5G Spectrum Research Articles

Dynamic spectrum resource allocations in wireless senor networks for improving packet transmission

Spectrum allocation has gained a lot of attention in cognitive wireless networks and research as one of the key problems for enhancing spectrum quality in the communication processes in the contemporary communication-dependent wireless environment. By effectively managing the restricted spectrum resources, adjusting to dynamic network conditions, lowering interference, and increasing energy efficiency, the study on dynamic spectrum allocation in wireless sensor networks seeks to improve packet transmission. In a variety of applications, this improves network performance, dependability, and quality of service. This is the reason we apply the dynamic source allocation to the sensor nodes in the network visualization for the packet transmission performance study in the 5G spectrum region. The primary goal of the study conducted for this article is to improve packet delivery ratios and data packet throughputs from the source to the destinations. Compared to previous research, this work has achieved 100% of its aims. In this context, certain DRL concerns are also addressed. The spectrum is allotted such that, in the event of phishing or malicious nodal assaults on the cluster groups of the wireless sensor nodal points in the WSN, efficient packet transmission will occur, beginning at the source and terminating at the sink. The simulation results demonstrate the efficacy of the approach described in the research paper and its application to data transmission.

Enhanced Antipodal Vivaldi Antenna with SSRR metamaterial for improved 5G performance in the 38 GHz band

This study involves the integration of a compact Antipodal Vivaldi Antenna (AVA) with a square-shaped split ring resonator (SSRR) metamaterial to achieve improved performance, specifically in the 38 GHz band of 5G applications. The compact antenna is fabricated on Roger's substrate 5880 with 20 x 6 x 0.5 mm3 dimensions. The operational frequency ranges from 34 GHz to 43.8 GHz, catering to the specific needs of the 5G spectrum. To optimize the antenna's performance, corrugations are strategically introduced in the flares of the AVA, resulting in a notable improvement in the front-to-back ratio (FBR) by 18.35 dB. Additionally, square-shaped split ring resonators (SSRRs) are integrated into the AVA aperture, contributing to a gain enhancement of 4.6 dBi. The overall design achieves a gain ranging from 9.2 dBi to 10.4 dBi across the 38 GHz frequency band. The proposed AVA demonstrates good characteristics, with the highest front-to-back (FBR) value recorded at 20.4 dB at 40.6 GHz. The FBR consistently exceeds 15.6 dB throughout the specified frequency range. The antenna design is fabricated, simulated, and experimentally verified, affirming its suitability for compact 5G devices. The results indicate that the proposed miniaturized AVA, incorporating SSRR metamaterial and optimized flare corrugations, is an efficient candidate for compact 5G devices, offering enhanced gain and FBR over the desired frequency band.

Design and performance analysis of a novel miniaturized band-stop filter for band rejection in Sub-6 GHz 5G spectrum

This paper introduces an innovative band stop filter specifically designed to reject a sub-6GHz band within the 5 G spectrum. Fabricated on an FR4 substrate with a relative permittivity of 4.4, the filter incorporates a defected ground structure (DGS) and features very compact dimensions of 19 mm × 11 mm × 0.8 mm. The filter design is performed using the High Frequency Structure Simulator (HFSS). Besides, the filter’s equivalent circuit is modeled using the ANSYS circuit editor. A parametric study has been conducted to identify the optimal parameters for the filter’s form and size. The proposed filter exhibits a rejected band of 1.42 GHz, spanning from 2.3 GHz to 3.72 GHz, with a center frequency of 3.18 GHz. Within the rejected band, the S21 value is less than −21.36, and the stop band fractional bandwidth (FBW) is 44.65%. Additionally, the filter demonstrates a negative group delay (NGD) characteristic in the frequency range of 2.97 GHz to 3.35 GHz, with a measured NGD time of −0.42 ns, and a quality factor equal to 2.24. These results underscore the filter’s suitability for applications utilizing frequencies below 2 GHz and above 3 GHz, ensuring efficient functionality.

