Multiple Transceivers Research Articles

On the utilization of the adjoint method in microwave tomography.

In microwave imaging, the adjoint method is widely used for the efficient calculation of the update direction, which is then used to update the unknown model parameter. However, the utilization and the formulation of the adjoint method differ significantly depending on the imaging scenario and the applied optimization algorithm. Because of the problem-specific nature of the adjoint formulations, the dissimilarities between the adjoint calculations may be overlooked. Here, we have classified the adjoint method formulations into two groups: the direct and indirect methods. The direct method involves calculating the derivative of the cost function, whereas, in the indirect method, the derivative of the predicted data is calculated. In this review, the direct and indirect adjoint methods are presented, compared, and discussed. The formulations are explicitly derived using the two-dimensional wave equation in frequency and time domains. Finite-difference time-domain simulations are conducted to show the different uses of the adjoint methods for both single source-multiple receiver, and multiple transceiver scenarios. This study demonstrated that an appropriate adjoint method selection is significant to achieve improved computational efficiency for the applied optimization algorithm.

Future Prediction of Close Contacts in IoT-based Contact Tracing System using a New Real-Life Dataset.

Contact tracing is an effective method for mitigating the infectious diseases spread and it played a crucial role in reducing COVID-19 outbreak. Since the pandemic, there has been an increased concern regarding people's health in hospital and office settings, as these limited air exchange spaces provide a conductive medium for virus spread. Various technologies were used to recognize close contacts autonomously, in addition, multiple machine learning attempts were carried out to determine proximity in contact tracing. This study, however, proposes a unique concept in contact tracing: forecasting future close contact prior to occurrence in order to regulate and control it rather than tracking past occurrences. For our research, we constructed a completely new real-life dataset that was collected during the pandemic in a hospital infectious ward (Alfred Hospital, Melbourne, Australia) utilizing a Bluetooth Low Energy (BLE) Internet of Things (IoT) system. Our prediction technique considers two types of environments: single transceiver environments and multiple transceivers settings, these transceivers record the nearby tags' BLE received signal strength indicator (RSSI) values. The system employs mathematical models and supervised machine learning (ML) algorithms to solve regression and classification problems for workers' pattern recognition within the environment. The output is compared using different metrics, such as efficiency, which reached more than 80%, root mean square errors and mean absolute errors which were as low as 2.4 and 1.2 respectively in some models.

UniFi

In recent years, considerable endeavors have been devoted to exploring Wi-Fi-based sensing technologies by modeling the intricate mapping between received signals and corresponding human activities. However, the inherent complexity of Wi-Fi signals poses significant challenges for practical applications due to their pronounced susceptibility to deployment environments. To address this challenge, we delve into the distinctive characteristics of Wi-Fi signals and distill three pivotal factors that can be leveraged to enhance generalization capabilities of deep learning-based Wi-Fi sensing models: 1) effectively capture valuable input to mitigate the adverse impact of noisy measurements; 2) adaptively fuse complementary information from multiple Wi-Fi devices to boost the distinguishability of signal patterns associated with different activities; 3) extract generalizable features that can overcome the inconsistent representations of activities under different environmental conditions (e.g., locations, orientations). Leveraging these insights, we design a novel and unified sensing framework based on Wi-Fi signals, dubbed UniFi, and use gesture recognition as an application to demonstrate its effectiveness. UniFi achieves robust and generalizable gesture recognition in real-world scenarios by extracting discriminative and consistent features unrelated to environmental factors from pre-denoised signals collected by multiple transceivers. To achieve this, we first introduce an effective signal preprocessing approach that captures the applicable input data from noisy received signals for the deep learning model. Second, we propose a multi-view deep network based on spatio-temporal cross-view attention that integrates multi-carrier and multi-device signals to extract distinguishable information. Finally, we present the mutual information maximization as a regularizer to learn environment-invariant representations via contrastive loss without requiring access to any signals from unseen environments for practical adaptation. Extensive experiments on the Widar 3.0 dataset demonstrate that our proposed framework significantly outperforms state-of-the-art approaches in different settings (99% and 90%-98% accuracy for in-domain and cross-domain recognition without additional data collection and model training).

