Achievable Data Research Articles

Multiuser Scheduling Algorithm for 5G IoT Systems Based on Reinforcement Learning

MU-MIMO technology is adopted in 5 G to support the increasing number of user terminals accessing the 5 G IoT systems. The algorithms adopted in the existing literatures for user scheduling in MIMO system are greedy algorithm essentially, which needs to repeatedly calculate the achievable data rate (or its low complexity characterization) of each user during the user selection. Due to the large number of IoT terminals, the existing methods will generate huge computational load. In this paper, we propose a multiuser scheduling algorithm for 5 G IoT systems based on reinforcement learning. The user terminal's action-value, which denotes the expectation of user terminal's achievable data rate, is obtained through Q-learning. We define the Q-value as the upper bound of the confidence interval of the user terminal's action-value and the proposed algorithm selects users on the basis of the Q-value. The proposed algorithm does not need to try different user combinations to maximize the throughput, and it is unnecessary to repeatedly calculate user's achievable data rate, so that the computational load is reduced. Simulation and numerical results show that the computational complexity of the proposed algorithm is lower than that of existing algorithms. At the same time, the system throughput achieved by this algorithm is not lower than that of greedy algorithms.

STAR‐RIS‐enabled simultaneous indoor and outdoor 3D localisation: Theoretical analysis and algorithmic design

AbstractRecent research and development interests deal with metasurfaces for wireless systems beyond their consideration as intelligent tunable reflectors. Among the latest proposals is the simultaneously transmitting (a.k.a. refracting) and reflecting reconfigurable intelligent surface (STAR‐RIS) which intends to enable bidirectional indoor‐to‐outdoor, and vice versa communications thanks to its additional refraction capability. This double functionality provides increased flexibility in concurrently satisfying the quality‐of‐service requirements of users located at both sides of the metasurfaces, for example, the achievable data rate and localisation accuracy. The authors focus on STAR‐RIS‐empowered simultaneous indoor and outdoor three‐dimensional (3D) localisation, and study the fundamental performance limits via Fisher information analyses and Cramér Rao lower bounds (CRLBs). The authors also devise an efficient localisation algorithm based on an off‐grid compressive sensing (CS) technique relying on atomic norm minimisation (ANM). The impact of the training overhead, the power splitting at the STAR‐RIS, the power allocation between the users, the STAR‐RIS size, the imperfections of the STAR‐RIS‐to‐BS channel, as well as the role of the multi‐path components on the positioning performance are assessed via extensive computer simulations. It is theoretically demonstrated that high‐accuracy, up to centimetre level, 3D localisation can be simultaneously achieved for indoor and outdoor users, which is also accomplished via the proposed ANM‐based estimation algorithm.

Interband cascade technology for energy-efficient mid-infrared free-space communication

Space-to-ground high-speed transmission is of utmost importance for the development of a worldwide broadband network. Mid-infrared wavelengths offer numerous advantages for building such a system, spanning from low atmospheric attenuation to eye-safe operation and resistance to inclement weather conditions. We demonstrate a full interband cascade system for high-speed transmission around a wavelength of 4.18 µm. The low-power consumption of both the laser and the detector in combination with a large modulation bandwidth and sufficient output power makes this technology ideal for a free-space optical communication application. Our proof-of-concept experiment employs a radio-frequency optimized Fabry–Perot interband cascade laser and an interband cascade infrared photodetector based on a type-II InAs/GaSb superlattice. The bandwidth of the system is evaluated to be around 1.5 GHz. It allows us to achieve data rates of 12 Gbit/s with an on–off keying scheme and 14 Gbit/s with a 4-level pulse amplitude modulation scheme. The quality of the transmission is enhanced by conventional pre- and post-processing in order to be compatible with standard error-code correction.