Sqrt-Loglogish CNN and Markov model for 5G spectrum sensing application

The research presents innovative methods for spectrum sensing in 5G networks, using the Sqrt-Loglogish convolutional neural network (SL-CNN) and hidden orthogonal intuitionistic fuzzy Markov model (HOIFMM). The proposed methods aim to tackle issues related to detecting principal user signals accurately, mitigating interference, and efficiently utilizing the spectrum in wideband spectrum environments due to their diverse and ever changing characteristics. The Sqrt-Loglogish CNN improves spectrum sensing by addressing static threshold dependency and potential overfitting. The HOIFMM offers a complex framework for predicting sparsity levels and primary user patterns. The results highlight the effectiveness of the suggested techniques in differentiating primary user signals from noise and interference, resulting in enhanced interference management tactics and overall network performance. MATLAB simulation is performed and compared the proposed methods performance with existing state-of-the-art methods such as CNN, deep neural network (DNN), long short-term memory (LSTM) and artificial neural networks (ANN). The proposed method has outperformed existing methods in terms of sensitivity, accuracy, and precision. Future endeavors include improving these methods, investigating sophisticated machine learning algorithms, and doing real world validations to guarantee scalability and resilience in various 5G deployment situations. This research advances the spectrum sensing capabilities in 5G networks, potentially improving efficiency, reliability, and quality of service.

Gain enhancement of mm-wave antenna using graded index lens integrated frequency selective surface for 5G NR FR2 applications

In this study, the gain of a printed antenna is boosted for utilization in 5G systems by employing a phase-oriented graded index-type lens system. In the prescribed design, various metamaterial unit cells are arranged as arrays with radial phases for the graded meta lens to optimize transmission characteristics. The suggested arrangement creates a meta lens with spatially varying surface impedance and locally varying refractive index, allowing the conversion of spherical wavefronts into planar wavefronts for beam collimation in the 5G band. The focal length-to-diameter ratio (f/d) is fixed at 0.38 in this prescribed design. The integration of the FSS structure with the patch antenna enhances the efficiency above 98% and increases gain by 2.635dBi owing to the focusing effect of the properly placed lens. The prescribed planar lens is easy to realize during manufacturing compared to 3D lenses. The meta lens integrated patch yields a gain of around 8.936dBi at 29 GHz. The performance of the lens antenna is evaluated through simulation studies and then validation of results is performed with experimental arrangement to ensure accuracy and reliability of the suggested methodology for gain enhancement of the functioning antenna at FR2 5G spectrum.

Novel metamaterial array-based dual port MIMO antenna using low profile substrate with feature multiband, and high isolation for sub-6G, IoT, and WiMAX applications

This article represents a single-layered two-port MIMO antenna loaded into a compact plane-patterned metamaterial (MTM) structure for a 5G communication system. The antenna operates at three bands to investigate metamaterial properties in addition to diversity parameters, an arrangement of a series of arrays suggested a 2-port design antenna and a circular-shaped split ring resonator unit cell was developed. The design of a single port antenna utilizes 1 × 3 MTM unit cells for each component. This antenna operates within a frequency range ranging from 1 GHz to 15 GHz. Additionally, the suggested MIMO antenna offers a dominant isolation of –55dB. The measurement’s results show that, with an entire antenna size of 112 mm × 26.5 mm and a 3.33 GHz bandwidth, the MIMO antenna is achieved with good efficiency and CCL < 0.35, considerable DG > 9.97dB, ECC < 0.18, and TARC <–9.97. The presented design is suitable for medical imaging, RFID, Bluetooth, Wi-Fi, WiMAX, IOT, satellite communication systems, and the 5G and sub-6 GHz spectrum.

Optimization of resource allocation in 5G networks: A network slicing approach with hybrid NOMA for enhanced uRLLC and eMBB coexistence

