Limited Data Rate Research Articles

A 0.3-to-1-GHz IoT Transmitter Employing Pseudo-Randomized Phase Switching Modulator and Single-Supply Class-G Harmonic Rejection PA

A wideband Internet of Things (IoT) transmitter (TX) employing open-loop binary frequency-shift keying (BFSK) modulator with a pseudo-randomized phase transition (PRPT) time and a single-supply Class-G harmonic rejection (HR) power amplifier (PA) is presented. The proposed open-loop phase switching modulator eliminates the data-rate limitation in a conventional phase-locked loop (PLL)-based closed-loop modulator, while the PRPT scheme increases the effective phase resolution with a better power efficiency than delta–sigma modulation (DSM)-based randomization. Thus, a low spur level below −40 dBc is achieved with only a 4-bit phase resolution. The Class-G HR PA, including a four-level supply voltage waveform generator, is proposed as a high-efficiency and low spurious PA architecture. The proposed HR PA presents the third- and fifth-harmonics cancellation over the 0.3-to-1-GHz band, while only a single supply is required for Class-G implementation of the HR PA. The proposed BFSK TX is implemented in a 55-nm CMOS process. Measured with a 0.3-to-1-GHz continuous-wave carrier, TX output power and PA drain efficiency are 2.7 ± 0.2 dB and 52% ± 3%, respectively, operating from a 0.9-V supply. The HRs of −31.4/−42.7 and −28.2/−42.4 dBc at the third/fifth harmonics are measured at the lowest (0.3 GHz) and the highest (1 GHz) carrier frequencies, respectively. With a data rate of 1 Mb/s, the measured FSK errors are 3.6% and 4.2% at both ends of the operating frequency.

Atmospheric absorption and scattering impact on optical satellite‐ground links

SummaryFree‐space radio‐frequency (RF) communication links for intersatellite or satellite‐to‐ground communications are getting increasingly constraint by the insufficient spectrum availability and limited data rate of RF technology. With the advent of large satellite mega‐constellation networks for global communications coverage, this limitation of classical RF communication becomes even more critical. Therefore, the establishment of point‐to‐point free‐space optical link technology (FSO) in space will become of paramount importance in future systems, where the application will be for data‐relays links, or for mega‐constellations inter‐satellite links, as well as for direct data downlinks, or from deep‐space probes to ground. Further advantages of optical FSO—besides spectrum availability—is its increased power efficiency, higher data rates, avoidance of interference, and inherent protection against interception. When, however, these optical communication links have to pass through Earth's atmosphere, attenuation and scattering effects do influence the signal transmission. In this publication, we investigate the effects of atmospheric attenuation, including the effects of molecular absorption as well as aerosol scattering and absorption, for typical wavelength regions used for FSO, dependent on the link geometries. Based on transmission‐simulation databases, we show useful spectral ranges and their specific attenuation strength. Free spectral transmission windows dependent on atmospheric quality and elevation angle are identified for reliable and efficient use of the optical transmission technology in space applications.

Real‐time image transmission through underwater wireless optical communication link for Internet of Underwater Things

SummaryThe Internet of Underwater Things (IoUTs) can be considered as a potential candidate to interconnect physical devices (things) such as submarines, ships, divers, buoys, and unmanned underwater vehicles (AUVs) to collect and exchange information with each other in the ocean environment. Traditionally, sound waves have been used to transfer information between IoUTs, but due to the lack of limited bandwidth and data rate, the underwater wireless optical communication (UWOC)‐based IoUTs can be considered as a viable solution. In this work, a real‐time RGB image is transferred between two IoUTs using an intensity modulation direct detection (IM/DD) on–off keying (OOK) modulation scheme. To estimate the performance of the reconstructed image, structure similarity index (SSIM) and peak signal‐to‐noise ratio (PSNR) have been evaluated. During transmission of an image through the water, the quality of the received image degrades due to the absorption, scattering, and underwater turbulence which further limits the transmission range. Thus, to enhance the quality of the received images, two filters, that is, median and Wiener filters, have been proposed. The median filter improves the SSIM and PSNR of the reconstructed image more appropriately as compared to the Wiener filter. The results show that the proposed median filter can enhance the communication range of the UWOC point‐to‐point link by 100 m.

