Concurrent Transmissions Research Articles

Federated Learning in Multi-RIS-Aided Systems

The fundamental communication paradigms in the next-generation mobile networks are shifting from connected things to connected intelligence. The potential result is that current communication-centric wireless systems are greatly stressed when supporting computation-centric intelligent services with distributed big data. This is one reason that makes federated learning come into being, it allows collaborative training over many edge devices while avoiding the transmission of raw data. To tackle the problem of model aggregation in federated learning systems, this article resorts to multiple reconfigurable intelligent surfaces (RISs) to achieve efficient and reliable learning-oriented wireless connectivity. The seamless integration of communication and computation is actualized by over-the-air computation (AirComp), which can be deemed as one of the uplink nonorthogonal multiple access (NOMA) techniques without individual information decoding. Since all local parameters are uploaded via noisy concurrent transmissions, the unfavorable propagation error inevitably deteriorates the accuracy of the aggregated global model. The goals of this work are to 1) alleviate the signal distortion of AirComp over shared wireless channels and 2) speed up the convergence rate of federated learning. More specifically, both the mean-square error (MSE) and the device set in the model uploading process are optimized by jointly designing transceivers, tuning reflection coefficients, and selecting clients. Compared to baselines, extensive simulation results show that 1) the proposed algorithms can aggregate model more accurately and accelerate convergence and 2) the training loss and inference accuracy of federated learning can be improved significantly with the aid of multiple RISs.

Realization of multiband communications using different Rydberg final states

Rydberg atoms can serve as an atomic radio frequency receiver for digital and analog information transmission. In this paper, a ladder-type electromagnetically induced transparency system is prepared in a room temperature cesium atomic vapor cell. Microwave electric fields in the Ku band at a frequency of 12.52 GHz and the Ka band at a frequency of 39.80 GHz are used as two-channel communication carriers to demonstrate concurrent information transmission. Analog and digital communications are demonstrated by performing audio and pseudo-random binary sequence signal transmission, respectively. The dynamic range of the proposed system is ∼50 dB, and the communication bandwidth is more than 10 MHz. The obtained results demonstrate the fundamental principles of two- or multi-band communication systems based on different Rydberg final states.

Wireless, Battery-Free, and Fully Implantable Micro-Coil System for 7 T Brain MRI.

An elegant solution for the concurrent transmission of data and power is essential for implantable wireless magnetic resonance imaging (MRI). This paper presents a self-tuned open interior microcoil (MC) antenna with three useful operating bands of 300 (7 T), 400, and 920 MHz, for blood vessel imaging, data telemetry, and efficient wireless transmission of power, respectively. The proposed open interior MC antenna contains two mirrorlike arms with diameters and lengths of 2.4 mm and 9.8 mm, respectively, to avoid blood flow blockage. To wirelessly show LED glow on a saline based phantom, the MC was fabricated on a flexible polyimide material and combined with a miniaturized rectifier and a micro-LED. Using a path gain, the power transfer efficiency (PTE) of the MC rotation was also analyzed. Additionally, the PTE was calculated for a range of distances between 25 and 60 mm, and a -27.1 dB PTE attained at a distance of of 30 mm. Based on the recommendations of the International Commission on Non-Ionizing Radiation Protection for human brain safety when exposed to radio-frequencies from external transmitter, a specific absorption rate analysis was analyzed. Measurements of the s-parameters were noted using a saline solution and blood vessel model to imitate a realistic human head. They were found to correlate reasonably with the simulated results.

