Showing papers on "Fading published in 2022"

Unveiling the Genesis and Effectiveness of Negative Fading in Nanostructured Iron Oxide Anode Materials for Lithium-Ion Batteries.

Abstract: Iron oxide anode materials for rechargeable lithium-ion batteries have garnered extensive attention because of their inexpensiveness, safety, and high theoretical capacity. Nanostructured iron oxide anodes often undergo negative fading, that is, unconventional capacity increase, which results in a capacity increasing upon cycling. However, the detailed mechanism of negative fading still remains unclear, and there is no consensus on the provenance. Herein, we comprehensively investigate the negative fading of iron oxide anodes with a highly ordered mesoporous structure by utilizing advanced synchrotron-based analysis. Electrochemical and structural analyses identified that the negative fading originates from an optimization of the electrolyte-derived surface layer, and the thus formed layer significantly contributes to the structural stability of the nanostructured electrode materials, as well as their cycle stability. This work provides an insight into understanding the origin of negative fading and its influence on nanostructured anode materials.

Intelligent Reflecting Surface-Aided URLLC in a Factory Automation Scenario

Abstract: Different from conventional wired line connections, industrial control through wireless transmission is widely regarded as a promising solution due to its reduced cost, increased long-term reliability, and enhanced reliability. However, mission-critical applications impose stringent quality of service (QoS) requirements that entail ultra-reliability low-latency communications (URLLC). The primary feature of URLLC is that the blocklength of channel codes is short, and the conventional Shannon’s Capacity is not applicable. In this paper, we consider the URLLC in a factory automation (FA) scenario. Due to densely deployed equipment in FA, wireless signal are easily blocked by the obstacles. To address this issue, we propose to deploy intelligent reflecting surface (IRS) to create an alternative transmission link, which can enhance the transmission reliability. In this paper, we focus on the performance analysis for IRS-aided URLLC-enabled communications in a FA scenario. Both the average data rate (ADR) and the average decoding error probability (ADEP) are derived under finite channel blocklength for seven cases: 1) Rayleigh fading channel; 2) With direct channel link; 3) Nakagami-m fading channel; 4) Imperfect phase alignment; 5) Multiple-IRS case; 6) Rician fading channel; 7) Correlated channels. Extensive numerical results are provided to verify the accuracy of our derived results.

Capacity fading mechanisms and state of health prediction of commercial lithium-ion battery in total lifespan

Abstract: • Aging mechanisms of LIB in total lifespan are revealed. • SOH prediction of total lifespan is conducted based on a prediction technique. • Capacity detection technique and use strategy of retired LIBs are recommended. In this study, aging mechanisms and state of health prediction of lithium-ion battery in total lifespan are investigated. Battery capacity fading can be divided into three stages: stable capacity fading, fast capacity fading, and repetition between capacity increase and decrease. Incremental capacity analysis and electrochemical impedance spectroscopy are used to study relevant aging mechanisms. In the first stage, aging mechanisms that affect lithium-ion batteries include loss of lithium and loss of active material at the negative and positive electrode. In the second stage, the aging mechanisms are loss of lithium and loss of active material at the negative electrode. In the third stage, the loss of lithium is recovered to increase capacity. Finally, back propagation neural network optimized by genetic algorithm is used to predict state of health of lithium-ion battery in total lifespan, including cycle life of new batteries, second-life use after being retired, and residual capacity of retired batteries.

FASURA: A Scheme for Quasi-Static Massive MIMO Unsourced Random Access Channels

Abstract: This article considers the massive MIMO unsourced random access problem on a quasi-static Rayleigh fading channel. Given a fixed message length and a prescribed number of channel uses, the objective is to construct a coding scheme that minimizes the energy-per-bit subject to a fixed probability of error. The proposed scheme differs from other state-of-the-art schemes in that it blends activity detection, single-user coding, pilot-aided and temporary decisions-aided iterative channel estimation and decoding, minimum-mean squared error (MMSE) estimation, and successive interference cancellation (SIC). We show that an appropriate combination of these ideas can substantially outperform state-of-the-art coding schemes when the number of active users is more than 100, making this the best performing scheme known for this regime.

