Future Generation Wireless Networks Research Articles

Relay Assisted Device-to-Device Communication for Future Generation Wireless Networks: A Review from Architectural and Challenges Perspective

The rapid evolution of wireless communication technologies, along with the increasing demand for efficient and reliable data transfer, has driven the rethinking of traditional cellular network architectures in the context of next-generation networks. In conventional cellular systems, communication between users typically occurs through base stations. However, to improve efficiency, scalability, and spectral utilization, device-to-device (D2D) communication has been introduced, enabling direct data transmission between users without base station involvement. In this paper, we present a comprehensive review of D2D communication from architectural and challenges perspective for future generation networks. Additionally, the study focuses on relay-assisted D2D (RAD2D) communication, examining the role of machine learning (ML) and artificial intelligence (AI) in optimizing relay selection processes. In light of the existing literature, challenges for implementing RAD2D are discussed from different perspectives such as relay selection, energy efficiency, secure communication, resource allocation, and the management of dynamic network conditions

A Review on Machine Learning Assisted Handover Mechanisms for Future Generation Wireless Networks

A Review on Machine Learning Assisted Handover Mechanisms for Future Generation Wireless Networks

Development of hybrid sewing training-based dingo optimization algorithm for massive MIMO spectral efficiency maximization system

ABSTRACT A Base Station (BS) with several antenna elements serves a number of users in the frequency of the same time- slot in a huge multiuser “Multiple-Input Multiple-Output (MIMO)”. It has emerged as a viable method for the future generation of wireless networks due to its capacity to enhance both spectrum and efficiency of energy, even with straightforward linear processing like “Maximum Ratio Combining (MRC), Linear Minimum Mean Square Error (LMMSE) and Zero Forcing (ZF)”. In a power allocation scheduling method, only users who do not interfere with one another can change their power at any one time. These studies all take into account orthogonal channels. However, the “Spectral Efficiency (SE)” is reduced by the channels’ non-orthogonality. This encourages us to research how to maximize spectral efficiency in “Massive MIMO (M-MIMO)” systems by allocating power for both uplink and downlink transmission. Here, the Hybrid of Sewing Training and Dingo Optimization (HSTDO) is developed for executing the best resource allocation in the M-MIMO system to improve SE performance which helps to enhance the SE of the M-MIMO system. The simulation is carried out to compare the developed model with the conventional works to reveal the better spectral efficiency of the suggested algorithm.

A Survey on Throughput Maximization in IoT Networks

This paper presents a comprehensive survey on Non-Orthogonal Multiple access for multiple access in wireless networks. As networks are now migrating towards the wireless domain as opposed to the wired domain, the need for more efficient bandwidth allocation mechanism is necessary. With the advent of big data applications, increasing number of users, increased bandwidth and data requirement yet limited bandwidth availability have become serious challenges. Hence future generation wireless networks would need improved multiple access techniques than their present day counterparts. Non-Orthogonal Multiple access is a technique in which multiple users data is separated in the power domain. The problems addressed by NOMA are low overall bandwidth for multiple users. This paper presents a comprehensive review and taxonomy of the NOMA based multiple access framework. Index Terms:- Non-Orthogonal Multiple Access, Wireless Networks, Quality of Service (QoS), Bit Error Rate, Throughput.

THz graphene-integrated metasurface for electrically reconfigurable polarization conversion

Abstract Terahertz (THz) waves have been widely hailed as a key enabling technology for future sixth generation (6G) wireless networks. Dynamic modulation of their polarization states is of great attraction for high-capacity communications and anisotropic sensing. The development of such technology is, however, still in very early stage owing to the difficulties of realizing electrical reconfigurability for THz devices. Artificially constructed metasurfaces and new nanomaterials, such as graphene, have been shown to provide revolutionary platforms for manipulating and controlling the wave properties, especially at THz frequencies. This work leverages the light–matter interaction in a graphene-integrated metasurface functioning as an electrically reconfigurable THz polarization converter. A novel graphene-gold bilayer topology is applied to construct such a metasurface which enables wide-range electrical tunability of the polarization conversion. Under a y-polarized illumination, the reflected components of x- and y-polarizations are tuned dynamically through an external bias voltage across the metasurface, thereby producing an elliptically polarized wave with tuneable ellipticity and angle. By changing the voltage from 0 V to 12 V, the reflected polarization ellipticity has been tuned from −0.94 to −0.5 at around 240 GHz, featuring linear-to-circular and linear-to-elliptical polarization conversions. Meanwhile, the polarization angle has been modulated from 12° to −23° at around 236 GHz. This work provides an experimentally validated THz graphene-integrated metasurface with wide polarization modulation depths, low biasing voltages and simple configuration. It promises great potential for applications in future THz communications and sensing.