Combating Packet Collisions Using Non-Stationary Signal Scaling in LPWANs

LoRa, a representative Low-Power Wide Area Network (LPWAN) technology, has been shown as a promising platform to connect Internet of Things. Practical LoRa deployments, however, suffer from collisions, especially in dense networks and wide coverage areas expected by LoRa applications. Existing collision resolving approaches do not exploit the modulation properties of LoRa and thus cannot work well for low-SNR LoRa signals. We propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NScale</i> to decompose concurrent transmissions by leveraging subtle inter-packet time offsets for low SNR LoRa collisions. NScale (1) translates subtle time offsets, which are vulnerable to noise, to robust frequency features, and (2) further amplifies the time offsets by non-stationary signal scaling, i.e., scaling the amplitude of a symbol differently at different positions. In practical implementation, we propose a noise resistant iterative symbol recovery method to combat symbol distortion in low SNR, and address frequency shifts incurred by CFO and packet time offsets in decoding. We propose optimized designs for diminishing the time costs of computation-intensive tasks and meeting the real-time requirements of LoRa collision resolving. We theoretically show that NScale introduces < 1.7 dB SNR loss compared with the original LoRa. We implement NScale on USRP N210 and evaluate its performance in both indoor and outdoor networks. NScale is implemented in software at the gateway and can work for COTS LoRa nodes without any modification. The evaluation results show that NScale improves the network throughput by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.3\times $ </tex-math></inline-formula> for low SNR collided signals compared with other state-of-the-art methods.

A Deep Q-Network Approach to Optimize Spatial Reuse in WiFi Networks

The proliferation of IEEE 802.11 or WiFi networks, and the explosive growth in traffic demands call for solutions to maximize the capacity of WiFi networks. Hence, maximizing the spatial reuse of WiFi networks is critical as doing so allows multiple concurrent transmissions. In this respect, a critical network parameter, Clear Channel Assessment (CCA) threshold, plays a vital role as it dictates whether a node is allowed to transmit after sensing the channel. In this paper, we propose to use Deep Q-network (DQN) under two learning patterns to select the CCA threshold of devices. We further consider Transmit Power Control (TPC) in conjunction with CCA threshold selection to improve the capacity of a WiFi network. The simulation results show that our approach is capable of selecting the optimal CCA threshold for each device. As a result, the average throughput is 62.4% higher than that of a legacy Dynamic Sensitivity Control (DSC) algorithm.

FSAQoS

To ensure a successful transfer of messages in Vehicular Ad hoc Networks (VANETs), data communication channels between vehicles must meet specific standards. As a result, determining the Quality of Service (QoS) of the communication links established among vehicles is a critical task. In this paper, we present a Fuzzy System for Assessment of Quality of Service (FSAQoS), in which we consider two models (FSAQoS1 and FSAQoS2) to assess QoS in Software-Defined VANETs (SDN-VANETs). FSAQoS1 takes into consideration the latency of message transmission between neighboring vehicles, the reliability of data exchange, as well as the beacon signals disseminated across the network that inform vehicles about the state and location of their neighbors. In addition to these parameters, FSAQoS2 considers the interference of the concurrent transmission of nearby vehicles. We evaluate the proposed system by computer simulations. From the evaluation results, we see that FSAQoS2 shows better results than FSAQoS1, although its complexity is higher.

Performance of a hybrid dual-hop and multi-hop network based on NOMA

ABSTRACT In this work, a novel network is proposed, which supports simultaneous dual-hop and multi-hop transmissions using the key concept of non-orthogonal multiple access (NOMA). The proposed network is designed in such a way that the existing infrastructure of a multi-hop network can be utilised efficiently for concurrent dual-hop transmissions. While one source transmits its signal to a remote destination via relay nodes in time slots, a maximum of another sources may transmit their information to the corresponding destinations using dual-hop transmissions via the same relay nodes over time slots. The performance of this hybrid dual-hop/multi-hop network is analysed and the impact of number of hops, transmit signal-to-noise ratio (SNR) and imperfection of successive interference cancellation (SIC) on the outage performance of each source is evaluated. Novel closed-form expressions for outage probability and ergodic capacity have been developed to assess the performance of the proposed network. In addition, an asymptotic performance analysis has also been also carried out for both outage probability and ergodic capacity of the proposed network.