Natural Intelligence as the Brain of Intelligent Systems

This article discusses the concept and applications of cognitive dynamic systems (CDS), which are a type of intelligent system inspired by the brain. There are two branches of CDS, one for linear and Gaussian environments (LGEs), such as cognitive radio and cognitive radar, and another one for non-Gaussian and nonlinear environments (NGNLEs), such as cyber processing in smart systems. Both branches use the same principle, called the perception action cycle (PAC), to make decisions. The focus of this review is on the applications of CDS, including cognitive radios, cognitive radar, cognitive control, cyber security, self-driving cars, and smart grids for LGEs. For NGNLEs, the article reviews the use of CDS in smart e-healthcare applications and software-defined optical communication systems (SDOCS), such as smart fiber optic links. The results of implementing CDS in these systems are very promising, with improved accuracy, performance, and lower computational costs. For example, CDS implementation in cognitive radars achieved a range estimation error that is as good as 0.47 (m) and a velocity estimation error of 3.30 (m/s), outperforming traditional active radars. Similarly, CDS implementation in smart fiber optic links improved the quality factor by 7 dB and the maximum achievable data rate by 43% compared to those of other mitigation techniques.

Stable yellow light emission from lead-free copper halides single crystals for visible light communication

Yellow light-emitting diodes (LEDs) as soft light have attracted abundant attention in lithography room, museum and art gallery. However, the development of efficient yellow LEDs lags behind green and blue LEDs, and the available perovskites yellow LEDs suffer from the instability. Herein, a pressure-assisted cooling method is proposed to grow lead-free CsCu 2 I 3 single crystals, which possess uniform surface morphology and enhanced photoluminescence quantum yield (PLQY) stability, with only 10% PLQY losses after being stored in air after 5000 ​h. Then, the single crystals used for yellow LEDs without encapsulation exhibit a decent Correlated Color Temperature (CCT) of 4290 ​K, a Commission Internationale de l'Eclairage (CIE) coordinate of (0.38, 0.41), and an excellent 570-h operating stability under heating temperature of 100 ​°C. Finally, the yellow LEDs facilitate the application in wireless visible light communication (VLC), which show a −3 dB bandwidth of 21.5 ​MHz and a high achievable data rate of 219.2 Mbps by using orthogonal frequency division multiplexing (OFDM) modulation with adaptive bit loading. The present work not only promotes the development of lead-free single crystals, but also inspires the potential of CsCu 2 I 3 in the field of yellow illumination and wireless VLC. The facile pressure-assisted cooling method is proposed to prepare lead-free CsCu2I3 single crystals, which promotes potential applications in both lighting for special occasions and wireless visible light communication.

Performance of Multipulse Pulse-Position Modulation in NLOS Ultraviolet Communications

The performance of multipulse pulse-position modulation (MPPM) in non-line-of-sight (NLOS) ultraviolet communications (UVC) with output signals of detectors following Poisson distribution and Poisson-triggered Gaussian (PTG) distribution has been investigated. Specifically, the probabilities of a given number of incorrectly identified pulsed or empty slots in an MPPM symbol have been derived with output signals Poisson and PTG distributed. Based on those probabilities, the expressions of symbol-error rate and achievable data rate of MPPM in the NLOS UVC systems have been further obtained. Finally, Monte-Carlo simulations are presented to verify the theoretical results.

A Power-Domain MST Scheme With BPPM in NLOS Ultraviolet Communications

Due to the high path loss of non-line-of-sight (NLOS) ultraviolet communications (UVC) channel, pulse modulation schemes, such as on-off keying (OOK) and M-ary pulse-position modulation (PPM), and photon-counting receivers are commonly adopted. Although M-ary PPM can be demodulated and decoded without the channel state information, its spectral efficiency is lower than OOK's. To improve the spectral efficiency of M-ary PPM in NLOS UVC, a power-domain multilayer-superposed transmission (MST) scheme with binary PPM (BPPM) is proposed in this work. Based on this scheme, the signal in each layer can be directly decoded without successive interference cancellation, which is necessary for other MST schemes in the power domain. Hence, a low complexity receiver in the NLOS UVC system can be realized. Additionally, the bit-error rate (BER) and achievable data rate (ADR) expressions of the proposed MST scheme are derived. Monte-Carlo simulations are performed to verify the analytical BER expression. The NLOS UVC system performance employing the proposed MST scheme is further demonstrated and compared with pure BPPM. The results indicate that with the optimal power allocation factor for each layer, the overall ADR of the NLOS UVC system with the proposed power-domain MST scheme can surpass that with pure BPPM.