Three-Dimensional Motion Compensation Method Based on Sparse Array Designed for Time-Division Multiplexing Multiple-Input-Multiple-Output Through-Wall Radar

A large-aperture radar composed of a multiple-input-multiple-output (MIMO) planar array can complete 3D through-wall imaging (TWI), but the simultaneous work of the multiple transceiver channels leads to difficulties in designing the hardware. In engineering, multiple transceiver channels are usually realized by time-division multiplexing (TDM) in MIMO radar, which is called TDM MIMO radar. A time delay will be introduced when the channels are switched, which will cause high sidelobes and position deviation in the 3D imaging of moving targets, also known as range migration. This paper proposes a motion compensation algorithm based on sparse array, designed to eliminate range migration in moving targets in 3D TWI scenes. In the proposed algorithm, the coincident array elements of the equivalent array are used as the compensation channels to calculate the position difference of the target, which can correct the remaining MIMO channels. The proposed algorithm is compared with no compensation, and the reference-channel-based motion compensation algorithm (RCMCA). According to the simulation and experimental results, the proposed motion compensation algorithm can effectively eliminate sidelobes, and keep the position deviation within 0.30 m in the 3D TWI of moving targets under the TDM MIMO radar, without increasing the system complexity.

Achievable Rate Region for uRLLC Interference Channel With Finite Blocklength Transmission

Finite blocklength is a favorable way to meet the extremely low-latency requirement, which leads to the classic Shannon's capacity formula no longer suitable. With the achievable rate region, optimization problems on three different scenarios are considered: (i) joint design of power and blocklength allocation for two transceiver pairs with single-antenna transmitter; (ii) beamforming and blocklength design for the two transceiver pairs with multi-antenna transmitter; (iii) beamforming and blocklength design for the multiple transceiver pairs with multi-antenna transmitter. Under the finite blocklength transmission mode, the achievable rate expression is a complicated function with respected to the blocklength and power allocation coefficients or beamforming vector, which makes the optimization problems difficult to solve. In this paper, by analyzing the monotonic and concaveconvex properties of achievable rate with interference channel (IFC), we formulate the achievable rate region as the convex hull of a series of power/beamforming and blocklength rate regions for two-user systems with IFC, as well as the Pareto boundary of achievable rate region on the blocklength and beamforming vector for the two-user systems, respectively. Sequentially, the optimal blocklength and power coefficients are derived in the closed-form and optimal beamforming vectors are also obtained by transforming the non-convex problem into convex one. Numerical results provide the perspective of looking at the rate region with finite blocklength.

Efficient Channel Estimation in Multiple Input Multiple Output Communication Systems using Hybrid Intelligence‐based Deep Learning Model using Horse Dingo Optimizer

AbstractThe estimation of the channel in multiple input multiple output (MIMO) systems over wireless communication has faced many challenges, such as high bit rate transmission with less time complexity, low error rate, and high convergence rate. And also, there is some potential for enhancing the system performance regarding channel efficiency diversity. MIMO system uses a huge count of antennas on the receiver and the transmitter side. This increases the cost requirements and power consumption. For achieving coherent detection in the MIMO system, optimization such as water filling and beam forming are required to find the proper channel. Hence, multiple transceivers used in both the transmitter side and receiver side create a channel estimation issue that is complicated when analyzed to a single input, single output system. Therefore, several solutions have been recommended to decrease the computational cost and power consumption in channel estimation of MIMO systems. This work intends to propose a novel deep structured architecture to handle the channel estimation problem in a MIMO system. The major objective of the developed method is to validate the channel coefficients of MIMO at the transmitter according to the obtained SNR feedback data packet from an acceptor with the help of the hybrid intelligence‐based deep learning model (HI‐DLM). For both scenarios, the HI‐DLM is introduced, in which the convolution neural network (CNN) is integrated with other deep‐structured architecture. Especially, the fully connected layers of CNN are restored by the long short‐term memory. In the HI‐DLM‐aided channel estimation, the hyperparameter optimization is accomplished by the novel dingo‐horse herd optimization for reducing the mean square error and bit error rate to acquire the estimated channel. The corresponding algorithm is validated on the communication of the MIMO system by experimentations. Thus, it is revealed that the offered algorithm provides better convergence and less computational cost.