Potential key challenges for terahertz communication systems

The vision of 6G communications is an improved performance of the data rate and latency limitations and permit ubiquitous connectivity. In addition, 6G communications will adopt a novel strategy. Terahertz (THz) waves will characterize 6G networks, due to 6G will integrate terrestrial wireless mobile communication, geostationary and medium and low orbit satellite communication and short distance direct communication technologies, as well as integrate communication, computing, and navigation. This study discusses the key challenges of THz waves, including path losses which is considered the main challenge; transceiver architectures and THz signal generators; environment of THz with network architecture and 3D communications; finally, Safety and health issues.

Experimental investigation of 16.6 Gbps SDM-WDM visible light communication based on a neural network receiver and tricolor mini-LEDs.

Visible light communication (VLC) based on a light-emitting diode (LED) suffers from a limited bandwidth of commercial LED, device nonlinearity, channel distortion, and transmitted power caused by a complex free-space channel, power amplifier, and illuminant devices resulting in a limited data rate. In this Letter, to provide an alternative high-speed solution, we first designed and fabricated three 175 µm tricolor mini-LEDs with various wavelengths. They are used to set up a spatial division multiplexing-wavelength division multiplexing VLC system over a 2 m link. Then we utilize a neural network receiver to replace the traditional channel estimation, equalization, and demodulation at the offline digital signal processing of the receiver. The experiment showed that the data rates of 2.65, 7, and 7 Gbps were achieved in three respective links using quadrature phase shift keying-optical orthogonal frequency division multiplexing. The three data rates have bit-error rates below the forward error correction limit, whose data rate sum of 16.6 Gbps is the highest mini/micro-LED-based VLC, to the best of our knowledge.

AODR: An Automatic On-Demand Retransmission Scheme for WIA-FA Networks

In Industrial Wireless Sensor Networks (IWSNs), monitoring data generated by field devices are supposed to be delivered to the gateway with high reliability and low latency. However, most of the existing industrial wireless standards are based on IEEE 802.15.4, offering a very limited data rate, which prevents their adoption in critical industrial applications. Based on IEEE 802.11, a recent international standard WIA-FA is proposed to address higher communication requirements in factory automation. In this paper, we study the timeslot allocation for retransmissions in the WIA-FA network. Specifically, we first design a novel superframe to support the Negative ACKnowledgment (NACK)-based retransmission mode in the WIA-FA network, and build a network model which considers the uplink and downlink packet losses simultaneously. Then, we analyze the three major drawbacks of the default NACK-based retransmission scheme in WIA-FA and propose an Automatic On-Demand Retransmission (AODR) scheme. Finally, we give a detailed reliability analysis of the proposed AODR scheme, and prove the relationship between the transmission reliability and critical factors (e.g., the channel condition and the length of the superframe) in the WIA-FA network. Simulation results show that the proposed AODR scheme outperforms existing works in terms of transmission reliability and timeliness for different channel conditions.

Backhaul-Aware Intelligent Positioning of UAVs and Association of Terrestrial Base Stations for Fronthaul Connectivity

The mushroom growth of cellular users requires novel advancements in the existing cellular infrastructure. One way to handle such a tremendous increase is to densely deploy terrestrial small-cell base stations (TSBSs) with careful management of smart backhaul/fronthaul networks. Nevertheless, terrestrial backhaul hubs significantly suffer from the dense fading environment and are difficult to install in a typical urban environment. Therefore, this paper considers the idea of replacing terrestrial backhaul network with an aerial network consisting of unmanned aerial vehicles (UAVs) to provide the fronthaul connectivity between the TSBSs and the ground core-network (GCN). To this end, we focus on the joint positioning of UAVs and the association of TSBSs such that the sum-rate of the overall system is maximized. In particular, the association problem of TSBSs with UAVs is formulated under communication-related constraints, i.e., bandwidth, number of connections to a UAV, power limit, interference threshold, UAV heights, and backhaul data rate. To meet this joint objective, we take advantage of the genetic algorithm (GA) due to the offline nature of our optimization problem. The performance of the proposed approach is evaluated using the unsupervised learning-based k-means clustering algorithm. We observe that the proposed approach is highly effective to satisfy the requirements of smart fronthaul networks.

Optical wireless communication performance enhancement using Hamming coding and an efficient adaptive equalizer with a deep-learning-based quality assessment.