Achievable Rate of Near-Field Communications Based on Physically Consistent Models

This paper introduces a novel information-theoretic approach for studying the effects of mutual coupling (MC), between the transmit and receive antennas, on the overall performance of single-input-single-output (SISO) near-field communications (NFC). By incorporating the finite antenna size constraint using Chu’s theory and under the assumption of canonical-minimum scattering (CMS), we derive the MC between two radiating volumes of fixed sizes. Expressions for the self and mutual impedances are obtained by the use of the reciprocity theorem. Based on a circuit-theoretic two-port model for SISO radio communication systems, we first establish its input-output relationship where the noise depends on the self/mutual impedances of the antennas, unlike the conventional assumption of independent additive white Gaussian noise. We then characterise the achievable data rate for a given pair of transmit and receive antenna sizes, thereby providing an upper bound on the system performance under physical size constraints. Through the lens of these findings, we shed new light on the influence of MC on the information-theoretic limits of near-field communications using compact antennas.

High-Speed Imaging Receiver Design for 6G Optical Wireless Communications: A Rate-FOV Trade-Off

The design of a compact high-speed and wide field of view (FOV) receiver is challenging due to the presence of two well-known trade-offs. The first one is the area-bandwidth trade-off of photodetectors (PDs) and the second one is the gain-FOV trade-off due to the use of optics. The combined effects of these two trade-offs imply that the achievable data rate of an imaging optical receiver is limited by its FOV, i.e., a rate-FOV trade-off. In this paper, we propose an imaging receiver design in the form of an array of (PD) arrays. To control the area-bandwidth trade-off, small PDs are used in an array of arrays structure instead of a single large PD. Moreover, to achieve a reasonable receiver FOV, we use an array of focusing lenses that focus the light individually on each inner PD array. The proposed array of arrays structure provides an effective method to control both gain-FOV trade-off (via an array of lenses) and area-bandwidth trade-off (via arrays of small PDs). We first derive a tractable analytical model for the signal-to-noise ratio (SNR) of an array of PDs that is equipped with a focusing lens assuming maximum ratio combining (MRC). Then, we extend the model to the proposed array of arrays structure and the accuracy of the analytical model is verified based on several Optic Studio-based simulations. Next, we formulate an optimization problem to maximize the achievable data rate of the imaging receiver subject to a minimum required FOV. The optimization problem is solved for two commonly used modulation techniques, namely, on-off keying (OOK) and direct current (DC) biased optical orthogonal frequency division multiplexing (DCO-OFDM) with variable rate quadrature amplitude modulation (QAM). Our results show the limits of high speed wide-FOV imaging receivers that can support mobility. For example, it is demonstrated that a data rate of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 24$ </tex-math></inline-formula> Gbps with a FOV of 15° is achievable using OOK with a total receiver size of 2 cm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\!\times \!\,\,2$ </tex-math></inline-formula> cm.

Low-complexity selective mapping technique for PAPR reduction in downlink power domain OFDM-NOMA

To support ultra-massive connectivity, non-orthogonal multiple access (NOMA) techniques are expected to be used in 6G instead of conventional orthogonal multiple access (OMA) techniques. Furthermore, given that orthogonal frequency division multiplexing (OFDM) was used by 4G and 5G, NOMA is expected to be combined with OFDM to mitigate frequency selectivity in multipath channels. However, after passing through nonlinear high power amplifiers (HPAs), OFDM-NOMA has reportedly suffered from nonlinear distortion due to the high peak-to-average power ratio (PAPR) problem, thus reducing users’ achievable data rates, sum rate capacity, and users’ bit error rate after going through nonlinear HPAs. Many PAPR reduction techniques have been introduced in the literature; however, high PAPR reduction gain comes at the expense of computational complexity. In this paper, a novel selective mapping (SLM) scheme for PAPR reduction in OFDM-NOMA systems is proposed. By utilizing the structure of the OFDM-NOMA transmitter, the proposed SLM scheme achieves the same performance as that of the conventional SLM scheme while requiring less computational complexity.

