Maximum Data Research Articles

Design and verification of SoC for OFDM-based visible light communication transceiver systems and integration with off-the-shelf analog front-end

In this paper, a System-on-Chip (SoC) design for Orthogonally Frequency Division Multiplexing (OFDM)-based Visible Light Communication (VLC) transceiver is presented. The VLC transceiver system comprises the physical (PHY) layer and analog front-end (AFE). The OFDM modulation was implemented in the PHY layer. We design the SoC-based PHY layer using the “reuse methodology”. In this methodology, the Intellectual Property (IP) cores do not necessarily need to be created from scratch as it can be obtained from a 3rd party. Using this methodology, it can increase our productivity during the designing process. This methodology is suitable for developing an OFDM system, especially in VLC system, that requires high complexity blocks. When the IP cores are not available from the 3rd party, they can be designed from scratch. We design the IP cores with the AXI4 protocol standard which is widely used in SoC design. Later, the OFDM system IP cores are integrated by using the AXI4-Stream protocol. In addition, the dual-core ARM Cortex-A9 processor is integrated into the OFDM system IP cores using the AXI4-Lite protocol. The transmitter (TX) and receiver (RX) applications run on Linux OS (Xilinux) can access the OFDM system IP cores with the memory–mapped I/O method. To guarantee the successful design, we have tested our SoC design with the off-the-shelf AFE transceiver integration in a real setting. The analog part for this work was created by available commercially components. Three modulation types were selected for the field test, i.e., BPSK, QPSK, and QAM-16. The maximum data rates of VLC system also have been investigated in a real-time as a proof of concept of the proposed SoC architecture.

A Novel Fairness Allocation Strategy With Minimum Mainlobe Interference for mmWave Networks

In the fifth-generation (5G) communication system, millimeter-wave (mmWave) technology brings superior capabilities, such as higher capacity, lower latency, and a flexible beamforming structure. The interference management strategies play an important role in mmWave beamforming networks to support the multibeam operation and maximize the overall data rates for user equipments (UEs). Currently, most of the existing research do not jointly consider designs, including the mainlobe interference (MI) avoidance and resource blocks (RBs) fairness allocation. In this article, a novel fairness allocation strategy is proposed to achieve the minimum MI and a fair RB assignment for mmWave networks. To achieve the minimum MI, an MI mitigation (MIM) algorithm is designed to maximize the data rate for each UE. With the adaptive mini-timeslot design, the MIM algorithm can achieve MI cancelation for all UEs at each identical timeslot and beam. To combine MIM and fairness for RB allocation among all UEs, the MIM-fairness allocation (MIM-FA) algorithm is also presented. Based on a novel mini-timeslot with designed multiple frames, the MIM-FA algorithm can simultaneously guarantee the fairness among all UEs and mitigate MI at each mini-timeslot for each beam. Additionally, the MIM-FA algorithm can be verified that it achieves the maximum user data rate with the identical number of RBs under the lowest number of frames. Simulation results validate that the proposed MIM and MIM-FA algorithms can provide a higher data rate and better fairness for different scenarios compared to current state-of-the-art competitive approaches.

Data Rate Maximization in RIS-Assisted D2D Communication with Transceiver Hardware Impairments

We maximize the transmit rate of device-to-device (D2D) in a reconfigurable intelligent surface (RIS) assisted D2D communication system by satisfying the unit-modulus constraints of reflectin elements, the transmit power limit of base station (BS) and the transmitter in a D2D pair. Since it is a non-convex optimization problem, the block coordinate descent (BCD) technique is adopted to decouple this problem into three subproblems. Then, the non-convex subproblems are approximated into convex problems by using successive convex approximation (SCA) and penalty convex-concave procedure (CCP) techniques. Finally, the optimal solution of original problem is obtained by iteratively optimizing the subproblems. Simulation results reveal the validity of the algorithm that we proposed to solve the optimization problem and illustrate the effectiveness of RIS to improve the transmit rate of the D2D pair even with hardware impairments.

Underwater quasi-omnidirectional wireless optical communication based on perovskite quantum dots.

