Wireless Communication Techniques Research Articles

Design of a cost-effective customized Electronic Health Record system to handle patient management during Covid-19 pandemic

Healthcare is one of the basic needs for human beings. Unfortunately, a densely populated country like Bangladesh has always struggled to provide adequate healthcare to all of its people, especially to the rural population. To handle with huge amount of data and coordination between the doctors and patients, electronic health record system (EHR) has become a necessity. During this Covid-19 pandemic, face to face consultation between frontline workers like doctors, and nurse and patients has become difficult. As a result, many patients are having difficulty in getting treatment from doctors. In Bangladesh’s perspective at this moment, a cost effective, energy efficient and portable device system is needed to build up a customized Electronic health record system. The proposed system can reduce medical errors about patient identification and treatment, increase effectiveness and timeliness of doctors and overall improve the health care of people of the rural area. Therefore, an easy to use, affordable, user-friendly E customized EHR system design is proposed in this paper by utilizing recent wireless communication techniques that will give the rural people better health service.

PAPR REDUCTION TECHNIQUES AND IMAGE QUALITY ASSESSMENTIN IMAGE BASED MMS VLC SYSTEM

The radiofrequency method of transmission suffers from the problem of the limited licensed radio frequency spectrum, & security, wide EMI (electromagnetic interference), high multipath fading & power consumption for short-range applications. The solution to these problems can be achieved by using optical wireless communication technique called the Visible Light Communication system where the data is sent through regulated emission of light. The transmission of digital image information productively in the present optical wireless communication framework is an uphill task as these systems often suffer from problems like frequency selective fading propagation losses and inter-symbol interferences. In order to conquer such difficulties we hereby propose a robust method to transfer the digital image through a Multi-Carrier Modulation Scheme-MMS. In this paper, an Image-Based Multicarrier modulation VLC system is designed through which is sent a corrupted Digital Image with additive white Gaussian noise and explored the overall execution of the Image based Multicarrier modulation VLC system at distinct SNR values. The paper also addresses the issue of high Peak to Average Power Ratio (PAPR) in Multicarrier modulation and reduced it by using different PAPR reduction techniques. The received image quality of the proposed system is obtained under different signal to noise ratios at different modulation schemes..

Achievable Rate of NOMA-Based DF Relaying System With Imperfect SIC Over Imperfect Estimation of κ-μ Shadowed Fading Channels

A cooperative relaying system based on non-orthogonal multiple access (NOMA) is considered a promising technique in next-generation wireless communications. In this letter, we investigate the performance of a dual-hop decode-and-forward based on the NOMA relaying system in terms of achievable rate and power allocation coefficient over imperfect estimation of $\kappa $ - $\mu $ shadowed fading channels. Moreover, we consider imperfect successive interference cancellation at the relay in the first phase of transmission. Specifically, we derive the closed expressions for the average achievable rate and power allocation coefficient in terms of hypergeometric function. Finally, the numerical results confirm that our derived analytical results fit well the Monte Carlo simulations.

Design and implementation of AI Based Robotic Car for Surveillance and transportation

The world of control is an exciting field that has exploded with new technologies where the Internet of Things vision becomes a reality. Today, IoT with AI is used to make applications such as intelligent transportation, smart security, and smart home. The wireless communication technique is beneficial in IoT nowadays. In this paper, the author proposed a model for android control robot car using wireless technology. Obstacle detection is advantageous in terms of avoiding accidents; the author has been introduced in this paper. This robot car also detects the AQI index of the place. The data is shared on the BLYNK cloud app as well for further decisions.

Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge.

Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth survey on the most recent advances in SS for CR. We start by explaining the Half-Duplex and Full-Duplex paradigms, while focusing on the operating modes in the Full-Duplex. A thorough discussion of Full-Duplex operation modes from collision and throughput points of view is presented. Then, we discuss the use of learning techniques in enhancing the SS performance considering both local and cooperative sensing scenarios. In addition, recent SS applications for CR-based Internet of Things and Wireless Sensors Networks are presented. Furthermore, we survey the latest achievements in Spectrum Sensing as a Service, where the Internet of Things or the Wireless Sensor Networks may play an essential role in providing the CR network with the SS data. We also discuss the utilisation of CR for the 5th Generation and Beyond and its possible role in frequency allocation. With the advancement of telecommunication technologies, additional features should be ensured by SS such as the ability to explore different available channels and free space for transmission. As such, we highlight important future research axes and challenging points in SS for CR based on the current and emerging techniques in wireless communications.

