length quarter-half- or full-wavelength with central frequency, but using these approaches, the design topology becomes expensive and complex. The above mechanisms can be possibly overcome using a planar microstrip transmission line structure due to its simple design fabrication procedure and low cost. So, pointing out the above problems in bandpass filters such as low-cost, low insertion loss, and good out-of-band performance, this article presents a broadband filter with multifrequency suppression capability at 4.9 GHz, 8.3 GHz, and 11.5 GHz using a T-shaped shorted stub-loaded resonator with a central square ring coupled to the basic broadband filter. Initially, the C-shaped resonator is utilized for the formation of a stopband at 8.3 GHz for a satellite communication system, and then a shorted square ring resonator is added to the existing C-shaped structure for the realization of two more stopbands at 4.9 GHz and 11.5 GHz for 5G (WLAN 802.11j) communication, respectively. The overall circuit area covered with the proposed filter is 0.52 λg × 0.32 λg (λg is the wavelength of the feed lines at frequency 4.9 GHz). All the loaded stubs are folded in order to save the circuit area, which is an important requirement of next-generation wireless communication systems. The proposed filter has been analyzed using a well-known transmission line theory, even–odd-mode, and simulated with the 3D software HFSS. After the parametric analysis, some attractive features were obtained, i.e., compact structure, simple planar topology, low insertion losses of 0.4 dB over the entire band, good return loss greater than 10 dB, and independently controlled mutli stopbands, which make the proposed design unique and can be used in various wireless communication system applications. Finally, a Rogers RO-4350 substrate is selected for the fabrication of the prototype using an LPKF S63 ProtoLaser machine and then measured using a ZNB20 vector network analyzer for matching the simulated and measured results. After testing the prototype, a good agreement was found between the results.

Spectrum sensing-focused cognitive radio network for 5G revolution

The cognitive radio network (CRN), an instrumental part of the next-generation wireless communication systems, is mainly dependent on spectrum sensing to function properly. The radio spectrum can help in clean energy transition and load capacity factors by providing a more efficient and accurate spectrum utilization. By using it, the number of spectrums that is used for communication can be optimized, which can reduce the amount of energy consumed by the network. Additionally, 5G radio spectrum sensing can be used to identify and classify different types of signals, which can help reduce the amount of interference in the network and improve the efficiency of energy utilization. It can also allow for the digitization of clean energy infrastructure and facilitate better decision-making processes that take into account environmental impacts while optimizing energy use because of its efficient characteristics like non-linearity, detection, scalability, robustness, generalization, non-stationarity in wireless environments, dynamic entity, weighted sum of Gaussian functions centered at specific frequencies, and robustness against noise and interference. It can adapt to noise and interference by adjusting its parameters, and this allows accurate distinguishing between primary and secondary users in the wireless spectrum, which is why a radial basis function is a popular choice for spectrum sensing in 5G networks. Radial basis function networks (RBFNs) can work better in 5G spectrum sensing for better signal classification, dynamic adaptation, fast detection, faster decision-making, and improved noise and interference reduction. One of the most sought-after goals in the field of wireless research is the creation of spectrum-sensing technology that is dependable and intelligent because multilayer learning approaches are inappropriate for dealing with time-series data due to the higher misclassification rate and inherent computational complexity. To address this, the study proposed the radial basis function network that learns the temporal aspects from spectral data and makes use of additional environmental statistics such as frequency, efficiency, energy, spectrum allocation, distance, and duty-cycle time, which are considered environmental data that may be used to fine-tune sensor performance. The scheme is simulated with real-time parameters, and the results are quite promising in terms of evaluation parameters.

Performance of IRS-Aided FD Two-Way Communication Network With Imperfect SIC

Intelligent reflecting surface (IRS) is a promising technology to deploy reconfigurable and cost-effective next-generation wireless communication systems. In this work, we investigate the performance of an IRS-aided two-way communication network over Rayleigh fading channels, where downlink and uplink transmission between the base station and the user equipment is established in full-duplex mode. We take into account the impact of residual self-interference (RSI), which results from imperfect self-interference cancellation. We derive the analytical expressions of outage probability (OP), asymptotic OP, and obtain diversity order of the system. We also derive ergodic capacity in terms of the Meijer-G function. Further, we derive the analytical expressions of average symbol error rate (ASER) for general order rectangular quadrature amplitude modulation (QAM), cross QAM, and hexagonal QAM. We highlight the impact of reflecting elements, RSI, and other system parameters on the performance of the considered network and also compare the ASER of various QAM constellations. Finally, Monte-Carlo simulations validate the derived analytical expressions.