In this paper, a quasi-omnidirectional transmitter is proposed and demonstrated for underwater wireless optical communication (UWOC) using the photoluminescence of perovskite quantum dots (QDs). The proposed transmitter, without complex driving circuits, is compact and reliable thanks to the lens-free design. The system performance is tested in a 50-m swimming pool with a water attenuation coefficient of 0.38 dB/m. The maximum data rates of on-off-keying (OOK) signals over 10-m and 20-m transmission distances can reach 60 Mbps and 40 Mbps, respectively. When four clients are adopted in a code division multiple access (CDMA) based UWOC network, the maximum data rates of each client can reach 10 Mbps and 7.5 Mbps over 10-m and 20-m underwater channels, respectively. The system can meet the requirements of the last meter end-user access in the Internet of underwater things (IoUT) and underwater optical cellular network systems.

Высокоскоростные одномодовые вертикально-излучающие лазеры спектрального диапазона 1550 нм

The results of complex studies of static and dynamic performance of 1550 nm-range VCSELs, which were created by direct bonding (wafer fusion technique) InAlGaAs/InP optical cavity wafers with AlGaAs/GaAs distributed reflector wafers grown by molecular beam epitaxy, are presented. The VCSELs with a buried tunnel junction diameter less than 7 μm demonstrated a single-mode lasing with a side-mode suppression ratio more than 40 dB; however, at diameters less than 5 μm, a sharp increase in the threshold current is observed. It is associated to the appearance of a saturable absorber due to penetration of optical mode into the non-pumped regions of the active region. The maximum single-mode output optical power and the–3 dB modulation bandwidth reached 4.5 mW and 8 GHz, respectively, at 20°C. The maximum data rate at 20ºC under non-return-to-zero on-off keying modulation was 23 Gb/s for a short-reach link based on single-mode fiber SMF-28. As the length of the optical link increased up to 2000 m, the maximum data rate dropped to 18 Gbit/s. The main factors affecting the high-speed operation and data transmission range are defined and discussed, and the further ways to overcome themit are proposed.

1550 nm range high-speed single-mode vertical-cavity surface-emitting lasers

The results of complex studies of static and dynamic performance of 1550 nm-range VCSELs, which were created by direct bonding (wafer fusion technique) InAlGaAs/InP optical cavity wafers with AlGaAs/GaAs distributed Bragg reflector wafers grown by molecular beam epitaxy, are presented. The VCSELs with a buried tunnel junction diameter less than 7 μm demonstrated a single-mode lasing with a side-mode suppression ratio more than 40 dB; however, at diameters less than 5 μm, a sharp increase in the threshold current is observed. It is associated to the appearance of a saturable absorber due to penetration of optical mode into the non-pumped regions of the active region. The maximum single-mode output optical power and the -3 dB modulation bandwidth reached 4.5 mW and 8 GHz, respectively, at 20oC. The maximum data rate at 20oC under non-return-to-zero on-off keying modulation was 23 Gb/s for a short-reach link based on single-mode fiber SMF-28. As the length of the optical link increased up to 2000 m, the maximum data rate dropped to 18 Gbit/s. The main factors affecting the high-speed operation and data transmission range are defined and discussed, and the further ways to overcome themit are proposed. Keywords: VCSEL, wafer fusion, molecular beam epitaxy, single-mode operation, high-speed performance.

Simulation and Field Trial Results of Reconfigurable Intelligent Surfaces in 5G Networks

Recently, reconfigurable intelligent surfaces (RISs) are considered as a strong candidate for next generation wireless technologies, thanks to its advantage of being able to configure the wireless propagation environment in a cost-effective and energy-efficient way. Many literature study the theoretical aspects of RIS-assisted communication while prototyping and field trials are relatively scarce. A key step towards the standardization and commercialization of RISs is to complete comprehensive field trials in cellular networks, such as the 5th generation (5G) network. There are several typical deployment scenarios in 5G networks such as indoors, outdoors and mixed indoors and outdoors, where RISs can provide coverage to weak reception areas, enhance transmission robustness, fix coverage holes and increase the maximum available data rate. In this paper, a variety types of RIS prototypes are fabricated and tested with off-the-shelf 5G user equipments (UEs) and 5G base stations (BSs) to validate the performance gain introduced by RISs to typical deployment scenarios of 5G at different working frequencies. Some system-level simulations are also conducted for several typical scenarios to be used as a baseline to verify that the test results are theoretically correct. All test parameters and signals are selected according to 5G standards to reflect the performance of RISs in real-world 5G networks. The experimental results confirm the feasibility and effectiveness of RISs to solve coverage issues in 5G networks across different frequency ranges.