Energy Harvesting in the UNB-PLC Spectrum: Hidden Opportunities for IoT Devices

This article focuses on the hidden benefits of harvesting the wasted energy from undesirable components of electric signals in electric power systems for powering the transceivers of Internet of Things (IoT) devices. These components, mainly harmonics and interharmonics, occupy the ultranarrowband power line communication spectrum (i.e., frequencies below 3 kHz). In this context, we introduce a mathematical formulation that allows us to quantify the number of transceivers of IoT devices that this kind of wasted energy can power. Based on a measurement campaign in a building facility, we show that the wasted energy can be modeled as a cyclostationary random process on weekdays and a stationary one on weekends, mimicking the energy consumption profile in a building facility. Numerical results also highlight achievable data rates obtained in the building facility if the wasted energy is reused. This analysis shows that this kind of harvested energy from wasted energy is suitable for powering numerous transceivers of IoT devices in practical scenarios.

A deep neural networks based demodulator for PD-SCMA-VLC

Power domain sparse code multiple access (PD-SCMA) scheme-based visible light communications (VLC) can support higher spectrum efficiency and increased number of users in wireless access networks. In PD-SCMA-VLC, successive interference cancellation (SIC) and message passing algorithm (MPA)-based receivers are used to recover the transmitted signals in the power and code domains, respectively, which are complex requiring higher signal to noise ratio levels to deliver the quality of services. We propose a deep neural networks (DNN) based scheme to recover the PD-SCMA signal effected by the mixed noise, multipath distortions, and the nonlinearity due to the light emitting diode, channel and photodiode. We show by experiment that, the proposed DNN significantly outperforms the conventional SIC-MPA in terms of the achievable data rate and bit error rate performance. For DNN-based PD-SCMA-VLC, the achievable data rates are more than 100 and 120 Mbps for the user groups 2 and 1, respectively.

Digitally encoded RF to optical data transfer using excited Rb without the use of a local oscillator

We present a passive RF to optical data transfer without a local oscillator using an atomic “Rydberg” receiver. We demonstrate the ability to detect a 5G frequency carrier wave (3.5 GHz) and decode digital data from the carrier wave without the use of a local oscillator to detect the modulation of the RF signal. The encoding and decoding of the data are achieved using an intermediate frequency (IF). The rubidium vapor detects the changes in the carrier wave's amplitude, which comes from the mixing of the IF onto the carrier. The rubidium vapor then upconverts the IF into the optical domain for detection. Using this technique for data encoding and extraction, we achieve data rates up to 238 kbps with a variety of encoding schemes.

Load Balancing Multi-Player MAB Approaches for RIS-Aided mmWave User Association

In this paper, multiple reconfigurable intelligent surface (RIS) boards are deployed to enhance millimeter wave (mmWave) communication in a harsh blockage environment, where mmWave line-of-sight (LoS) link is completely blocked. Herein, RIS-user association should be considered to maximize the users’ achievable data rate while assuring load balance among the installed RIS panels. However, maximum received power (MRP) based RIS-user association will overload some of the RIS boards while keeping others unloaded, which causes RIS load to unbalance and decreases the users’ achievable data rate. Instead, in this paper, an online learning methodology using centralized multi-player multi-armed bandit (MP-MAB) with arms’ load balancing is proposed. In this formulation, mmWave users, RIS boards, and achievable users’ rates act as the bandit game players, arms, and rewards. During the MAB game, the users learn how to avoid associating with the heavily loaded RIS boards, maximizing their achievable data rates, and balancing the RIS loads. Three centralized MP-MAB algorithms with arms’ load balancing are proposed from the family of upper confidence bound (UCB) MAB algorithms. These algorithms are UCB1, Kullback-Leibler divergence UCB (KLUCB), and Minimax optimal stochastic strategy (MOSS) with arms’ load balancing, i.e., UCB1-LB, KLUCB-LB, and MOSS-LB. Numerical analysis ensures the superior performance of the proposed algorithms over MRP-based RIS-user association and other benchmarks.