Optical wireless communication (OWC) technology is one of several alternative technologies for addressing the radio frequency limitations for applications in both indoor and outdoor architectures. Indoor optical wireless systems suffer from noise and intersymbol interference (ISI). These degradations are produced by the wireless channel multipath effect, which causes data rate limitation and hence overall system performance degradation. On the other hand, outdoor OWC suffers from several physical impairments that affect transmission quality. Channel coding can play a vital role in the performance enhancement of OWC systems to ensure that data transmission is robust against channel impairments. In this paper, an efficient framework for OWC in developing African countries is introduced. It is suitable for OWC in both indoor and outdoor environments. The outdoor scenario will be suitable to wild areas in Africa. A detailed study of the system stages is presented to guarantee the suitable modulation, coding, equalization, and quality assessment scenarios for the OWC process, especially for tasks such as image and video communication. Hamming and low-density parity check coding techniques are utilized with an asymmetrically clipped DC-offset optical orthogonal frequency-division multiplexing (ADO-OFDM) scenario. The performance versus the complexity of both utilized techniques for channel coding is studied, and both coding techniques are compared at different coding rates. Another task studied in this paper is how to perform efficient adaptive channel estimation and hence equalization on the OWC systems to combat the effect of ISI. The proposed schemes for this task are based on the adaptive recursive least-squares (RLS) and the adaptive least mean squares (LMS) algorithms with activity detection guidance and tap decoupling techniques at the receiver side. These adaptive channel estimators are compared with the adaptive estimators based on the standard LMS and RLS algorithms. Moreover, this paper presents a new scenario for quality assessment of optical communication systems based on the regular transmission of images over the system and quality evaluation of these images at the receiver based on a trained convolutional neural network. The proposed OWC framework is very useful for developing countries in Africa due to its simplicity of implementation with high performance.

Practical output consensus of nonlinear heterogeneous multi-agent systems with limited data rate

This paper investigates the consensus problem for nonlinear heterogeneous multi-agent systems with limited communication data rate. Each agent is modeled by a higher-order strict-feedback continuous-time system with unknown nonlinearities and external disturbance, and only the first state variable being measurable. Extended state observers (ESOs) are used to estimate the unmeasurable agent states and the unknown nonlinear dynamics. An ESO-based distributed output feedback protocol with dynamic encoding and decoding is then presented. It is shown that, for a connected undirected network, the proposed protocol guarantees practical output consensus, in which the steady-state consensus error can be made arbitrarily small. The ESO-based protocol also shapes the transient consensus performance, as it is capable of recovering the consensus performance of a linear counterpart with fully measurable states. Furthermore, we prove that for higher-order uncertain nonlinear multi-agent systems, consensus can be achieved with merely one bit information exchange between each pair of adjacent agents at each time step. Finally, simulations on third-order pendulum systems are given, which verify the theoretical results.

Compact sub-GHz bandwidth single-mode time-energy entangled photon source for high-speed quantum networks

The potential data rate of a quantum network is limited by both the entangled photon source (EPS) and quantum memories. While an EPS whose bandwidth matches with broadband quantum memories (BBQMs) can take full advantage of the data rate limit. The EPS with GHz bandwidth is usually obtained by filtering a much broader EPS signal that is generated through spontaneous parametric down-conversion (SPDC), but this method has obvious drawbacks, e.g., large space requirements, high losses, and relatively low spectral brightness. Here we present a simple and compact method to generate a single-longitudinal-mode sub-GHz-bandwidth time-energy EPS using a type-II SPDC in a submillimeter-length Fabry-Pérot cavity. The proposed photon source offers superior figures of merit: the maximum coincidence to accidental coincidence ratio is approximately 1800, the detected pair flux ranges up to 42500 pairs per second, and the source has a high Klyshko efficiency of 25%. This source offers a very potential way to boost the performance of broadband quantum memories and high-speed quantum networks.

Remote state estimation problem: Towards the data-rate limit along the avenue of the second Lyapunov method

In the context of control and estimation under information constraints, restoration entropy measures the minimal required data rate above which the state of a system can be estimated so that the estimation quality does not degrade over time and, conversely, can be improved. The remote observer here is assumed to receive its data through a communication channel of finite bit-rate capacity. In this paper, we provide a new characterization of the restoration entropy which does not require to compute any temporal limit, i.e., an asymptotic quantity. Our new formula is based on the idea of finding a specific Riemannian metric on the state space which makes the metric-dependent upper estimate of the restoration entropy as tight as one wishes.