Massive capacity of novel three‐dimensional OCDMA‐FSO system for next generation of high‐data wireless networks

AbstractThe present study examines an interesting wireless system known as spectral/temporal/spatial‐optical code division multiple access‐free space optics (OCDMA‐FSO) by integrating the new three‐dimensional successive weight (3D‐SW) code for the incoherent system. The system is proposed to be adopted in future generations of wireless networks in view of its attractive features such as simple architecture, high data rate, strong immunity against electromagnetic interference, and optimal power consumption. Furthermore, the recommended code has a zero cross‐correlation (ZCC) feature that removes multiple access interference (MAI) and lowers the effect of phase‐induced intensity (PIIN) noise, which primarily affects OCDMA performance. Meanwhile, an original bit error rate (BER) formulation based on the signal‐to‐noise ratio (SNR) calculation has been developed. The computational results clarified that a recommended approach improves optical system efficacy by boosting numerous analytical criteria. Firstly, the numerical outcomes exhibit that the proposed system improves cardinality by 3.67, 3.08, 2.19, and 5 times than the systems using three‐dimensional perfect difference (3D‐PD), both three‐dimensional perfect difference/multi diagonal (3D‐PD/MD) and three‐dimensional‐dynamic cyclic shift/multi diagonal (3D‐DCS/MD), two‐dimensional‐SW, and one‐dimensional‐SW codes, respectively. Further, It saves roughly −7.3 dBm and − 4.2 dBm when moving from (1D) and (2D) to (3D). Second, the implementation of the proposed model under Optisystem software reveals that the system is compatible with optical communication norms and can be used in upcoming generations of wireless networks, where it achieves BER of with better transmission quality reaching 12.09 at a high bit rate until 30 Gbps across a wireless distance up to 6 km.

Joint Active-Passive Beamforming and User Association in IRS-Assisted mmWave Cellular Networks

Intelligent reflecting surfaces (IRSs) are a promising technology for future-generation wireless networks by extending coverage region to blind spots and increasing mmWave propagation paths in non-line of sight environments. User association (UA) in dense millimeter wave (mmWave) networks is vital to characterizing connections among base stations (BSs) and mobile users for load balancing, interference management, and maximizing network utility. However, it has yet to be examined thoroughly in a multi-IRS-aided network. This paper presents a new UA scheme that takes cell interference into account for a multi-cell mmWave cellular network aided with multiple IRSs. We formulate a network spectral efficiency maximization problem by jointly optimizing active beamforming (AB) at the BSs, passive beamforming (PB) at the IRSs, and user-BS association with consideration of the impact of IRSs. We then propose a computationally efficient iterative algorithm based on alternating optimization (AO) to resolve this intractable mixed-integer non-convex problem. A fractional programming technique is used to optimize active beamforming at the BSs and passive beamforming at the IRSs, and a penalization method combined with successive convex programming is applied for UA optimization, which is shown to reach the optimal solution. Simulation results show significant performance improvements obtained by the proposed algorithm, providing higher spectral efficiency compared to several benchmark algorithms, while having a low computational complexity.

Hybrid Multiple Access for Network Slicing Aware Mobile Edge Computing

Meeting huge traffic demand with resource constraints imposes a significant challenge for future generation wireless networks. In this work, we propose to utilize limited resources in a dense mobile edge computing (MEC) network to compute user equipment (UE) tasks through a novel hybrid multiple access (HYMA) scheme that employs both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA). The main purpose of using HYMA is to reduce the co-channel interference incurred in NOMA by selectively deploying OMA while maintaining the required signal-to-interference ratio. We adopt partial offloading of computing tasks in the MEC network. We also employ network slicing to efficiently utilize the resources of the MEC network to meet different types of application requirements. We prioritize NOMA to increase spectral efficiency as well as energy efficiency. We first formulate a mixed integer nonlinear programming (MINLP) optimization problem to minimize the total energy consumption for both local computing and wireless transmission of the MEC network and propose an algorithm consisting of three parts (UE association, computing resource allocation, and wireless resource and uplink transmission power allocation) to solve the MINLP problem with less computational complexity. We demonstrate the viability of our solution via extensive simulations.