Contextual information aware optimal communication in radio networks in considering the pervasive computing -A literature review

The modern tactical network demands a highly dynamic communications environment that involves autonomous platforms and systems. In order to achieve the full potential of modern technologies, it is critical to ensure the critical data finds the optimum path at the right time in a highly aggressive environment employing secure and best possible available communication path or network resources. Moreover, Contextual information aware optimal communication, such as the power of the radios, battery level, distance among the radios, and maximum and minimum data rates of the radio aware optimal path selection, remains an unresolvable research area. The mentioned limitation engenders various complex challenges in mission-critical networks. Therefore, contextual information-aware optimal communication in radio networks is a priority demand raised as a primary objective for military communication research. In this paper, we have performed a comprehensive review of various proposed methodologies to achieve the objective, followed by a critical comparative analysis to anticipate the state of the mentioned research area that leads to a future research direction for military researchers.

Deep Learning Based Stacked Sparse Autoencoder for PAPR Reduction in OFDM Systems

Orthogonal frequency division multiplexing is one of the efficient and flexible modulation techniques, and which is considered as the central part of many wired and wireless standards. Orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) achieves maximum spectral efficiency and data rates for wireless mobile communication systems. Though it offers better quality of services, high peak-to-average power ratio (PAPR) is the major issue that needs to be resolved in the MIMO-OFDM system. Earlier studies have addressed the high PAPR of OFDM system using clipping, coding, selected mapping, tone injection, peak windowing, etc. Recently, deep learning (DL) models have exhibited improved performance on channel estimation, signal recognition, channel decoding, modulation identification, and end-to-end wireless system. In this view, this paper presents a new Hyperparameter Tuned Deep Learning based Stacked Sparse Autoencoder (HPT-SSAE) for PAPR Reduction Technique in OFDM system. The proposed model aims to substantially reduce the peaks in the OFDM signal. The presented HPT-SSAE model is utilized to adaptively create a peak-canceling signal based on the features of the input signal. In the HPT-SSAE model, the constellation mapping and demapping of symbols take place on every individual subcarrier adaptively using the SSAE model in such a way that bit error rate (BER) and the PAPR of the OFDM systems are cooperatively diminished. Besides, to enhance the performance of the SSAE model, the hyperparameter tuning process takes place using monarch butterfly optimization (MBO) algorithm. A comprehensive set of simulations were performed to highlight the supremacy of the HPT-SSAE model. The obtained experimental values showcased the betterment of the proposed model over the compared methods interms of bit error rate (BER), complementary cumulative distribution function (CCDF), and execution time.

Analysis of Wave Propagation Models With Radio Network Planning Using Dual Polarized MIMO Antenna for 5G Base Station Applications

Dual polarized printed multiple input multiple output (MIMO) antenna for Band 42 (3.4 - 3.6 GHz) with wave propagation models is presented. Polarization and spatial diversity are achieved by utilizing two printed bow-tie antennas in orthogonal orientation. The designed dual polarized antenna element with <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$8\times 8$ </tex-math></inline-formula> massive MIMO antenna configuration radiation patterns are deployed in selected geographical situation for detailed radio network planning using FEKO-WinProp platform. Knife edge diffraction, extended walfisch-ikegami and dominant path wave propagation models are implemented with designed MIMO antenna configurations. Modulation schemes of QPSK and QAM with corresponding data rates and throughput for all propagation models are presented. The signal strength and quality reflecting parameters reference signal received power (RSRP), received signal strength indicator (RSSI), reference signal received quality (RSRQ), and signal to noise plus interference ratio (SNIR) are also evaluated for each model. From the simulation results dominant path model provides data rate and throughput of 3.827, 995 MBit/s and 3.577, 930.1 MBit/s for single stream of data in uplink and downlink respectively. The maximum data rate of 1.37 GBits/s is achieved for deployed base stations with <inline-formula> <tex-math notation="LaTeX">$8\times 8$ </tex-math></inline-formula> massive MIMO antenna configuration effectively covering the entire geographical site.