Мобільна mesh-мережа для управління роєм об'єктів

The purpose of the article is to develop an adaptive wireless mesh-network architecture for managing technological processes, robotic devices and other objects. The article describes the architecture of a wireless mesh-network. The concept of a wireless mesh-network is described. The mesh-network is self-organizing, adaptive, and to be work autonomously able. The presented wireless mesh node controller architecture is the basis for small control systems for many objects and a swarm of objects. The interaction of network nodes is carried out using several transceivers. Multiple transceivers allow for the separation of control traffic and data traffic on different channels. The protocol stack is optimized for the functioning of the mesh network. The topology of a mesh network can change dynamically. That is, network nodes can move in space without losing communication with each other. The current state of the network is updated with a period that depends on the rate of change of the network node in the space. The mesh network configuration strategy and algorithms allow you to effectively build a network topology and establish interaction between network nodes. There can be many objects in the network that can act as a relay. A repeater can be a network node and a special dedicated repeater node. The low cost of network nodes makes it possible to create a low-cost network for performing various functions of object control and data transmission. The network can be used to manage a swarm of objects. Proprietary software is used to increase the efficiency of forming routing tables taking into account cluster structures in a mesh network. The mesh network can be used to control IoT objects, robotic objects, as well as a variety of objects and control systems for various technological processes.

A Review on Critical Data Transmission in Wireless Body Area Networks

Wireless body area networks (WBANs) assemble multiple transceiver nodes in, on, or around a patient's body to transmit physiological signals to the sink node and further send it to the medical personnel via a medical server. WBANs a sensor network that is characterized as energy-dependent. Due to this finite nature, the deployment of intelligent utilization is needed. Quality of service (QoS) is another area that needs rapt attention to receive exactly what was sent from the source node to the destination node and throughput. Critical data transmission is characterized by abnormal data status that requires an urgent response from the medical personnel without delay to save the patient's life. In this review article, we propose a review of critical data transmission in wireless body area networks. However, most past articles in this line focus more on energy-efficient, security and privacy, quality of the links, throughput, network maximization, and so on. None of them looks into the direction of transmitting critical data directly to the sink node without multi-hopping of the physiological signals between intermediate nodes, which wastes the time of transmission to save patient life. This disparity between these scholars motivates us to fill the gap between them. This review article briefly discussed the state-of-the-art critical data transmission in WBANs alongside the WBANs architecture and implementation. Furthermore, a pragmatic approach to determining the threshold's degree of critical data index sensed during transmission was also considered.

Efficient MIMO Configuration for Bi-Directional Vertical FSO Link with Multiple Beam Induced Pointing Error

We proposed the statistical misalignment model and the power-efficient configuration of transceivers for bi-directional multi-input and multi-output (MIMO) based vertical free space optical (FSO) links. Spatial diversity based MIMO FSO systems could be used to mitigate atmospheric fading issues. However, the increased number of channels can cause additional pointing error in pointing, acquisition and tracking (PAT) systems. The statistical misalignment model for detecting misalignment error is derived from the multiple transceivers. For the bi-directional characteristics of non-terrestrial back-haul networks, transmission performance is down-leveled to the worse in the asymmetric MIMO configuration of transceivers. The symmetric structure can mitigate the effect of increased pointing error to improve transmission performance. The proposed technique can be applied to the design of power-efficient FSO systems for non-terrestrial wireless back-haul networks.

Performance Analysis of Multi-Cell Association in Downlink MU-MIMO System with Arbitrary Beamforming

This article deals with the analysis of the multi-cell association setup, and it exploits the possibility of enhancing coverage in the envisioned sixth generation (6G) large-scale cellular networks. Specifically, we propose a simple, effective approach for finding a closed-form solution to the coverage probability of a given user in a multi-cell association regime of downlink multiple-user multiple-input multiple-output (MU-MIMO) systems. In particular, a Rayleigh fading channel is considered, wherein the transmitter has only the knowledge of the second-order statistics of the channel. The proposed work uses an indefinite quadratic formulation method and thereby investigates the effect of cell association in a correlated downlink broadcast channel with co-channel interference, additive white noise, and multiple transceiver antenna elements. In the results, we show that a predefined signal-to-interference-plus-noise ratio (SINR) threshold dictates an effective multi-cell association setup, and we identify the region in which a multi-cell association performs better that a single association-based network. The derived theoretical expressions in this paper are validated by the same means of simulation.