Resource Allocation for Uplink Cell-Free Massive MIMO Enabled URLLC in a Smart Factory

Smart factories need to support the simultaneous communication of multiple industrial Internet-of-Things (IIoT) devices with ultra-reliability and low-latency communication (URLLC). Meanwhile, short packet transmission for IIoT applications incurs performance loss compared to traditional long packet transmission for human-to-human communications. On the other hand, cell-free massive multiple-input and multiple-output (CF mMIMO) technology can provide uniform services for all devices by deploying distributed access points (APs). In this paper, we adopt CF mMIMO to support URLLC in a smart factory. Specifically, we first derive the lower bound (LB) on achievable uplink data rate under the finite blocklength (FBL) with imperfect channel state information (CSI) for both maximum-ratio combining (MRC) and full-pilot zero-forcing (FZF) decoders. The derived LB rates based on the MRC case have the same trends as the ergodic rate, while LB rates using the FZF decoder tightly match the ergodic rates, which means that resource allocation can be performed based on the LB data rate rather the exact ergodic data rate under FBL. The log-function method and successive convex approximation (SCA) are then used to approximately transform the non-convex weighted sum rate problem into a series of geometric program (GP) problems, and an iterative algorithm is proposed to jointly optimize the pilot and payload power allocation. Simulation results demonstrate that CF mMIMO significantly improves the average weighted sum rate (AWSR) compared to centralized mMIMO. An interesting observation is that increasing the number of devices improves the AWSR for CF mMIMO whilst the AWSR remains relatively constant for centralized mMIMO.

Performance Analysis for RIS-Aided Secure Massive MIMO Systems With Statistical CSI

This letter studies a reconfigurable intelligent surface (RIS)-aided secure massive multiple-input multiple-output (MIMO) communication system. We derive the approximate expression of the sum achievable security data rate (ASDR) with statistical channel state information (CSI). To further improve the system performance, a genetic algorithm (GA) is proposed to optimize the RIS’s phase shifts, where both the continuous and discrete phase shifts are considered. Finally, simulation results confirm the correctness of our derived expressions, and demonstrate the effectiveness of using RIS in improving the security performance.

Resource Allocation in Multi-Cluster Cognitive Radio Networks With Energy Harvesting for Hybrid Multi-Channel Access

Cognitive radio and energy harvesting techniques have been able to provide insight for solutions to the inefficiency in spectrum utilization and the effects of the limited storage capacity of energy batteries. Nevertheless, the requirement for interference constraint for primary user (PU) protection, the quality of service (QoS) requirements of the SUs, and the low power density of the ambient electromagnetic waves have restricted the performance of the radio frequency powered cognitive radio networks (RF-CRNs) in terms of the achievable data rate for specific energy budget or sufficient energy budget for target data rate. We are therefore motivated to investigate a radio frequency powered cognitive radio (RF-CR) with the capacity for improved achievable throughput and energy harvesting. Our model consists of multiple PUs and SUs coexisting in a practical overlapping clustered network. In each time frame for the adopted time division multiple access (TDMA) technique, SUs can exploit the multi-user benefit to harvest energy from both the PU and SUs transmissions for improved active probability. Therefore, taken into consideration the heterogeneity of each SUs in terms of their signal-to-noise (SNR), the energy harvesting rates and the inter- and intra-cluster interference, the problem is formulated into a fractional nonlinear optimization to determine the sensing duration, and power allocations that maximize the average energy efficiency of the RF-CRN subject, to constraints on energy causality, and PU protection. The performance of the proposed hybrid multi-channel access scheme is studied in terms of the trade-off between the total achievable throughput by the secondary users and the interference generated among others. Simulation results show that a trade-off exists between achieving optimal spectral efficiency and energy efficiency and, the optimal transmit power therefore depends on the primary design objective. Results equally show that the proposed hybrid multi-channel access scheme outperforms the existing scheme in literature.