A 100-Gb/s PAM-4 Voltage-Mode Transmitter With High-Resolution Unsegmented Three-Tap FFE in 40-nm CMOS

This letter presents a 100-Gb/s four-level pulse amplitude modulation (PAM-4) voltage-mode transmitter (TX) with a three-tap feed-forward equalizer (FFE). A new configuration, including FFE and output impedance (Zout) control loops, for implementing voltage-mode FFE is proposed to avoid the driver being segmented. The method can significantly decrease the layout complexity of a high-resolution voltage-mode FFE, improving the output bandwidth. The TX front end merges the 2:1 multiplexer into the driver and adopts a quarter-rate clocking scheme to save significant power. Designed and fabricated in 40-nm CMOS, the PAM-4 TX achieves a maximum data rate of 100 Gb/s with 2.39-pJ/b energy efficiency under a chip-on-board assembly with 5-dB Nyquist loss.

Service-Aware User Association and Resource Allocation in Integrated Terrestrial and Non-Terrestrial Networks: A Genetic Algorithm Approach

In 6G networks and beyond, multiple radio access networks (RANs), including; the satellite, high altitude platforms, low altitude platforms, and the terrestrial network, will co-exist. These networks are characterized by different capabilities and limitations in meeting the envisioned 6G contrasting user requirements. Therefore, associating users with the appropriate radio access network (RAN) in such an integrated network is rigorous and complex. In this work, the user association and resource allocation problem is formulated as a multi-objective optimization problem (MOOP), aiming to maximize data rate while minimizing mobility-induced handoff in the integrated network. Moreover, the problem is formulated in such a way as to prioritize the service provisioning of mission-critical users. The weighted sum method is adopted to simplify and transform the MOOP into a single-objective optimization problem (SOOP). In order to solve the formulated NP-hard SOOP, a genetic algorithm (GA) whose fitness value is based on the user’s service group is proposed. The performance of the proposed algorithm is evaluated by comparing it to the optimal solution, the greedy signal-to-interference-plus-noise ratio (SINR) based association, and the random user association algorithms. Simulation results show that as the number of access nodes in the network increases, the GA’s spectrum efficiency (SE) remains within 0.4% of the optimal solution. Moreover, the GA outperforms all three schemes in user acceptance ratio (AR) and handoff probability.

Aerial Intelligent Reflecting Surfaces in MIMO-NOMA Networks: Fundamentals, Potential Achievements, and Challenges

Non-orthogonal multiple access (NOMA) technique and unmanned aerial vehicles (UAVs) have been recognized as promising technologies for enabling the stringent requirements of the different network infrastructures expected for the next generation of wireless networks. In parallel, intelligent reconfigurable surfaces (IRSs) have been widely pointed out as an auspicious solution to further improve spectral efficiency, coverage range, and connectivity. By integrating IRS with UAV and NOMA schemes with multiple-input multiple-output (MIMO) it is possible to smartly improve the overall network performance. In order to explore some of these potentials, this paper provides a comprehensive discussion about the interplay of aerial IRS in MIMO-NOMA (AIRS-NOMA) networks, as well its architecture, functionality principles, and performance gains. In particular, attractive gains related to the data rate maximization, user fairness, energy efficiency, and coverage range are highlighted. Simulation results are provided to support our insightful discussions, in which it is revealed that the performance gains of AIRS-NOMA networks are superior when compared to terrestrial deployment. In addition, to guide new studies perspectives, it is addressed some issues and research opportunities associated with this potential integration.