Improved two-way double-relay selection technique for cooperative wireless communications

In this article, a novel two-way double-relay selection strategy with its bit error rate (BER) performance analysis is proposed. In this novel strategy, as a first step we choose two relays out of a set of relay-nodes in a way to maximize the system performance in terms of BER and complexity. In the second step, the selected relays apply orthogonal space-time coding scheme using the three-phase protocol to establish a two-way communication between the transceivers, which will lead to a significant improvement in the achievable diversity and coding gain with a very low decoding complexity by using a symbol-wise decoder. Furthermore, the performance of the overall system is further enhanced through the use of a network coding method at the selected relay-nodes. Moreover, this paper proposes the analytical approximation of the BER performance. As well, we show that the analytical results match perfectly the simulated ones. In addition, we prove that our strategy outperforms the current state-of-the-art ones by proposing a better cooperative communication system in terms of BER.

Secrecy performance of terahertz wireless links in rain and snow

Wireless communication technique operating at terahertz (THz) frequencies is regarded as the most potential candidate for future wireless networks due to its wider frequency bandwidth and higher directionality when compared with that employing radio frequency (RF) and millimeter waves (mmWaves). It has been proved that the high directionality owned by THz wireless links could help to reduce the possibility of eavesdropping attacks at physical layer. However, for outdoor applications in adverse weathers (such as water fog, dust fog, rain and snow), scattering and absorption effects suffered by a THz link due to weather particles and gaseous molecules could degrade its secrecy performance seriously. In this work, we present theoretical investigations on physical layer security of a point-to-point THz link in rain and snow with a potential eavesdropper locating outside of the legitimate link path. Signal degradation due to rain/snow, gaseous attenuation and beam divergence are included in a theoretical model to estimate the link performance. Secrecy capacity of the link with carriers at 140, 220 and 340 GHz is calculated and compared. We find that the rain/snow intensity, carrier frequency and receiver sensitivity could affect the secrecy performance and their influence on insecure region and maximum safe data transmission rate is discussed and summarized.

Beamforming Design in Multiple-Input-Multiple-Output Symbiotic Radio Backscatter Systems

Symbiotic radio (SR) backscatter is a possible low-power wireless communication technique for future Internet of Things devices. In this letter, a multiple-input-multiple-output (MIMO) SR backscatter system is proposed, where the secondary multi-antenna transmission from the backscatter device (BD) to the receiver is riding on the primary multi-antenna transmission from the transmitter to the receiver. We investigate the beamforming design optimization problem which maximizes the sum capacity of primary and secondary transmissions under the capacity constraint of secondary transmission. In the MIMO SR backscatter system, each antenna of the SR BD reflects its received ambient radio frequency signals from all the transmitting antennas of the transmitter, which causes that the globally optimal solution is difficult to obtain. Here, we derive an algorithm to obtain the capacity upper bound. Furthermore, considering both primary and secondary transmissions, we propose an exact penalty method based locally optimal solution. Simulation results display that the proposed exact penalty method based locally optimal solution achieves the sum capacity which is close to the upper bound.

WITHDRAWN: Design and characteristics response of spiral patch monopole antenna on FR4 substrate

Abstract This paper describes the design aspects and development of the Monopole antenna on FR-4 using a single spiral patch technique with the optimized performance parameters that support dual band wireless communication techniques that are working on different applications with improved efficiency and impedance bandwidth to meet present and future wireless demands. This designed antenna covers the frequency ranges from 1.5 GHz to 3.5 GHz for L and S-band applications. Ansys HFSS is used to design and simulate the desired antenna. Using Vector Network Analyzer MS2027C-Anritsu, Return loss, VSWR, and impedance (Smith chart) values are measured and validated. E field and H field Radiation patterns are alo measured and validated using anechoic chamber.