SummaryTraditional Orthogonal Multiple Access (OMA) and spectrum sharing methods struggle to provide the diverse quality of service (QoS) demands for enhanced mobile broadband (eMBB), ultra‐reliable low latency communications (uRLLC), and massive machine type communications (mMTC) leading to suboptimal performance and service quality degradation. Single‐carrier‐non‐orthogonal multiple access (SC‐NOMA) appears to be a more optimized solution. It can serve multiple users simultaneously on the same time‐frequency resources. This approach offers both enhanced spectrum efficiency and meets the QoS requirements for the coexistence of eMBB, uRLLC, and mMTC. However, SC‐NOMA has some drawbacks. Decoding a user's signal involves a complex successive interference cancellation (SIC) process that gets harder with more users causing delays and errors. Additionally, strong user signals can interfere with weaker ones, limiting the number of users per channel. In order to overcome the drawbacks associated with OMA and SC‐NOMA, this paper introduces a new method called user‐paired NOMA (hybrid NOMA). Hybrid NOMA adopts a strategic approach, employing two user pairing techniques: near‐far/far‐near (NF‐FN) and near‐near/far‐far (NN‐FF). NF‐FN pairing prioritizes users with similar signal strengths but different distances from the base station. This minimizes interference for the weaker user during SIC. NN‐FF pairing, on the other hand, groups users with similar signal strengths and proximity. This approach further simplifies SIC and minimizes potential interference altogether. The simulation results demonstrate trade‐offs between eMBB and uRLLC performance. OMA suffers with dedicated resource allocation, while SC‐NOMA balances performance but experiences interference. NN‐FF prioritizes eMBB and offers best latency, while NF‐FN prioritizes uRLLC with high spectral efficiency but suffers from higher latency. Finally, by providing a thorough grasp of how hybrid NOMA resource allocation works to improve the performance of various use cases, this research makes a significant contribution to the field of 5G spectrum optimization.

Quad-Band 1 × 4 Linear MIMO Antenna for Millimeter-Wave, Wearable and Biomedical Telemetry Applications.

In this paper, we present the design of a millimeter-wave 1 × 4 linear MIMO array antenna that operates across multiple resonance frequency bands: 26.28-27.36 GHz, 27.94-28.62 GHz, 32.33-33.08 GHz, and 37.59-39.47 GHz, for mm-wave wearable biomedical telemetry application. The antenna is printed on a flexible substrate with dimensions of 11.0 × 44.0 mm2. Each MIMO antenna element features a modified slot-loaded triangular patch, incorporating 'cross'-shaped slots in the ground plane to improve impedance matching. The MIMO antenna demonstrates peak gains of 6.12, 8.06, 5.58, and 8.58 dBi at the four resonance frequencies, along with a total radiation efficiency exceeding 75%. The proposed antenna demonstrates excellent diversity metrics, with an ECC < 0.02, DG > 9.97 dB, and CCL below 0.31 bits/sec/Hz, indicating high performance for mm-wave applications. To verify its properties under flexible conditions, a bending analysis was conducted, showing stable S-parameter results with deformation radii of 40 mm (Rx) and 25 mm (Ry). SAR values for the MIMO antenna are calculated at 28.0/38.0 GHz. The average SAR values for 1 gm/10 gm of tissues at 28.0 GHz are found to be 0.0125/0.0079 W/Kg, whereas, at 38.0 GHz, average SAR values are 0.0189/0.0094 W/Kg, respectively. Additionally, to demonstrate the telemetry range of biomedical applications, a link budget analysis at both 28.0 GHz and 38.0 GHz frequencies indicated strong signal strength of 33.69 dB up to 70 m. The fabricated linear MIMO antenna effectively covers the mm-wave 5G spectrum and is suitable for wearable and biomedical applications due to its flexible characteristics.

Design and Investigation of Compact Backed Mirror Two-Port MIMO Antenna for n257 (30 GHz) 5G Spectrum

Design and Investigation of Compact Backed Mirror Two-Port MIMO Antenna for n257 (30 GHz) 5G Spectrum

A dual-band MIMO PIFA antenna with a printed rectangular open-ended ring for 5G/WLAN mobile terminal

A dual-band 8 × 8 multiple-input-multiple-output (MIMO) PIFA antenna that operates in the sub-6 GHz spectrum for 5G and WLAN mobile terminals is presented. The eight elements of the MIMO antenna are formed by using an L-slotted PIFA antenna, an L-shaped parasitic element, and a 2D rectangular open-ended ring parasitic structure that is printed next to the L-shaped parasitic element. In this article, we first proposed an ultra-thick PIFA antenna element to work in the 3.4-3.8 GHz 5G band and the 5.15-5.85 GHz WLAN band, adopting a new method that can provide dual-band behavior with wide bandwidth. Then, the final antenna element is used to design an eight-port MIMO antenna system, and the results show good MIMO performance in terms of envelope correlation coefficient (ECC), diversity gain (DG), mean effective gain (MEG), and multiplexing efficiency (ME).