C-Lop: Accurate contention-based modeling of MPI concurrent communication

MPI communication optimization is a crucial stage to optimize high-performance applications. As a formal analysis of MPI communication, the communication performance models have made some achievements in improving the efficiency of collective algorithms and optimizing communication scheduling. However, previous models are difficult to model asynchronous concurrent communication and do not take into account numerous contention factors. In this paper, we present C-Lop, an incremental MPI performance model based on τ-Lop. Firstly, C-Lop proposes a method for asynchronous modeling of concurrent communication. As the only model that considers concurrent transmission, τ-Lop describes the cost of the all processes as a whole without distinguishing the cost of each process. Here, C-Lop uses the idea of asynchronous modeling that describe the cost of the system by averaging the communication cost per process. It can describe the communication cost for some systems with out-of-sync communication more accurately. Moreover, C-Lop introduces the parameter C to represent the contention, and considers the contention of concurrent transmissions on network-on-chip, data reuse, and contention of noncommunication processes to make a more accuracy estimation. Furthermore, parameter C can be customized to fit more application scenarios. In addition, we evaluate several common collective algorithms, a matrix multiplication algorithm (SUMMA), and two kinds of communication in a three-dimensional multi-grid application on the Tianhe-3 prototype, and results show that C-Lop outperforms the competition.

Real-Time Information Exchange Strategy for Large Data Volumes Based on IoT.

In this paper, we study and analyse the real-time information exchange strategy of big data in the Internet of Things (IoT) and propose a primitive sensory data storage method (TSBPS) based on spatial-temporal chunking preprocessing, which substantially improves the speed of near real-time storage and writing of microsensory data through spatial-temporal prechunking, data compression, cache batch writing, and other techniques. The model is based on the idea of partitioning, which divides the storage and query of perceptual data into the microperceptual data layer and the perceptual data layer. The microaware data layer mainly studies the storage optimization and query optimization of raw sensory data and cleaned valid data; the aware data is the aggregation and statistics of microaware data, and the aware data layer mainly studies the storage optimization and query optimization of aware data. By arranging multiple wireless sensors at key monitoring points to collect corresponding data, building the core data service backend of the system, defining multifunctional servers, and constructing an optimal database model, we effectively solve the parameter collection and classification aggregation processing of different devices. To address the requirement of reliable and secure transmission in the process, we design a highly concurrent and high-performance TCP-based socket two-layer transmission framework and introduce the asymmetric encryption method (RSA) and data integrity verification method to design a transmission protocol that is both reliable and secure. The integration of big data and IoT is bound to bring the intelligence of human society to a new level with unlimited development prospects.

Quantum transport in p-type narrow channel with DC-biased double finger gate

The quantum transport in a p-type narrow channel device with a DC-biased double finger gate is investigated using a Luttinger four-band Hamiltonian and a propagation matrix approach. The results show that when the potential energy modulation effect produced by the finger gate is large, the quantum transport shows a resonance behavior indicative of large barriers in a double-barrier system. A simple analytical method based on an ideal resonant square quantum well approximation is used to predict the energies of the resonance peaks contributed by the light and heavy holes. The results show that the first conductance peak is formed at 2e2/h and is contributed by the heavy holes. A second conductance resonance peak is formed at 3e2/h due to the semi-reflection of the heavy holes and resonant transmission of the light holes. Finally, a third conductance resonance peak is formed at 4e2/h as a result of the concurrent resonant transmission of the light holes and heavy holes.