Hybrid Grey Wolf Optimization with Cuckoo Search‐based optimal channel estimation for energy efficient massive multiple input multiple output

SummaryThe massive multiple input multiple output (mMIMO) provides reliable base station (BS) for the mobile users (MUs) with CSI (channel state information) and jointly offers spectral efficiency (SE) and energy efficiency (EE). Conversely, because of the existence of multiple transceivers at both the transmitter and receiver side, the channel estimation (CE) issue is increasingly complex and expensive in terms of hardware and energy utilization. Hence, we have proposed an effective Hybrid Grey Wolf Optimization with Cuckoo Search (GWO‐CS) based optimal channel estimation for developing energy efficient mMIMO. The proposed GWO‐CS selects the optimal channel by jointly optimizing the spectral efficiency and reduces the SINR (signal to interference plus noise ratio). Experimental analysis of the performance of the proposed approach is carried out using existing approaches. The results obtained show that, the EE of the proposed GWO‐CS based CE provides 15–37 Mbits for varying quantization bits, 22.5–25 Mbits for different user equipment (UE) ranges and 7–24 Mbits for various SE. However, the existing approaches fail to provide such EE and this proves the efficiency of proposed approach.

Reconfigurable Intelligent Surface-Enabled Spectrum-Sharing Communications Based on Successive Interference Cancellation

In this letter, a reconfigurable intelligent surface (RIS)-enabled successive interference cancellation (SIC)-based spectrum sharing (SS) scheme is proposed for SS networks where multiple transceiver pairs communicate over the same spectrum at the same time. The key idea is to apply the SIC technique at each receiver and utilize RIS simultaneously, so as to reduce the interference among different transceiver pairs and to focus energy. Specifically, to minimize the total power consumption at all the transmitters under given data rate constraints, the decoding order at each receiver, the reflection coefficients at RIS, and the transmit power at each transmitter are jointly optimized. The formulated problem is a mixed-combinatorial-and-continuous optimization problem and thus is difficult to solve. To address this, a low-complexity but effective decoding order determining method is first proposed. Given the decoding orders, the reflection coefficients and the transmit power are alternately optimized with the help of the semidefinite relaxation method. Substantial performance gains are shown compared with traditional RIS-enabled SS scheme without SIC.

Symbol Detection Based on Back Tracking Search Algorithm in MIMO-NOMA Systems

One of the most important methods used to cope with multipath fading effects, which cause the symbol to be received incorrectly in wireless communication systems, is the use of multiple transceiver antenna structures. By combining the multi-input multi-output (MIMO) antenna structure with non-orthogonal multiple access (NOMA), which is a new multiplexing method, the fading effects of the channels are not only reduced but also high data rate transmission is ensured. However, when the maximum likelihood (ML) algorithm that has high performance on coherent detection, is used as a symbol detector in MIMO NOMA systems, the computational complexity of the system increases due to higher-order constellations and antenna sizes. As a result, the implementation of this algorithm will be impractical. In this study, the backtracking search algorithm (BSA) is proposed to reduce the computational complexity of the symbol detection and have a good bit error performance for MIMO-NOMA systems. To emphasize the efficiency of the proposed algorithm, simulations have been made for the system with various antenna sizes. As can be seen from the obtained results, a considerable reduction in complexity has occurred using BSA compared to the ML algorithm, also the bit error performance of the system is increased compared to other algorithms.