Impact of 5G on Internet of Things and its Challenges

In this era of rapid technological growth, the Internet of Things (IOT) refers to a system of interrelated, internet-connected objects that are able to collect and transfer data over a wireless network without human intervention. We see the IOT as billions of smart, connected things (a sort of ―universal global neural network in the cloud) that will encompass every aspect of our lives, and its foundation is the intelligence that embedded processing provides. The IOT is comprised of smart machines interacting and communicating with other machines, objects, environments and infrastructures. As a result, huge volumes of data are being generated, and that data is being processed into useful actions that can ―command and control things to make our lives much easier and safer—and to reduce our impact on the environment. The creativity of this new era is boundless, with amazing potential to improve our lives. The following thesis is an extensive reference to the possibilities, utility, applications and the evolution of the Internet of Things. The rollout of commercial 5G cellular networks has commenced, marking a significant milestone in the adoption of 5G and the Internet of Things (IoT). This adoption is propelled by various factors, such as rising consumer and enterprise demands, coupled with the availability of cost-effective devices. Notably, substantial investments by operators in 5G technology, spectrum allocation, and infrastructure development, alongside the establishment of global standards, are key drivers fuelling growth and generating heightened market interest in the IoT. The substantial investments made by operators in 5G technology, spectrum allocation, and infrastructure, coupled with the adoption of global standards, play a pivotal role in stimulating growth and generating heightened market interest in the Internet of Things (IoT). The ongoing evolution of 5G mobile cellular networks, derived from existing 4G frameworks, underscores their adaptability to diverse use cases, both present and future-oriented. With a forward- looking approach, 5G infrastructure is poised to address current demands like smart energy applications while proactively accommodating forthcoming innovations such as autonomous vehicles. In navigating this technological transition, mobile operators face the challenge of ensuring that their networks remain adept at supporting a spectrum of present and future use cases. Strategic investment management is imperative for operators to seamlessly transition their networks to 5G while upholding the continuity of service for their customers Key Words: Scalability, safety, security, rapid growth, interoperability, devices, interconnections, 5G with Internet of things, healthcare, smart city

Cross-Border Collaboration: India's UPI Success Story In Indonesia (A Case Study On Unified Payments System)

This research paper delves into the successful introduction of the Unified Payments Interface (UPI) in the Indonesian market, with a primary focus on crucial elements such as the India-Indonesia (MoU), technology transfer, the impact of the 5G spectrum, credit generation, and quantitative analysis through surveys. A notable aspect of this study is examining the current technology transfer process in UPI implementation alongside previous instances, shedding light on the evolution of knowledge transfer methodologies. The effectiveness of the India-Indonesia MoU in facilitating UPI adoption reflects the dedication of both nations. The research investigates how India's expertise in UPI is customized to meet Indonesia's specific needs, historically and in the present. The study also evaluates UPI's role in promoting credit generation, thereby contributing to financial inclusion and economic growth. The research measures user sentiments, adoption rates, and transaction trends using a multifaceted approach involving surveys and quantitative data analysis. The findings provide valuable insights for policy development, the refinement of technology transfer strategies, and the sustainable growth of digital payment systems in Indonesia and similar emerging markets.

Overview of 5G services and spectrum deployment in urban regions

Overview of 5G services and spectrum deployment in urban regions

Design, fabrication, and measurement of a miniaturized MIMO antenna applicable for 5G communication

Abstract The design of low-profile Multiple-Input-Multiple-Output (MIMO) antennas for various 5G applications is a topic of huge interest in academia, research, and telecommunication sector. In this aspect, a compact and low-profile 5G MIMO antenna has been designed and analyzed for various 5G applications, specifically for the 24 GHz bands (24.25–24.45 GHz and 25.05–25.25 GHz) and local multipoint distribution system band (27.5–28.35 GHz) of the 5G spectrum. The proposed antenna structure is 20 × 20 × 1 mm3 in dimension. Two spade-shaped radiators composed of Copper (annealed) material are placed orthogonally to improve isolation and maintain signal diversity. Rogers RT 5880 is used as the material for substrate. The antenna exhibits a wide bandwidth of 21.5–28.5 GHz. The mutual isolation |S21| has been maintained ≤29 dB due to the insertion of a T-shaped parasitic strip in between the radiating elements. Novelty in design and superiority in performance has been observed when compared with related antenna categories.