Distributed Observer-Based Consensus Over Directed Networks With Limited Communication Bandwidth Constraints

In this paper, we present a distributed observer-type consensus controller design for general linear multiagent systems over directed digital networks with limited communication data rates. Considering that each agent can only exchange binary symbolic sequence with its neighbors due to bandwidth constraints, we adopt the probabilistic quantization approach in the distributed consensus controller design. Compared to the existing works, the main contribution is that we use distributed observer-type controllers to inhibit the impact of quantization noises in agent states. First, we study the observer-type protocols with total quantized communications, where the relative-state information of each agent is quantized. The quantized consensus can be achieved, and the upper bounds of steady-state errors in the mean-square sense are also characterized, which are related to the scale of networks, the control parameters, the quantization levels, and the structures of agents. Further, we extend the controller design based on total quantization to the partial quantization case where only the neighbors’ information is quantized.

High‐rate uncoded space‐time labelling diversity with low‐complexity detection

SummaryUncoded space‐time labelling diversity (USTLD) is a recent scheme that improved the error performance compared to conventional multiple‐input, multiple‐output systems. Thus far, USTLD has suffered from limited achievable data rates, as the original model uses only two transmit antennas. This motivates for the work in this paper, where the USTLD model is extended to allow for any desired number of transmit antennas. An analytical bound for the average bit error probability of this high‐rate USTLD (HR‐USTLD) system is derived. This expression is verified using the results of Monte Carlo simulations, which show a tight fit in the high signal‐to‐noise ratio region. The increased data rates associated with larger transmit antenna arrays in HR‐USTLD systems come at the cost of increased detection complexity. Therefore, this paper studies the application of low‐complexity detection algorithms based on the popular QR decomposition technique and proposes a new algorithm specifically designed for HR‐USTLD systems. Analysis of this algorithm in terms of accuracy and computational complexity is also provided and benchmarked against maximum‐likelihood detection (MLD). It is shown that the proposed algorithm achieves near‐MLD accuracy, while reducing complexity by 79.75% and 92.53% for the respective 4 × 4 16QAM and 4 × 5 16PSK HR‐USTLD systems investigated.

Data-Rate Driven Transmission Strategies for Deep Learning-Based Communication Systems

Deep learning (DL) based autoencoder is a promising architecture to implement end-to-end communication systems. One fundamental problem of such systems is how to increase the transmission rate. Two new schemes are proposed to address the limited data rate issue: adaptive transmission scheme and generalized data representation (GDR) scheme. In the first scheme, an adaptive transmission is designed to select the transmission vectors for maximizing the data rate under different channel conditions. The block error rate (BLER) of the first scheme is 80% lower than that of the conventional one-hot vector scheme. This implies that higher data rate can be achieved by the adaptive transmission scheme. In the second scheme, the GDR replaces the conventional one-hot representation. The GDR scheme can achieve higher data rate than the conventional one-hot vector scheme with comparable BLER performance. For example, when the vector size is eight, the proposed GDR scheme can double the date rate of the one-hot vector scheme. Besides, the joint scheme of the two proposed schemes can create further benefits. The effect of signal-to-noise ratio (SNR) is analyzed for these DL-based communication systems. Numerical results show that training the autoencoder using data set with various SNR values can attain robust BLER performance under different channel conditions.

A New IDMA System Based on CSK Modulation for Multiuser Underwater Acoustic Communications

This work proposes a novel interleave-division multiple access (IDMA) system based on cyclic shift keying (CSK) modulation, named CSK-IDMA, for multiuser underwater acoustic (UWA) communications. The CSK modulation uses a circular cyclic shift of the spreading sequence to represent the information, which can be viewed as a special $M$ -ary spread spectrum modulation. Compared with conventional direct-sequence spread spectrum (DSSS) technique, CSK overcomes the spreading gain versus data rate limitations. The proposed scheme adopts the IDMA technique to reduce the cochannel interference. At the receiver, we employ passive time reversal (PTR) technique to compress the channels and improve the signal-to-interference-noise ratio (SINR) at first. In order to perfectly incorporate with the IDMA receive structure, we propose a soft CSK demodulation which can iteratively exchange extrinsic information with a soft channel decoder to form a turbo equalization. Simulation results show the proposed CSK-IDMA scheme can offer significantly improved performance. The data processing results from a lake experiment show that the proposed scheme can support 8 users and 10 users with zero error bits for 2.3 km transmission and 2.7 km transmission, respectively. The corresponding bit error rate (BER) for 16 users are $\text{8.4} \times \text{10}^{-4}$ and $\text{9.7} \times \text{10}^{-4}$ , respectively. The data rate is 62.5 bit/s per user within 4 kHz bandwidth and spreading sequences of 256 chips. To the best of our knowledge, this is the first work which can support more than 8 users for multiuser UWA communications with a high bandwidth efficiency.