Multiple transceivers based wimax mesh network to optimize routing algorithm

The Base Station (BS) is a WiMAX (Worldwide Interoperability for Microwave Access) centralized scheduling mesh topology decision maker for scheduling the whole network including allocation of packets between the Subscribers (SSs) in the network through the BS. Hence, the system, which, by interference, especially affects the nodes, close to BS. A network routing algorithm was built for mesh topology named Energy Bit Minimum Routing (EBMR), which is used to optimize the chosen path. all nodes were fitted with a multi-channel and four scenarios were planned: the first scenario is called the Multi-Transceiver fitted both SSs with a multi-transceiver except at the brink without cap the number of parent nodes. Whereas the second scenario was called Closest Multi-Transceiver system no ceiling on the number of parent nodes, in this scenario only the nearest BS is fitted with multi-transceiver SSs. The third scenario used the Multi-Transceiver system but with cap the number of parent nodes by 30% for whole nodes network. The fourth scenario used the closest Multi-Transceiver system but with cap, the number of parent nodes by 30%, for whole nodes network. In scenarios, the system content considers 120 users as maximum. It will improve the network capacity, throughput, channel scheduling range and channel utilization ratio (CUR). WiMAX mesh topology is used to centralize scheduling and improve the performance system by finding the best route to centralizing the mesh network EBMR; consequently, it increases latency, CUR and distance scheduling, avoiding messing, otherwise. Multi-transceiver network is used to prevent primary interference and multi-channel network used to stop secondary interference. This paper develops two styles of network: the multi-transceiver multi-channel network and the closest multi-transceiver multi-channel device that uses the Time Division Multiple Access (TDMA) algorithm for EBMR-CS3,4 (Energy Bit Minimization Routing and centralized Scheduling). This algorithm is optimizing network efficiency by having higher throughput by preventing interaction with adjacent nodes and the scheduling duration and growing the device’s channel utilization ratio (CUR).

Analysis of wavelength deployment schemes in terms of optical network unit cost and upstream transmission performance in NG-EPONs

Next-generation Ethernet passive optical networks (NG-EPONs) were standardized by the IEEE 802.3 Working Group in 2020 [IEEE 802.3ca-2020–IEEE Standard for Ethernet Amendment 9: physical layer specifications and management parameters for 25 Gb/s and 50 Gb/s passive optical networks, 2020]. Due to the channel bonding technology [“Recent progress on 25G EPON and beyond,” in 42nd European Conference on Optical Communication (ECOC) (2016).] adopted by NG-EPONs, multiple wavelengths can be assigned to an optical network unit (ONU) simultaneously, leading to higher peak transmission rates. As a result, assigning traffic in multiple wavelength channels provides greater scheduling flexibility, a higher peak upstream rate, and better upstream transmission performance (i.e., lower latency); however, it leads to the use of high-cost ONUs with multiple transceivers and further increases the total cost of NG-EPONs. Therefore, selecting a proper wavelength deployment scheme is very important when designing future NG-EPONs. In this paper, we focus on the trade-off between ONU cost and the upstream performance in a static scenario, and we develop an integer linear programming model to formulate the problem. In addition, we propose a heuristic wavelength deployment scheme comparison and selection (WDSCS) algorithm to effectively select appropriate wavelength deployment schemes. According to our simulation results, our proposed WDSCS algorithm can efficiently find a finer number of deployment wavelengths to balance the cost of ONUs and the upstream transmission performance. The wavelength deployment schemes for future NG-EPONs can also be specified based on whether network operators prioritize network performance or cost.

A novel channel prediction method for MIMO‐OFDM in high‐speed environment

The OFDM system with multiple transceiver antennas is attractive to increase the spectrum or energy efficiency. Depending on the channel state information (CSI), precoding techniques offer array and multiplexing gain in such systems. However, if terminal equipment is fast moving, the CSI feedback would be outdated when it is applied to data transmission. This paper proposes a novel channel prediction method applicable for high-speed environment. Benefiting from the proposed structure, this method greatly improves the prediction accuracy, and meanwhile retains the low feedback overhead. Numerical results show that the performance of the proposed method outperforms conventional precoding methods in high-speed scenarios.

Investigation of Multiple Transceiver System for Free Space Optical Communication

In free space optical (FSO) communication, atmospheric turbulence has major impact on the stability of a free space optical transmission system. Laser beam with high coherency and intensity is commonly used to increase the transmission distance. However, with an increased distance, the stability of the system becomes more sensitive to the turbulence. In this work, a multiple transceiver system with signal summing approach is implemented to improve signal transmission stability. The performance of the proposed system is investigated with the intensity turbulence modeled. In comparison with the single transceiver system, the proposed system showed higher signal-to noise ratio and lower bit-error-ratio with doubled stability in terms of the improvement factor.