Simultaneous Terahertz Imaging With Information and Power Transfer (STIIPT)

Terahertz (THz) band transmission has the potential to revolutionize future-generation wireless networks by jointly meeting communication and non-communication demands of their connected devices. Recent advances in THz semiconductor technologies and antenna design are closing the THz band gap in millimeter-scale devices which are often battery-limited. The localization of these mobile devices in future wireless networks is of paramount significance for beamforming to overcome THz propagation loss. Consequently, prospective signal processing techniques with co-design architectures are emerging either for joint communication and sensing or for simultaneous information and power transfer. In this paper, we present a novel approach toward Simultaneous Terahertz Imaging with Information and Power Transfer (STIIPT) from a base station transceiver to an Integrated Receiver (IntRx). Leveraging the proposed non-linear rectenna model for energy harvesting, a customized On-Off Keying (cOOK) modulation scheme is proposed for simultaneous communication through a non-linear THz channel while generating a radar-like image to localize the IntRx acting as a target. The proposed theoretical models are corroborated with simulations using a THz band GaAs Schottky diode to demonstrate STIIPT performances which also emphasize the significance of ranging information to optimize rate–energy transfer tradeoff under the cOOK modulation scheme.

Design methodology for reconfigurable multi-radio platform for future generation wireless systems

Owing to the continuous development of technology, the future generation of wireless communication systems is increasingly becoming more complex to support a spectrum of new and existing services and standards. Consequently, the need for flexible and adaptable radios has become more prominent. Radio signals can be modulated using various methods. Radio modulation recognition refers to a series of processes for acquiring information regarding modulation types of non-cooperative received signals. It plays an important role as a pre-demodulation process required to ensure accuracy, safety, and effectiveness in recovering information. This study proposed a reconfigurable multi-radio platform comprising a reconfigurable antenna and receiver board. The antenna was reconfigurable to facilitate operation in different frequency bands controlled via the receiver board using bias voltages. The receiver board was programmable using custom-built software. Moreover, it can detect the modulation scheme and accurately demodulate signals that are modulated in one of three common modulation schemes: amplitude modulation, frequency modulation, and phase modulation. This solution offers the advantages of reduced size, cost, and power consumption because it uses one hardware system as opposed to the deployment of several individual radios. Moreover, the platform presents an adaptable, cost-effective solution for future-generation wireless networks and a flexible and robust terminal that can operate under changing communication environments.

Fuzzy Based Network Controlled Vertical Handover Mechanism for Heterogeneous Wireless Network

In future next Generation wireless networks, it is expected to have multi-mode wireless interface devices with common IP core communication. The user will be having multiple option of radio access technology (RAT) for data and voice service. This multi-mode provides the terminal seamless mobility across the heterogeneous wireless network. Mobile terminals transferring their communication sessions from one RAT to other, such transferring ongoing call process is known as vertical handover. With the rise in popularity of multimode mobile devices, switching between networks will be in high demand for users to move seamlessly through the network, either because users were moving away from an access point or because the network currently does not provide quality. service (QoS), but in both situations, a better network should be available, so a good network selection algorithm should take into account the possibility of multiple users performing a handover simultaneously in the same area. The objectives of this paper are to develop a handover mechanism that Provides good quality of service to the end user.

Network Slicing for NOMA-Enabled Edge Computing

The 5G network presents a new horizon with tremendous opportunities for future generation wireless networks. Mobile edge computing (MEC), non-orthogonal multiple access (NOMA), and network slicing (NS) are some of the key enablers for 5G. MEC reduces the latency to a great extent for a wireless network, while NOMA gives access to more users with resource constraints. NS provides users with a better quality of service and network operators with more flexibility. In this work, we propose an NS technique enabled with NOMA for a MEC network. The proposed NS technique improves service latency for MEC users and reduces the unnecessary allocation of radio resources in NOMA. The saved resources can be leveraged to accommodate more users, thus increasing the spectral efficiency of the network. We consider different types of services based on the task completion time of users in this work. The primary focus is to optimize the total energy consumption for wireless uplink transmission for the NOMA-enabled sliced MEC network. We also propose a heuristic algorithm as an alternative to reduce the time and computational complexities of the optimization algorithm and simulate the results extensively to show the effectiveness of our proposed algorithm.

Functional Security and Trust in Ultra-Connected 6G Ecosystem

Security and trust are the entangled role players in the future generation of wireless networks. Security in 5G networks is currently supported using several functions. Given the advantages of such a system, this article explores the functional security and trust for the 6G ecosystem with ultra-connectivity. Several associated challenges, application-specific domains, and consumer issues related to 6G security are discussed. The article highlights the network security-by-design and trust-by-design principles and performance expectations from the security protocols in supporting handover in an ultra-connected scenario. Finally, potential research directions are presented for a road towards the 6G ecosystem.