Effects of 700 and 3500 MHz 5G radiofrequency exposure on developing zebrafish embryos

Telecommunications industries are rapidly deploying the fifth generation (5G) spectrum and there is public concern about the safety and health impacts of this type of Radio Frequency Radiation (RFR), in part because of the lack of comparable scientific evidence. In this study we have used a validated commercially available setting producing a uniform field to expose zebrafish embryos (ZFe) to unmodulated 700 and 3500 MHz frequencies. We have combined a battery of toxicity, developmental and behavioral assays to further explore potential RFR effects. Our neurobehavioral profiles include a tail coiling assay, a light/dark activity assay, two thigmotaxis anxiety assays (auditory and visual stimuli), and a startle response - habituation assay in response to auditory stimuli. ZFe were exposed for 1 and 4 h during the blastula period of development and endpoints evaluated up to 120 hours post fertilization (hpf). Our results show no effects on mortality, hatching or body length. However, we have demonstrated specific organ morphological effects, and behavioral effects in activity, anxiety-like behavior, and habituation that lasted in larvae exposed during the early embryonic period. A decrease in acetylcholinesterase activity was also observed and could explain some of the observed behavioral alterations. Interestingly, effects were more pronounced in ZFe exposed to the 700 MHz frequency, and especially for the 4 h exposure period. In addition, we have demonstrated that our exposure setup is robust, flexible with regard to frequency and power testing, and highly comparable. Future work will include exposure of ZFe to 5G modulated signals for different time periods to better understand the potential health effects of novel 5G RFR.

A reconfigurable RF front-end for 5G direct sampling receivers with an optimized calibration scheme

This paper presents a reconfigurable radio frequency front-end (RFFE) tailored for direct RF sampling receivers operating within Frequency Range 1 (FR-1) of the 5G spectrum. It consists of a balun-LNA, a noise-cancelling, current-reuse, Q-enhanced filter, and a programmable gain amplifier (PGA). Fabricated in 22-nm FD-SOI technology, the RFFE covers the entire frequency range from 1.7 to 6.4 GHz with a tunable bandwidth ranging from 50 MHz to 1.2 GHz. The experimental results confirm that the RFFE achieves 3.9 dB NF, 55 dB ultimate OOB rejection, −4 dBm IB-IIP3, and 23 dBm OOB-IIP3. Furthermore, a digital calibration scheme is proposed to compensate for process, voltage, and temperature (PVT) variations, achieving lower than 2 % error in 6.61 µs on average. Subsequently, a proximal policy optimization (PPO) agent is employed to choose the optimal policy for the successive adjustments of quality factors and resonance frequencies of the filter’s resonators. As a result, the proposed reinforcement learning algorithm reduces the calibration’s convergence time by 59 %.

Performance of Path Loss Models over Mid-Band and High-Band Channels for 5G Communication Networks: A Review

The rapid development of 5G communication networks has ushered in a new era of high-speed, low-latency wireless connectivity, as well as the enabling of transformative technologies. However, a crucial aspect of ensuring reliable communication is the accurate modeling of path loss, as it directly impacts signal coverage, interference, and overall network efficiency. This review paper critically assesses the performance of path loss models in mid-band and high-band frequencies and examines their effectiveness in addressing the challenges of 5G deployment. In this paper, we first present the summary of the background, highlighting the increasing demand for high-quality wireless connectivity and the unique characteristics of mid-band (1–6 GHz) and high-band (&gt;6 GHz) frequencies in the 5G spectrum. The methodology comprehensively reviews some of the existing path loss models, considering both empirical and machine learning approaches. We analyze the strengths and weaknesses of these models, considering factors such as urban and suburban environments and indoor scenarios. The results highlight the significant advancements in path loss modeling for mid-band and high-band 5G channels. In terms of prediction accuracy and computing effectiveness, machine learning models performed better than empirical models in both mid-band and high-band frequency spectra. As a result, they might be suggested as an alternative yet promising approach to predicting path loss in these bands. We consider the results of this review to be promising, as they provide network operators and researchers with valuable insights into the state-of-the-art path loss models for mid-band and high-band 5G channels. Future work suggests tuning an ensemble machine learning model to enhance a stable empirical model with multiple parameters to develop a hybrid path loss model for the mid-band frequency spectrum.