Indoor precise point positioning with pseudolites using estimated time biases iPPP and iPPP-RTK

The global navigation satellite system (GNSS) provides outstanding positioning services for outdoor activities with sufficient accuracies, but it has poor indoor performance. Indeed, indoor positioning is also expected to achieve the outdoor positioning level to cater to an even higher volume of user demands. A pseudolite (PL), also called a pseudosatellite, is a ground-based positioning system that offers flexible deployment and accurate “orbits”. The PL system can carry on the role of the GNSS to provide precise positioning for indoor users. The clock differences originating from ground-based transmitters cause unsynchronized timing issues and impede attempts to fix the integer ambiguity. Numerous studies have been conducted with an emphasis on time synchronization to obtain this ambiguity-fixed solution by employing multiple transceivers in transmitter-receiver combinations for self-calibration inside a regional network of the ground-based system. However, this process requires a large investment and complicates the positioning owing to its intricate implementation. Actually, time synchronization can easily be achieved with a transmitter-only PL system at a low cost once the clock bias between transmitters is properly handled. Thus, we propose and present indoor precise point positioning (iPPP) and indoor PPP-real-time kinematic (iPPP-RTK) to handle the PL clock bias efficiently. Experiments demonstrate that the transmitter-only PL system can be time-synchronized without high cost or complicated operations and that centimeter level indoor precise positioning can be reliably achieved with our proposed methods.

Архітектура контролера вузла адаптивної мобільної мережі з аморфною топологією

The purpose of the article is to develop an adaptive mobile network node architecture with an amorphous topology. The article describes the host controller architecture. The concept of a mobile network is described. The mobile network is adaptive, self-organizing, and able to operate autonomously. The presented mobile network node controller architecture is the object swarm control system basis. A stack of mobile network protocols is presented, consisting of a control protocol, a data exchange protocol and a configuration protocol. The nodes of the network controllers interaction is carried out using several transceivers. The use of multiple transceivers made it possible to distribute data traffic, configuration traffic, and management traffic over different channels, which made it possible to carry out information exchange at the same time. The protocol stack is minimized. The functionality of the host and the network object (swarm) is completely separated. The topology of the mobile network is not deterministic, amorphous and changes when the network objects move in space. In this case, some connections are lost and others arise. The routing tables are constantly updated. The network in accordance with the laid down algorithm, is able to build the necessary topology and organize the necessary connections in order to complete the task with a swarm of objects. The network is capable of building packet retransmission chains for remote network objects. Thus, the implementation of a mobile network at its low cost allows solving a certain range of problems. The performer can be either a separate object associated with the operator through a swarm of repeaters, or a swarm of objects. In order to increase the efficiency of the formation of routing tables and minimize the cluster structures in a mobile network, it is advisable to use optimization algorithms based on set theory. The mobile network is designed to control a swarm of objects, which can be UAVs, robotic objects and control systems for various technological processes.

Multiple Transceivers for IEEE802.16 Mesh Network to Avoid Confusion Routing and Scheduling

The speed of data transfer and the amount of space within the communication service, taking into account the cost, security, capacity, and specifications of WiMAX is highly important in communications. There are varies difficulties for routing in WiMAX, for example, delay, long scheduling, interference and progressively stringent Quality of Service (QoS) backing and burden parity. This paper proposes a multi-transceiver and multi-channel centralized routing and scheduling algorithm to avoid the impact of packet collision with neighbor nodes. The proposed algorithm looks for a short path from the subscriber station (SS) node to Base station (BS), while the optimal path is achieved when the whole path has the lowest (energy bit minimum routing (EBMR)). After the route is fixed, and the traffic demanded at each node is known, the total traffic arriving at a node is centrally scheduled in order to avoid the transmission interferences. The results from the multi and nearest multi-transceiver systems showed that the proposed algorithm has effectively minimize the length of scheduling in the in multi nearest multi -transceiver system. Moreover, the channel utilization ratio (CUR) is found to be improved over the implementation of the proposed system