Performance Analysis of Improved Self Cancellation Technique for Wavelet Based OFDM Through Simulink Model

As per the most recent literature, Orthogonal Frequency Division Multiplexing (OFDM), a multi access technique, is considered most suitable for the 3G, 4G and 5G techniques in high speed wireless communication. What made OFDM most popular is its ability to deliver high bandwidth efficiency and superior data rate. Besides it, high value of peak to average power ratio (PAPR) and Inter Carrier Interference (ICI) are the challenges to tackle down via appropriate mitigation scheme. As a research contribution in the present work, an improved self-cancellation (SC) technique is designed and simulated through Simulink to mitigate the effect of ICI. This novel proposed technique (Improved SC) is designed over discrete wavelet transform (DWT) based OFDM and compared with conventional SC scheme over different channel conditions i.e. AWGN and Rayleigh fading environments. It is found that proposed DWT-OFDM with Improved SC scheme outperforms conventional SC technique significantly, under both AWGN and Rayleigh channel conditions. Further, in order to justify the novelty in the research contribution, a Split-DWT based Simulink model for Improved SC scheme is investigated to analyse the BER performance. This Split-DWT based Simulink model presented here foretells the future research potential in wavelet hybridization of OFDM to side-line ICI effects more efficiently.

Internet of Things and Synergic Deep Learning Based Biomedical Tongue Color Image Analysis for Disease Diagnosis and Classification

In recent times, internet of things (IoT) and wireless communication techniques become widely used in healthcare sector. Biomedical image processing is commonly employed to detect the existence of diseases using biomedical images. Tongue diagnosis is an efficient, non-invasive model to perform auxiliary diagnosis any time anywhere that is support the global necessity in the primary healthcare system. Conventionally, medical practitioners investigate the tongue features based on their expert's knowledge comes from experience. In order to eradicate the qualitative aspects, tongue images can be quantitatively examined, offering an effective disease diagnostic process in such a way that the physical harm of the patients can be minimized. Numerous tongue image analysis approaches exist in the literature, it is required to develop automated deep learning (DL) models to diagnose the diseases using tongue image analysis. In this view, this paper designs an automated IoT and synergic deep learning based tongue color image (ASDL-TCI) analysis model for disease diagnosis and classification. The proposed ASDL-TCI model operates on major stages namely data acquisition, pre-processing, feature extraction, classification, and parameter optimization. Primarily, the IoT devices are used to capture the human tongue images and transmitted to the cloud for further analysis. In addition, median filtering based image pre-processing and SDL based feature extraction techniques are employed. Moreover, deep neural network (DNN) based classifier is applied to determine the existence of the diseases. Lastly, enhanced black widow optimization (EBWO) based parameter tuning process takes place to enhance the diagnostic performance. For assessing the effectual performance of the ASDL-TCI model, a set of simulations take place on benchmark tongue images and examined the results under distinct dimensions. The simulation outcome verified the enhanced diagnostic performance of the ASDL-TCI model over the compared methods with the maximum precision, recall, and accuracy of 0.984, 0.973, and 0.983.

SWIPT Model Adopting a PS Framework to Aid IoT Networks Inspired by the Emerging Cooperative NOMA Technique

We present the design for an ultra-low latency and low energy Internet of Things (IoT) network inspired by the emerging cooperative Non-Orthogonal Multiple Access (NOMA) wireless communication technique. The IoT network model consists of a source at the center of the network, a near device inside the network, and a far device outside the network. The far device is in the near proximity of the near device, however. We deploy the near device as a relay to assist the far device. The near device is assumed to be a low energy node. As a result, the near device cannot forward signals to the far device through its own power. We therefore design the IoT network to apply the Simultaneous Wireless Information and Power Transfer (SWIPT) technique so that the near device would be able to harvest energy and use it to forward signals. Two cooperative IoT network scenarios are examined: Half-Duplex (HD) and Full-Duplex (FD) relaying, each with and without eavesdroppers. The design also exploits Power Splitting (PS) factors for fairness in Quality of Service (QoS) for the devices. Novel analysis expressions are obtained accuracy and approximation of closed-forms for Outage Probability (OP), secrecy OP, system throughput and Jain’s fairness index. The analysis results are proved and verified by Monte Carlo simulation results.

Connected Homes: Inclusion of IoT in Indian Households

Smart Homes system has gained a huge demand in last few years as they improve the standard of living and give user an easy life. Any house that is integrated with automated technology (i.e., has connectivity in nearly all devices) is called a smart home. The concept of smart home can be explored more by IoT (Internet of Things) and cloud computing through which daily household activities and device can be controlled, monitored and managed using wireless communication techniques. These days’ big organizations are investing heavily in this technology and coming up with new updates that are increasing new business opportunities and the expansion in acceptance of IoT technology especially in companies that produce raw materials, automobile industry and health care sector are encouraging the market growth in a positive way. The research study will analyze the demand, trends and consumer behavior of smart home devices and its potential impact on business turnover, economy and market. The survey will be based on primary data collection with the help of questionnaire. A ranking of the various critical success factors provided the list of factors that consumers that Indian consumers believe to be important while adopting an IoT enabled smart home.