Distributed and Dynamic Channel Assignment Schemes for Wireless Mesh Network

Wireless mesh network (WMN) with wireless backhaul technology provides last-mile Internet connectivity to the end-users. In multi-radio multi-channel WMN (MRMC-WMN), routers provide multiple concurrent transmissions among end-users. The existence of interference among concurrent transmissions severely degrades the network performance. A well-organized channel assignment (CA) scheme significantly alleviates the interference effect. But in trying to minimize interference, the CA scheme may affect the network connectivity. So, the CA scheme has to consider both these two conflicting issues. In this paper, as part of the initial configuration of WMNs, we propose a game theory-based load-unaware CA scheme to minimize the co-channel interference and to maximize the network connectivity. To adapt to the varying network traffic, we propose a dynamic channel assignment scheme. This scheme measures the traffic-load condition of the working channels of each node. Whenever a node finds an overloaded channel, it initiates a channel switch. Channel switching based on the fixed threshold may result in a channel over/underutilization. For optimal channel utilization, we propose a fuzzy logic-based approach to compute the channel switch threshold. The contending nodes and their densities and loads dominantly affect the network capacity and hence the performance. In the context of network capacity enhancement, we have addressed these factors and focused on increasing the network capacity. The simulation results indicate that our proposed load-unaware and load-aware CA schemes outperform the other related load-unaware and load-aware CA approaches.

MotorBeat

More and more home appliances are now connected to the Internet, thus enabling various smart home applications. However, a critical problem that may impede the further development of smart home is overlooked: Small appliances account for the majority of home appliances, but they receive little attention and most of them are cut off from the Internet. To fill this gap, we propose MotorBeat, an acoustic communication approach that connects small appliances to a smart speaker. Our key idea is to exploit direct current (DC) motors, which are common components of small appliances, to transmit acoustic messages. We design a novel scheme named Variable Pulse Width Modulation (V-PWM) to drive DC motors. MotorBeat achieves the following 3C goals: (1) Comfortable to hear, (2) Compatible with multiple motor modes, and (3) Concurrent transmission. We implement MotorBeat with commercial devices and evaluate its performance on three small appliances and ten DC motors. The results show that the communication range can be up to 10 m.

A hybrid photonic link for concurrent transmission of millimeter wave and Sub 6 Ghz wave using polarization modulator

AbstractA stable, simple, compact, and economical photonic link which enables the sending of millimeter‐wave (mm‐wave) along with Sub‐6 GHz wave signal simultaneously is proposed in this study. Instead of using the conventional high‐cost Mach Zehnder modulation‐based link, here a cost‐efficient polarization modulator is used. The polarization modulator is used to obtain the tuneable frequency response and also to get a better performance compared to the Mach Zehnder modulator‐based system which is widely used. The concept of free space optics is introduced in this proposed system to guarantee a higher power efficiency and a higher data transmission. The advantages of mm‐wave signals and Sub‐6 GHz wave signals can be obtained in parallel by the simultaneous transmission of both signals through the multiplexed link. A 16‐QAM modulation is employed for RF signal in both mm‐wave and Sub6 GHz signal. The performance of the designed link is verified by bit error rate (BER) and the simulation gives a very small value of BER which indicates the least probability of error.

ND‐ADR: Nondestructive adaptive data rate for LoRaWAN Internet of Things

SummaryTypically, LoRaWAN utilizes an adaptive data rate (ADR) for resource assignment (e.g., spreading factor and transmit power) to a large number of end devices (EDs). However, the slow adaptation of the spreading factor and transmitting power strategy makes the ADR vulnerable to destructive concurrent transmissions, resulting in massive packet collision. Therefore, this paper analyzes the impact of massive concurrent transmissions and proposes a novel “nondestructive adaptive data rate (ND‐ADR)” approach to address the packet collision problem. The proposed ND‐ADR aims to monitor the destructive concurrent transmissions proactively and mitigate them by allocating nondestructive transmission time to EDs. The proposed ND‐ADR ensures high robustness and reliability by reducing the chances of destructive transmissions and retransmissions. Results show that the proposed ND‐ADR outperforms the existing state‐of‐the‐art ADRs in packet success ratio and energy consumption.

Diarrhoea outbreak caused by coinfections of Cryptosporidium parvum subtype IIdA20G1 and rotavirus in pre-weaned dairy calves.