Implementation of RWP and Gauss Markov Mobility Model for Multi-UAV Networks in Search and Rescue Environment

Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms. In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are described in depth, together with the movement patterns they are related with. Furthermore, two-simulation scenarios conduct with help of an NS-3 simulator. The first scenario investigates the effect of UAV Speed by varying it from 10 to 50 m/s. the second scenario investigates the effect of the size of the transmitting packet by varying it from 64 to 1024 bytes. The performance of GM and RWP was compared based on packet delivery ratio (PDR), goodput, and latency metrics. Results indicate that the GM model provides the highest PDR and lowest latency in such high mobility environments.

Multicarrier technique for 5G massive MIMO system based on CDMA and CMFB

Filterbank multicarrier (FBMC) is an effective method for modulation over massive multiple-input multiple-output (MIMO) channels in the future fifth generation wireless networks. This multicarrier technique provides high spectral efficiency, and it is resilient against synchronization errors compared to the well-known orthogonal frequency division multiplexing technique. This paper introduces a new technique, that combines the Code-division multiple-access (CDMA) and cosine modulated filter banks, a specific class of FBMC, to massive MIMO communication systems. In the proposed technique, the data symbols are transmitted on different sub-bands and also, they are spread in each sub-band by CDMA code. The proposed technique reduces the interference between data symbols, which consequently improves bit-error-rate (BER) performance. Simulation results show that the overall BER performance of the proposed multicarrier transmission technique is significantly enhanced. The results obtained show that as the number of base station antennas increases, different channel distortions are averaged out, thus BER decreases (in average by 10–2) for the same signal-to-noise ratio.

Comprehensive Performance Analysis of Hovering UAV-Based FSO Communication System

Unmanned-aerial-vehicle (UAV)-based communications are expected to play an important role in the future generation wireless communication networks. It is a promising solution to enhance the wireless connectivity of devices without infrastructure. As compared to the terrestrial communications, UAVs offer various advantages such as line-of-sight (LoS) connectivity, dynamic deployment and flexible reconfiguration. Further, free space optics (FSO) communication is considered as a possible solution to enable UAV-based communication links due to its cost effective and high bandwidth nature. However, despite offering large bandwidth, UAV-based FSO links are marred by atmospheric path loss, atmospheric turbulence, non-zero boresight pointing errors, and angle-of-arrival (AoA) fluctuations. In this paper, the performance of a hovering UAV-based FSO communication system is investigated. The closed-form expressions for outage probability, average symbol error rate (SER), and ergodic capacity are derived taking into account both heterodyne (HD) and direct detection (DD) techniques for ground-to-UAV (G2U), UAV-to-UAV (U2U), and UAV-to-ground (U2G) links over the generalized Málaga distribution. Moreover, the asymptotic expressions for the above performance metrics are also derived to get the diversity gain of the system.

A Usage Aware Dynamic Spectrum Access Scheme for Interweave Cognitive Radio Network by Exploiting Deep Reinforcement Learning.

Future-generation wireless networks should accommodate surging growth in mobile data traffic and support an increasingly high density of wireless devices. Consequently, as the demand for spectrum continues to skyrocket, a severe shortage of spectrum resources for wireless networks will reach unprecedented levels of challenge in the near future. To deal with the emerging spectrum-shortage problem, dynamic spectrum access techniques have attracted a great deal of attention in both academia and industry. By exploiting the cognitive radio techniques, secondary users (SUs) are capable of accessing the underutilized spectrum holes of the primary users (PUs) to increase the whole system’s spectral efficiency with minimum interference violations. In this paper, we mathematically formulate the spectrum access problem for interweave cognitive radio networks, and propose a usage-aware deep reinforcement learning based scheme to solve it, which exploits the historical channel usage data to learn the time correlation and channel correlation of the PU channels. We evaluated the performance of the proposed approach by extensive simulations in both uncorrelated and correlated PU channel usage cases. The evaluation results validate the superiority of the proposed scheme in terms of channel access success probability and SU-PU interference probability, by comparing it with ideal results and existing methods.