Joint Power Allocation and Placement Scheme for UAV-Assisted IoT With QoS Guarantee

In the disaster and remote regions, unmanned aerial vehicles (UAVs) can assist the data acquisition for Internet of Things (IoT). How to cover massive IoT devices (IDs), which require diverse quality-of-service (QoS), is a crucial challenge. For UAV-assisted IoT, this paper studies the deployment scheme with QoS guarantee to place multiple UAVs for covering all ground IDs and maximizing the average data rate of UAVs. First, for the ground ID, we propose the QoS demand based power allocation (QDPA) algorithm to solve the diversity of QoS with respect to data rate demand. Then, the data rate maximization placement (DRMP) algorithm is proposed to optimize the placement of single UAV. Finally, based on QDPA and DRMP algorithms, we propose the joint power allocation and placement (JPAP) scheme with QoS guarantee, which can cover massive IDs, to deploy multiple UAVs for maximizing the average UAV data rate. Simulation experiments are conducted to verify the superiority of our proposed JPAP scheme, which can minimize the UAV number and maximize the average data rate of UAVs.

Rate maximization in full‐duplex systems: Gains and complexity of employing adaptive power allocation in downlink and/or uplink

AbstractThe next generations of mobile communications should deal with a set of new use cases, leading to a higher demand for spectral efficiency. Full‐duplex (FD) arises as a promising technology since it has the potential to double the system capacity without additional spectrum. However, FD networks are hindered by self‐interference (SI) and co‐channel interference caused by the reuse of frequency resources. Therefore, radio resource allocation (RRA) in FD networks by means of user pairing, frequency assignment, and power allocation are of utmost importance in order to improve spectral/energy efficiency and ensure quality of service (QoS). Although previous works investigated RRA to improve spectral efficiency, the fundamental question of where adaptive power allocation should be employed in the uplink and/or downlink of FD networks in a cost‐effective way remains unanswered. This article addresses this question in the context of total data rate maximization with QoS constraints where we propose four optimization problems using different power allocation strategies. The branch and bound method is employed to optimally solve the four formulated problems, which were used as upper bound solutions for benchmarking purposes. Moreover, we propose a low computational complexity solution able to adaptively switch the power allocation strategy depending on the scenario. Detailed system‐level simulations indicate that the best node to employ adaptive power allocation (mobile terminal or base station) depends on the cell radius and SI level. Also, our results show that, compared to existing solutions, the proposed low‐complexity is a great and intelligent strategy in terms of system performance and computational complexity considering both perfect and imperfect channel state information.

What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence

In the 1940s, Claude Shannon developed the information theory focusing on quantifying the maximum data rate that can be supported by a communication channel. Guided by this fundamental work, the main theme of wireless system design up until the fifth generation (5G) was the data rate maximization. In Shannon's theory, the semantic aspect and meaning of messages were treated as largely irrelevant to communication. The classic theory started to reveal its limitations in the modern era of machine intelligence, consisting of the synergy between Internet-of-things (IoT) and artificial intelligence (AI). By broadening the scope of the classic communication-theoretic framework, in this article, we present a view of semantic communication (SemCom) and conveying meaning through the communication systems. We address three communication modalities: human-to-human (H2H), human-to-machine (H2M), and machine-to-machine (M2M) communications. The latter two represent the paradigm shift in communication and computing, and define the main theme of this article. H2M SemCom refers to semantic techniques for conveying meanings understandable not only by humans but also by machines so that they can have interaction and &#x0022;dialogue&#x0022;. On the other hand, M2M SemCom refers to effective techniques for efficiently connecting multiple machines such that they can effectively execute a specific computation task in a wireless network. The first part of this article focuses on introducing the SemCom principles including encoding, layered system architecture, and two design approaches: 1) layer-coupling design; and 2) end-to-end design using a neural network. The second part focuses on the discussion of specific techniques for different application areas of H2M SemCom [including human and AI symbiosis, recommendation, human sensing and care, and virtual reality (VR)/augmented reality (AR)] and M2M SemCom (including distributed learning, split inference, distributed consensus, and machine-vision cameras). Finally, we discuss the approach for designing SemCom systems based on knowledge graphs. We believe that this comprehensive introduction will provide a useful guide into the emerging area of SemCom that is expected to play an important role in sixth generation (6G) featuring connected intelligence and integrated sensing, computing, communication, and control.