Coding Techniques using IDMA OFDM MIMO for Underwater Wireless Acoustic Communication

Future Underwater communication demands high speed data transmission. Present Underwater communication can only provide a limited data rate, where the available bandwidth is limited. To increase the data rate, we simulate the MIMO-OFDM with IDMA technique. In MIMO method many transmitter and many receiver antennas are present. MIMO method offer a very high capacity which raises linearly with the numeral of antennas. Data rate increases with MIMO method, bandwidth is saved and fading is reduced with OFDM. In OFDM technique the complete sign orthogonally overlays in a frequency field that secures the bandwidth. IDMA system is constructed on interleaving procedure. In this paper different coding techniques Convolutional, RS code, LDPC code, Turbo code with IDMA OFDM MIMO technique are compared. IDMA OFDM MIMO with Turbo code, BER performance is improved up to 10-6.

Gb/s Underwater Wireless Optical Communications Using Series-Connected GaN Micro-LED Arrays

High speed wireless communications are highly desirable for many industrial and scientific underwater applications. Acoustic communications suffer from high latency and limited data rates, while Radio Frequency communications are severely limited by attenuation in seawater. Optical communications are a promising alternative, offering high transmission rates (up to Gb/s), while water has relatively low attenuation at visible wavelengths. Here we demonstrate the use of series-connected micro-light-emitting-diode (μLED) arrays consisting of 6 μLED pixels either 60 μm or 80 μm in diameter and operating at 450 nm. These devices increase the output power whilst maintaining relatively high modulation bandwidth. Using orthogonal frequency division multiplexing (OFDM) we demonstrate underwater wireless data transmission at rates of up to 4.92 Gb/s, 3.22 Gb/s and 3.4 Gb/s over 1.5 m, 3 m and 4.5 m, respectively, with corresponding bit error ratios (BERs) of 1.5 × 10−3, 1.1 × 10−3 and 3.1 × 10−3, through clear tap water, and Mb/s rates through >5 attenuation lengths (ALs) in turbid waters.

Data Rate Limit in Low and High SNR Regime for Nakagami-q Fading Wireless Channel

Adequate data rate is always desired in wireless communication channels. Previously, few fading models were used to model wireless communication channels and to perform analysis on them. In this paper, analyses of data rate limit of single-input single-output (SISO) wireless communication system over Nakagami-q fading channels are presented. The calculation of capacity has been carried out using small and large limit argument approximations. The analytical solution for channel capacity is presented using small and large limit argument approximations. Where small and large limit argument approx-imations correspond low and high signal-to-noise ratio (SNR) regime. Behavior of channel capacity with respect to SNR and fading parameter respectively has been investigated deeply. The comparison of the channel capacity behavior for both low SNR and high SNR regime and have also been done and analyzed. It has found that the channel capacity increased with increasing SNR in low SNR regime. The channel capacity also behave in the same manner in high SNR regime as well.

Data rate limits for the remote state estimation problem

In the context of control and estimation under information constraints, restoration entropy measures the minimal required data rate above which a system can be regularly observed. The observer here is assumed to receive its state information through a communication channel of a finite bit-rate capacity. In this paper, we provide a new characterization of restoration entropy which does not require to compute any temporal limit, i.e., an asymptotic quantity. Our new formula is based on the idea of finding an adapted Riemannian metric on the state space that allows to ‘see’ the decisive quantity that determines the restoration entropy - a certain type of Lyapunov exponent - in only one step of time.

A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE

The MIMO-OFDM system fully exploits the advantages of MIMO and OFDM, effectively resisting the channel multipath fading and inter-symbol interference while increasing the data transmission rate. Studies show that it is the principal technical mean for building underwater acoustic networks (UANs) of high performance. As the core, a signal detection algorithm determines the performance and complexity of the MIMO-OFDM system. However, low computational complexity and high performance cannot be achieved simultaneously, especially for UANs with a narrow bandwidth and limited data rate. This paper presents a novel signal detection algorithm based on generalized MMSE. First, we propose a model for the underwater MIMO-OFDM system. Second, we design a signal coding method based on STBC (space-time block coding). Third, we realize the detection algorithm namely GMMSE (generalized minimum mean square error). Finally, we perform a comparison of the algorithm with ZF (Zero Forcing), MMSE (minimum mean square error), and ML (Maximum Likelihood) in terms of the BER (bit error rate) and the CC (computational complexity). The simulation results show that the BER of GMMSE is the lowest one and the CC close to that of ZF, which achieves a tradeoff between the complexity and performance. This work provides essential theoretical and technical support for implementing UANs of high performance.