Dual Band 1x4 Linear Metamaterial Bowtie Antenna Array for Autonomous Vehicle in Public Safety Band Communications

This research presents the design, simulation, and fabrication of a dual-band 1x4 linear metamaterial bowtie antenna array for applications in 5G wireless systems and public safety band communications. The single-element antenna is a compact dual-band structure with a complementary split-ring resonator (TCSRR) element, and it exhibits resonant frequencies of 3.5 GHz and 4.9 GHz, covering the sub-6GHz 5G spectrum and the public safety band. The antenna aray design is optimized for impedance matching and radiation efficiency. The 1x4 linear antenna array is designed with a quarter-wave transformer feed network and carefully controlled mutual coupling to enhance gain and directionality. Simulated and measured results confirm the performance of the array, with a reflection coefficient within -10 dB from 3.2 GHz to 3.85 GHz and from 4.55 GHz to 5.95 GHz and 3.45 GHz to 3.75 GHz and 4.45 GHz to 5.7 GHz, respectively. The array exhibits a peak realized gain of up to 8.7 dBi and efficient radiation patterns. This work offers promising insights into the development of antenna systems for advanced wireless communication applications and vehicle-to-vehicle communication in public safety band.

Optimizing dual-band antenna efficiency: Ridge width parametric study of quad ridge horn antennas

The purpose of this project was to develop a quad ridged horn antenna for a GSM and mid band 5G application, capable of dual frequency range operation at 1.8 GHz and 3.5 GHz. The antenna was constructed using 3D printing technology and Polylactic Acid (PLA), a thermoplastic polymer known for its high strength and compatibility with 3D printing processes. The impact of varying ridge width dimensions on the antenna's performance was evaluated using a range of parametric techniques. Ridge widths of 10 mm, 13.5 mm, and 17 mm were analysed to assess the effects of dimension alterations. Results demonstrated that the antenna is capable of dual band frequency operation with signal reflections of -16.89 dB and -28.60 dB at 1.8 GHz and 3.5 GHz, respectively. This research contributes to the development of efficient and cost-effective antennas for wireless communication applications in the GSM and mid band 5G spectrum.

A Comprehensive Investigation of Beam Management Through Conventional and Deep Learning Approach

5G spectrum uses cutting-edge technology which delivers high data rates, low latency, increased capacity, and high spectrum utilization. To cater to these requirements various technologies are available such as Multiple Access Technology (MAT), Multiple Input Multiple Output technology (MIMO), Millimetre (mm) wave technology, Non-Orthogonal Multiple Access Technology (NOMA), Simultaneous Wireless Information and Power Transfer (SWIPT). Of all available technologies, mmWave is prominent as it provides favorable opportunities for 5G. Millimeter-wave is capable of providing a high data rate i.e., 10 Gbit/sec. Also, a tremendous amount of raw bandwidth is available i.e., around 250 GHz, which is an attractive characteristic of the mmWave band to relieve mobile data traffic congestion in the low frequency band. It has a high frequency i.e., 30 – 300 GHz, giving very high speed. It has a very short wavelength i.e., 1-10mm, because of this it provides the compact size of the component. It will provide a throughput of up to 20 Gbps. It has narrow beams and will increase security and reduce interference. When the main beam of the transmitter and receiver are not aligned properly there is a problem in ideal communication. To solve this problem beam management is one of the solutions to form a strong communication link between transmitter and receiver. This paper aims to address challenges in beam management and proposes a framework for realization. Towards the same, the paper initially introduces various challenges in beam management. Towards building an effective beam management system when a user is moving, various steps are present like beam selection, beam tracking, beam alignment, and beam forming. Hence the subsequent sections of the paper illustrate various beam management procedures in mmWave using conventional methods as well as using deep learning techniques. The paper also presents a case study on the framework's implementation using the above-mentioned techniques in mmWave communication. Also glimpses on future research directions are detailed in the final sections. Such beam management techniques when used for mmWave technology will enable build fast, efficient, and capable 5G networks.