Alternative Chirp Spread Spectrum Techniques for LPWANs

Chirp spread spectrum (CSS) is the modulation technique currently employed by Long-Range (LoRa), which is one of the most prominent Internet of Things wireless communications standards. The LoRa physical layer (PHY) employs CSS on top of a variant of frequency shift keying, and non-coherent detection is employed at the receiver. While it offers a good trade-off among coverage, data rate and device simplicity, its maximum achievable data rate is still a limiting factor for some applications. Moreover, the current LoRa standard does not fully exploit the CSS generic case, i.e., when data to be transmitted is encoded in different waveform parameters. Therefore, the goal of this paper is to investigate the performance of CSS while exploring different parameter settings aiming to increase the maximum achievable throughput, and hence increase spectral efficiency. Moreover, coherent and non-coherent reception algorithm design is presented under the framework of maximum likelihood estimation. For the practical receiver design, the formulation of a channel estimation technique is also presented. The performance evaluation of the different variants of CSS is carried out by inspection of the symbol error ratio as a function of the signal-to-noise ratio together with the maximum achievable throughput each scheme can achieve.

Reinforcement Learning Aided UAV Base Station Location Optimization for Rate Maximization

The application of unmanned aerial vehicles (UAV) as base station (BS) is gaining popularity. In this paper, we consider maximization of the overall data rate by intelligent deployment of UAV BS in the downlink of a cellular system. We investigate a reinforcement learning (RL)-aided approach to optimize the position of flying BSs mounted on board UAVs to support a macro BS (MBS). We propose an algorithm to avoid collision between multiple UAVs undergoing exploratory movements and to restrict UAV BSs movement within a predefined area. Q-learning technique is used to optimize UAV BS position, where the reward is equal to sum of user equipment (UE) data rates. We consider a framework where the UAV BSs carry out exploratory movements in the beginning and exploitary movements in later stages to maximize the overall data rate. Our results show that a cellular system with three UAV BSs and one MBS serving 72 UE reaches 69.2% of the best possible data rate, which is identified by brute force search. Finally, the RL algorithm is compared with a K-means algorithm to study the need of accurate UE locations. Our results show that the RL algorithm outperforms the K-means clustering algorithm when the measure of imperfection is higher. The proposed algorithm can be made use of by a practical MBS–UAV BSs–UEs system to provide protection to UAV BSs while maximizing data rate.

Enhanced Dynamic Spectrum Access in UAV Wireless Networks for Post-Disaster Area Surveillance System: A Multi-Player Multi-Armed Bandit Approach.

Modern wireless networks are notorious for being very dense, uncoordinated, and selfish, especially with greedy user needs. This leads to a critical scarcity problem in spectrum resources. The Dynamic Spectrum Access system (DSA) is considered a promising solution for this scarcity problem. With the aid of Unmanned Aerial Vehicles (UAVs), a post-disaster surveillance system is implemented using Cognitive Radio Network (CRN). UAVs are distributed in the disaster area to capture live images of the damaged area and send them to the disaster management center. CRN enables UAVs to utilize a portion of the spectrum of the Electronic Toll Collection (ETC) gates operating in the same area. In this paper, a joint transmission power selection, data-rate maximization, and interference mitigation problem is addressed. Considering all these conflicting parameters, this problem is investigated as a budget-constrained multi-player multi-armed bandit (MAB) problem. The whole process is done in a decentralized manner, where no information is exchanged between UAVs. To achieve this, two power-budget-aware PBA-MAB) algorithms, namely upper confidence bound (PBA-UCB (MAB) algorithm and Thompson sampling (PBA-TS) algorithm, were proposed to realize the selection of the transmission power value efficiently. The proposed PBA-MAB algorithms show outstanding performance over random power value selection in terms of achievable data rate.

Miniature Coil for Wireless Power and Data Transfer through Aluminum.

This paper presents the design and development of miniature coils for wireless power and data transfer through metal. Our coil has a total size of 15 mm × 13 mm × 6 mm. Experimental results demonstrate that we can harvest 440 mW through a 1 mm-thick aluminum plate. Aluminum and stainless-steel barriers of different thicknesses were used to characterize coil performance. Using a pair of the designed coils, we have developed a through-metal communication system to successfully transfer data through a 1 mm-thick aluminum plate. A maximum data rate of 100 bps was achieved using only harvested power. To the best of our knowledge, this is the first report that demonstrates power and data transfer through aluminum using miniature coils.