Diarrhoea is one of the most important syndromes in neonatal calves. In industrialized nations with intensive animal farming, Cryptosporidium spp. and rotavirus are primary causes of calf diarrhoea, but the role of these and other enteric pathogens is not clear in China. In November and December 2018, a diarrhoea outbreak was identified in over 150 pre-weaned calves on a dairy farm in Heilongjiang Province, northeast China and approximately 60 calves died. To determine the cause of the outbreak, we analyzed 131 faecal samples collected from pre-weaned calves (0-2 months) during (n=114) and after the outbreak (n=17). Initially, 10 diarrheic samples during the outbreak and 10 non-diarrheic samples after the outbreak were screened for rotavirus, coronavirus, Escherichia coli K99 and Cryptosporidium parvum by using an enzymatic immunoassay (EIA). In addition, 81 other samples were tested specifically for rotavirus by EIA, and all 131 samples were analyzed for Cryptosporidium spp., Giardia duodenalis and Enterocytozoon bieneusi by PCR. The initial EIA analysis identified C. parvum (8/10) and rotavirus (5/10) as the dominant pathogens in calves during the outbreak, while both pathogens were detected at lower frequency after the outbreak (2/10 and 1/10, respectively). Further PCR analyses indicated that the occurrence of C. parvum infections in calves was significantly higher during the outbreak (75.4%, 86/114) than after the outbreak (11.8%, 2/17; odds ratio [OR]=23.0), and was significantly associated with the occurrence of watery diarrhoea (OR=15.7) and high oocyst shedding intensity. All C. parvum isolates were identified as subtype IIdA20G1. Among other pathogens analyzed, the overall prevalence of rotavirus, G. duodenalis and E. bieneusi was 19.8% (20/101), 38.9% (51/131) and 42.0% (55/131) in calves, respectively, without significant differences during and after the outbreak. Among the three pathogens, only the rotavirus infection was associated with diarrhoea in calves. More importantly, coinfections of C. parvum and rotavirus were significantly associated with the occurrence of watery diarrhoea in calves and were seen only during the outbreak. Thus, C. parvum subtype IIdA20G1 and rotavirus appeared to be responsible for this diarrhoea outbreak. Control measures should be implemented to effectively prevent the concurrent transmission of these enteric pathogens in pre-weaned dairy calves in China.

Cognitive radio based spectrum sharing models for multicasting in 5G cellular networks: A survey

The dramatic growth of smart devices catering content-centric data traffic has fueled the need for group communication services in cellular networks, among which multicasting is of particular interest. The unique potential of multicasting to fulfill the vision of a hyper-connected society in 5G networks is underlined by its ability to manage resources efficiently, while supporting concurrent transmission of common data to a large number of users. The bandwidth intensive communication requirements of multimedia multicast applications demand optimal usage of the spectral resources. Moreover, massive capacity, connectivity and ultra low latency requirements of the content centric applications have triggered the urge to get the content nearer to the users and employ short range communication, thus leading to densification of cellular networks. However, the limited availability of radio resources coupled with elevated levels of interference pose a major hindrance towards enabling spectrum reuse in dense networks. Cognitive radio (CR) is a viable technology to enhance the spectral efficiency, by allowing low priority unlicensed users to share the spectrum of high priority licensed users. The ability of CR to adapt its transmission parameters according to the application demands makes it a promising candidate for efficient spectrum management and interference mitigation in 5G cellular networks. This paper presents a survey on the state-of-the art techniques proposed for catering multicast services in CR networks. The study provides a detailed analysis on the utility of various spectrum sharing models of CR networks in fulfilling the end-to-end communication goals of multicast services. We particularly emphasize on the nature of multicast traffic, the key enabling techniques and methodologies employed for enhancing the efficacy of such services and approaches for mitigating interference experienced by the licensed users. By carefully analyzing the existing works, we provide possible design guidelines for multicast services in future 5G networks. Finally, we identify few open issues and discuss the future research directions.