An efficient SLM technique based on chaotic biogeography-based optimization algorithm for PAPR reduction in GFDM waveform

ABSTRACT High data rates, extremely low power consumption, and minimal end-to-end latency are considered to be mandatory requirements for 5G wireless networks. Rapid improvements in design and performance of 5G physical layer waveforms have become necessary. The drawback of Orthogonal Frequency Division Multiplexing (OFDM) is high PAPR, that causes signal distortion, which reduces system efficiency. Generalized frequency division multiplexing (GFDM) is a promising non-orthogonal multicarrier transmission scheme, which has recently received a great deal of attention towards future fifth generation (5G) wireless networks. It overcomes the limitations of orthogonal frequency division multiplexing (OFDM), while preserving most of the advantages of it. Selective Level mapping (SLM) is one of the PAPR reduction techniques, that uses the phase shift technology. In this paper, SLM based on Chaotic Biogeography Based Optimization (CBBO) algorithm is proposed to offer an efficient solution to the problem of high PAPR, existing in the GFDM waveforms. Experimental results prove that, the proposed CBBO–SLM technique provides significant improvement in terms of PAPR reduction, as compared to the conventional SLM methods, such as conventional GFDM and OFDM-SLM. The proposed novel scheme is most suitable for QAM and QPSK applications, as it provides good PAPR reduction performance, at lower computational complexity.

Mode division multiplexing free space optics system with 3D hybrid modulation under dust and fog

Mode division multiplexing (MDM) is an emerging information transmission technique in which multiple data signals can be transmitted simultaneously on different modes of a single wavelength laser beam over a free-space channel. MDM is a potential technique for the realization of high-speed spectral efficient communication links for future generations of wireless networks. We present a novel MDM-based free-space optics (FSO) system. The system integrates a 3D hybrid modulation scheme produced by combining carrier suppressed-non-return-to-zero (CSNRZ), differential quadrature phase-shift keying (DQPSK), and polarization shift keying (PolSK) modulation schemes for beyond 100 Gbps applications. Three unrelated 40 Gbps data signals are modulated and transmitted on one optical carrier utilizing three distinct signal properties: amplitude (CSNRZ), phase (DQPSK), and polarization state (PolSK). The proposed 3D modulation scheme offers a high-capacity system, where each channel transmits 4 Gbps as compared to 1 Gbps in the case of OOK modulation. MDM using distinct Hermite Gaussian modes: (HG00 and HG01) of a laser beam is incorporated to boost the spectral efficiency and information rates of the FSO link. The proposed 120 Gbps single-channel MDM-FSO link performance is examined under the impact of different levels of dust and fog environmental conditions using quality factors and received eye diagrams as the performance metrics. This system achieved optimal performances up to 1250 m (very light dust), 540 m (light dust), 170 m (moderate dust), 750 m (low fog), and 425 m (medium fog). In the worst-case scenario, the system manages to work up to a 67 m range in dense dust with a maximum attenuation of 297.38 dB/km and a 200 m distance in heavy fog with only 90 dB/km attenuation which is less than 1/3rd of the attenuation measured for dense dust event. In addition, our results and the case studies confirm that dust introduces greater signal attenuation than fog. Therefore, an encounter with a dust environment should be considered as the bottleneck issue for FSO links. The creative contribution of this paper is to put forward a bandwidth-efficient MDM-FSO-enabled B5G system that could be deployed in harsh and challenging locations at reduced visibility. This is expected to be further technically sustainable owing to the use of advanced 3D hybrid optical orthogonal modulation and therefore find use in implementing 5G and 6G cellular and data networks.

Performance analysis of Heterogeneous Cloud-Radio Access Networks: A user-centric approach with network scalability

Heterogeneous cloud-radio access network (HC-RAN) is a very promising network architecture for future generation wireless communication systems. The centralized computation of HC-RAN provides flexibility to coordinate multi-point (CoMP) transmission of remote radio heads (RRHs). These RRHs can cooperatively form static or dynamic clusters which are network-centric or user-centric to serve the user equipment (UE). To meet the demands of future generation wireless networks, the user-centric approach is gaining much attention, especially in dynamic clustering. In dynamic user-centric CoMP, a set of overlapped clusters can cooperate dynamically to serve UEs. In a large network, the main challenge is the scalability of the computational complexity and fronthaul load with the increase of the number of UEs. To address this, we developed a scalable user-centric HC-RAN by utilizing dynamic cooperation clustering (DCC) framework. We presented an algorithm for joint user association, resource allocation, and cluster formation. We derived the expressions for different combining and precoding vectors to satisfy the scalability condition. We evaluated the performance of the scalable user-centric HC-RAN in terms of the achievable rate per UE at two different levels of cooperation with imperfect channel state information (CSI). The performance of the derived schemes is nearly optimal compared to the unscalable benchmark schemes and the ideal scalable system.