Deep-Unfolded Sparse CDMA: Multiuser Detector and Sparse Signature Design

Sparse code division multiple access (SCDMA) is a promising non-orthogonal multiple access technique for future wireless communications. In SCDMA, transmitted symbols from multiple users are coded by their own sparse signature sequences, and a base station attempts to detect those symbols using the signature sequences. In this paper, we present a new deep-unfolded multiuser detector called a complex sparse trainable projected gradient (C-STPG) detector for SCDMA systems. Deep unfolding is a deep learning method that tunes trainable parameters in iterative algorithms using supervised data and deep learning techniques. The proposed detector provides a much superior detection performance over that of the LMMSE detector. Other advantages of the proposed detector include a low computational complexity in execution and a low training cost owing to the small number of trainable parameters. In addition, we propose a novel joint learning strategy called gradual sparsification for designing sparse signature sequences based on deep unfolding. This method is computationally efficient in optimizing a set of sparse signature sequences. Numerical results show that the gradual sparsification successfully yields sparse signature sequences with a smaller symbol error rate than those of randomly designed sparse signature sequences.

Underwater Optical Wireless Communications in Swarm Robotics: A Tutorial

Underwater swarm robotics is an emerging topic. Compared to individual autonomous vehicles, high-capacity communication links are required between the mobile agents. In this tutorial, suitable communication technologies are studied, with emphasis on LED-based underwater optical wireless communications. A comprehensive overview about challenges, advances, and practical aspects of underwater swarm robotics employing optical wireless communications is provided. The tutorial includes the following topics: (1) Channel modeling fundamentals; (2) Physical layer transmission techniques for underwater optical wireless communications; (3) Data link layer aspects and hybrid transmission schemes; (4) Ambient light and interference suppression; and (5) Realization aspects. Finally, suggestions regarding future work are given. The tutorial is intended for readers with a background or interest in electrical and information engineering.

Capacity Improvement in Reconfigurable Intelligent Surface Assisted MIMO Communications

Reconfigurable intelligent surface (RIS) is thought to be a potential key technique for future wireless communications due to its ability for manipulating the electromagnetic environment smartly. This paper focuses on the rank and capacity analysis when a RIS is introduced into a multiple-input multiple-output (MIMO) system. By establishing a system model for this communication system, various simulations are conducted for identifying the characteristics of the channel. The simulations of different distance between the access point (AP) and user equipment (UE) show that the condition number of the channel is worsen when the distance increases and the role of the RIS in rank improvement is weaken. The spatial distributions of the reciprocal condition number of the channel which corresponds to the RIS locations are obtained and rank-deficient zones are found in different AP, UE and RIS configurations, which depicts the spatial characteristics of the RIS-assisted MIMO channel. The simulations also indicate that the condition number of the channel not only varies with the RIS location, but is also affected by the antenna array size and orientation of AP and UE. In addition, when the AP has a larger amount of antennas than UE, it is advantageous to place the RIS near the UE rather than the AP to achieve better channel condition. Modulation and coding schemes are applied in the simulations for comparison and capacity improvement is witnessed. Beneficial suggestions for RIS deployment in the MIMO system are concluded according to the simulation results.

IEEE Access Special Section Editorial: Communications in Harsh Environments

Communication systems deployed in harsh environments, such as high-speed trains, subways, deserts, trenches, forests, and underground mines, should be specially constructed to withstand extreme conditions such as high or low temperatures, corrosive humidity, extreme weather, or excessive dust and dirt. Such applications require specially designed wireless communication, fiber-optic communications, satellite communication, or signal processing techniques that can perform under extreme conditions and meet the QoS, security, and reliability requirements. Quite often, communications in harsh environments have an extremely low signal-to-noise ratio (SNR), high Doppler shift, and long latency, and often consume more power and energy. Bandwidth limitation in harsh environments requires spectrum efficient communications. The current state of art technologies such as massive MIMO, advanced modulation and channel coding, artificial intelligence, and signal processing provide different venues to explore this challenging area.