UQRCom

While communication in the air has been a norm with the pervasiveness of WiFi and LTE infrastructure, underwater communication still faces a lot of challenges. Even nowadays, the main communication method for divers in underwater environment is hand gesture. There are multiple issues associated with gesture-based communication including limited amount of information and ambiguity. On the other hand, traditional RF-based wireless communication technologies which have achieved great success in the air can hardly work in underwater environment due to the extremely severe attenuation. In this paper, we propose UQRCom, an underwater wireless communication system designed for divers. We design a UQR code which stems from QR code and address the unique challenges in underwater environment such as color cast, contrast reduction and light interfere. With both real-world experiments and simulation, we show that the proposed system can achieve robust real-time communication in underwater environment. For UQR codes with a size of 19.8 cm x 19.8 cm, the communication distance can be 11.2 m and the achieved data rate (6.9 kbps ~ 13.6 kbps) is high enough for voice communication between divers.

Distribution of Multi MmWave UAV Mounted RIS Using Budget Constraint Multi-Player MAB

Millimeter wave (mmWave), reconfigurable intelligent surface (RIS), and unmanned aerial vehicles (UAVs) are considered vital technologies of future six-generation (6G) communication networks. In this paper, various UAV mounted RIS are distributed to support mmWave coverage over several hotspots where numerous users exist in harsh blockage environment. UAVs should be spread among the hotspots to maximize their average achievable data rates while minimizing their hovering and flying energy consumptions. To efficiently address this non-polynomial time (NP) problem, it will be formulated as a centralized budget constraint multi-player multi-armed bandit (BCMP-MAB) game. In this formulation, UAVs will act as the players, the hotspots as the arms, and the achievable sum rates of the hotspots as the profit of the MAB game. This formulated MAB problem is different from the traditional one due to the added constraints of the limited budget of UAVs batteries as well as collision avoidance among UAVs, i.e., a hotspot should be covered by only one UAV at a time. Numerical analysis of different scenarios confirm the superior performance of the proposed BCMP-MAB algorithm over other benchmark schemes in terms of average sum rate and energy efficiency with comparable computational complexity and convergence rate.

Optimization for IRS-Assisted MIMO-OFDM SWIPT System With Nonlinear EH Model

Simultaneous wireless information and power transfer (SWIPT) has emerged as an appealing solution to prolonging the lifetime of low-power Internet of Things (IoT) networks. Meanwhile, an intelligent reflecting surface (IRS) can reconstruct a favorable wireless propagation environment for IoT terminals to achieve high spectrum and energy efficiencies. To take full advantage of these two technologies, this article studies the optimization of an IRS-assisted multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) SWIPT system with nonlinear energy harvesting (EH) model. In particular, we aim to maximize the achievable data rate by jointly designing the transmit precoding matrices, the IRS matrix, as well as the power splitting (PS) ratio subject to the transmit power and harvested power constraints. Since the formulated problem is highly nonconvex, we develop an alternating optimization (AO)-based algorithm to find a high-quality suboptimal solution. Moreover, we further design a heuristic algorithm based on a two-stage optimization strategy to reduce the computational complexity. Simulation results verify that the proposed AO-based algorithm can significantly improve the achievable data rate compared to conventional benchmarks, and the proposed heuristic low-complexity algorithm can achieve comparable performance to the AO-based algorithm.