An Ingenious Multiport Interferometric Front-End for Concurrent Dual-Band Transmission

This article proposes and presents an innovative approach to realizing the concurrent dual-band transmission with only a single front-end and local oscillator at radio frequency (RF). Fundamentally, the proposed concurrent dual-band front-end is based on the conventional multiport interferometric architecture for single-band operation. Nevertheless, the conventional variable loads are replaced by diode networks with IF input signals to produce the RF signals at their designated center frequencies. Furthermore, due to the linear characteristics of a multiport network, the signals with different data contents will be mixed into both RF channels. To this end, an inverse matrix operation is applied to reversely convert the original data streams before the modulations of IF input signals. As a result, the two original data streams can be effectively modulated into specific RF channels (for transmission) with minimal interchannel interferences based on this configuration. In addition to the theoretical analyses, this innovative concurrent dual-band transmitting front-end has been investigated and verified with M-quadrature amplitude modulation (QAM) signals in simulations and experiments. All outcomes demonstrate excellent performances in concurrent dual-band transmission with significant reductions in both size and biasing power.

Content Distribution Based on Joint V2I and V2V Scheduling in mmWave Vehicular Networks

With the explosive growth of vehicle applications, vehicular networks based on millimeter wave (mmWave) bands have attracted interests from both academia and industry. mmWave communications are able to utilize the huge available bandwidth to provide multiple Gbps transmission rates among vehicles. In this paper, we address the content distribution scheduling problem in mmWave vehicular networks. It has been challenging for all vehicles in the same network to complete content downloading due to the limited communication resources of roadside units (RSUs) and the high mobility of vehicles. We propose a joint vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) scheduling scheme to minimize the total number of content distribution time slots from a global optimization perspective. In the V2I phase, the RSU serially transmits integrity content to vehicles, which are selected according to the vehicular network topology and transmission scheduling scheme. In the V2V phase, full-duplex communications and concurrent transmissions are exploited to achieve content sharing between vehicles and improve transmission efficiency. Performance evaluations demonstrate that our proposed scheme reduces the number of time slots and significantly improves system throughput when compared with other schemes, especially under large-size file transfers and a large number of vehicles.

Interference Aware Cooperative Routing for Edge Computing-Enabled 5G Networks

Recently, there has been growing research on developing interference-aware routing (IAR) protocols for supporting multiple concurrent transmission in next-generation wireless communication systems. The existing IAR protocols do not consider node cooperation while establishing the routes because motivating the nodes to cooperate and modeling that cooperation is not a trivial task. In addition, the information about the cooperative behavior of a node is not directly visible to neighboring nodes. Therefore, in this paper, we develop a new routing method in which the nodes’ cooperation information is utilized to improve the performance of edge computing-enabled 5G networks. The proposed metric is a function of created and received interference in the network. The received interference term ensures that the Signal to Interference plus Noise Ratio (SINR) at the route remains above the threshold value, while the created interference term ensures that those nodes are selected to forward the packet that creates low interference for other nodes. The results show that the proposed solution improves ad hoc networks’ performance compared to conventional routing protocols in terms of high network throughput and low outage probability.

Visual Communication Design Based on Collaborative Wireless Communication Video Transmission

With the development of wireless communication technology, video and multimedia have become an integral part of visual communication design. Designers want higher interactivity, diversity, humanization, and plurality of attributes in the process of visual communication. This makes the process of visual communication have high requirements for the quality and real-time data transmission. To address the problem of transmitting HD video in a heterogeneous wireless network with multiple concurrent streams to improve the transmission rate and thus enhance the user experience, with the optimization goal of minimizing the system transmission delay and the delay difference between paths, the video sender and receiver are jointly considered, and the video transmission rate and the cache size at the receiver are adaptively adjusted to improve the user experience, and a cooperative wireless communication video transmission based on the control model for video transmission based on cooperative wireless communication is established, and video streams with self-similarity and long correlation are studied based on Pareto distribution and P / P / l queuing theory, based on which an adaptive streaming decision method for video streams in heterogeneous wireless networks is proposed. Simulation results show that the proposed multistream concurrent adaptive transmission control method for heterogeneous networks is superior in terms of delay and packet loss rate compared with the general load balancing streaming decision method, in terms of transmission efficiency and accuracy.