Joint Interference Alignment and Power Allocation Based on Stackelberg Game in Device-to-Device Communications Underlying Cellular Networks

As a promising wireless communication technique, Device-to-Device (D2D) can improve the utilization of spectrum resources, overall system throughput and reduce end-to-end delay, energy consumption by exploiting the direct radio link between local devices. Meanwhile, introducing D2D in cellular networks is very challenging due to the complex interference problem. To deal with the complex interference of D2D Underlying Cellular Networks, Interference alignment (IA) as an efficient interference management technique is extensively studied for D2D communications underlaying the cellular networks. However, most of the previous researches on IA only consider the equal power allocation for users, which leads to suboptimal overall system throughput. In order to further improve the system performance, in this paper, we propose a joint power allocation based on stackelberg game and interference alignment algorithm (STPA-IA) to eliminate the complex interference in D2D communications underlaying cellular networks. In this joint approach, the base station (BS) is modeled as the leader while the D2D pairs are followers. The performance of network system and that of D2D users are regarded as the revenues of leader and followers in stackelberg game. The strategy of the leader (BS) is to get the maximum benefits by reducing the interference, while the followers tend to (D2D pairs) maximize their own utility according to leader's strategy. The non-cooperative game is proved to get the nash equilibrium by the above strategies. Moreover, the close-form expression of the allocated power by maximum the unity function of leader and followers is derived. Extensive simulation results demonstrate that the proposed algorithm outperforms previous works in terms of sum-rate with lower time complexity.

Machine Learning Applied to Problem-Solving in Medical Applications

Physical health plays an important role in overall well-being of the human beings. It is the most observed dimension of health among others such as social, intellectual, emotional, spiritual and environmental dimensions. Due to exponential increase in the development of wireless communication techniques, Internet of Things (IoT) has effectively penetrated different aspects of human lives. Healthcare is one of the dynamic domains with ever-growing demands which can be met by IoT applications. IoT can be leveraged through several health service offerings such as remote health and monitoring services, aided living, personalized treatment, and so on. In this scenario, Deep Learning (DL) models are employed in proficient disease diagnosis. The current research work presents a new IoT-based physical health monitoring and management method using optimal Stacked Sparse Denoising Autoencoder (SSDA) technique i.e., OSSDA. The proposed model utilizes a set of IoT devices to collect the data from patients. Imbalanced class problem poses serious challenges during disease diagnosis process. So, the OSSDA model includes Synthetic Minority Over-Sampling Technique (SMOTE) to generate artificial minority class instances to balance the class distribution. Further, the hyperparameter settings of the OSSDA model exhibit heavy influence upon the classification performance of SSDA technique. The number of hidden layers, sparsity, and noise count are determined by Sailfish Optimizer (SFO). In order to validate the effectiveness and performance of the proposed OSSDA technique, a set of experiments was conducted on diabetes and heart disease datasets. The simulation results portrayed a proficient diagnostic outcome from OSSDA technique over other methods. The proposed method achieved the highest accuracy values i.e., 0.9604 and 0.9548 on the applied heart disease and diabetes datasets respectively.

PAPR Reduction in MIMO-OFDM Systems Using Low- Complexity Additive Signal Mixing

A MIMO-OFDM wireless communication technique possesses several advantages accrued from combining MIMO and OFDM techniques such as increased channel capacity and improved BER performance. This has made the technique very amiable to current and future generations of communication systems for high data-rate transmission. However, the technique also inherits the high PAPR problem associated with OFDM signals—a problem still requiring a practical solution. This work proposes a PAPR reduction algorithm for solving the problem of high PAPR in MIMO-OFDM systems. The proposed method uses a low-complexity signal mixing concept to combine the original transmit signal and a generated peak-cancelling signal. The computational complexity of the proposed method is O(M) , which is very much less than O(N log2 N) of the FFT algorithms. This is because M, which denotes the number of nonzero peakcancelling samples, is much less than N, the FFT window size. The proposed method was found to achieve high PAPR reductions while utilizing only a few nonzero peak-cancelling samples and it does not significantly change the power of the transmitted signal. For example, with M=5% of 256-point IFFT samples, corresponding to a data rate loss of 4.8%, a large PAPR reduction of 5.9 dB could be achieved at a small power loss of 0.09 dB. Compared with other methods proposed in literature, the proposed method was found to outperform them in terms of PAPR reductions and BER performance.