Active Reconfigurable Intelligent Surface Aided Secure Transmission

Abstract: Reconfigurable Intelligent Surface (RIS) draws great attentions in academic and industry due to its passive and low power consumption nature, and has currently been used in physical layer security to enhance the secure transmission. However, due to the existence of “double fading” effect on the reflecting channel link between transmitter and user, RIS helps achieve limited secrecy performance gain compared with the case without RIS. In this correspondence, we propose a novel active RIS design to enhance the secure wireless transmission, where the reflecting elements in RIS not only adjust the phase shift but also amplify the amplitude of signals. To solve the non-convex secrecy rate optimization based on this design, an efficient alternating optimization algorithm is proposed to jointly optimize the beamformer at transmitter and reflecting coefficient matrix at RIS. Simulation results show that with the aid of active RIS design, the impact of “double fading” effect can be effectively relieved, resulting in a significantly higher secrecy performance gain compared with existing solutions with passive RIS and without RIS design.

Delay Compensation-Based State Estimation for Time-Varying Complex Networks With Incomplete Observations and Dynamical Bias

Abstract: In this article, a delay-compensation-based state estimation (DCBSE) method is given for a class of discrete time-varying complex networks (DTVCNs) subject to network-induced incomplete observations (NIIOs) and dynamical bias. The NIIOs include the communication delays and fading observations, where the fading observations are modeled by a set of mutually independent random variables. Moreover, the possible bias is taken into account, which is depicted by a dynamical equation. A predictive scheme is proposed to compensate for the influences induced by the communication delays, where the predictive-based estimation mechanism is adopted to replace the delayed estimation transmissions. This article focuses on the problems of estimation method design and performance discussions for addressed DTVCNs with NIIOs and dynamical bias. In particular, a new distributed state estimation approach is presented, where a locally minimized upper bound is obtained for the estimation error covariance matrix and a recursive way is designed to determine the estimator gain matrix. Furthermore, the performance evaluation criteria regarding the monotonicity are proposed from the analytic perspective. Finally, some experimental comparisons are proposed to show the validity and advantages of the new DCBSE approach.

A strong tracking adaptive fading‐extended Kalman filter for the state of charge estimation of lithium‐ion batteries

Abstract: Lithium‐ion batteries are widely used as rechargeable energy and power storage system in smart devices and electric vehicles because of their high specific energy, high power densities, etc. The state of charge (SOC) serves as a vital feature that is monitored by the battery management system to optimize the performance, safety, and lifespan of lithium‐ion batteries. In this paper, a strong tracking adaptive fading‐extended Kalman filter (STAF‐EKF) based on the second‐order resistor–capacitor equivalent circuit model (2RC‐ECM) is proposed for accurate SOC estimation of lithium‐ion batteries under different working conditions and ambient temperatures. The characteristic parameters of the established 2RC‐ECM for the lithium‐ion battery are identified offline using the least‐squares curve fitting method with an average R‐squared value of 0.99881. Experimental data from the hybrid pulse power characterization (HPPC) is used for the estimation and verification of the proposed STAF‐EKF method under the complex Beijing bus dynamic stress test (BBDST) and the dynamic stress test (DST) working conditions at varying ambient temperatures. The results show that the established 2RC‐ECM tracks the actual voltage of the battery with a maximum error of 28.44 mV under the BBDST working condition. For the SOC estimation, the results show that the proposed STAF‐EKF has a maximum mean absolute error (MAE) and root mean square error (RMSE) values of 1.7159% and 1.8507%, while the EKF has 6.7358% and 7.2564%, respectively, at an ambient temperature of −10°C under the BBDST working condition. The proposed STAF‐EKF delivers optimal performance improvement compared to the EKF under different working conditions and ambient temperatures, serving as a basis for an accurate and robust SOC estimation method with quick convergence for the real‐time applications of lithium‐ion batteries.

On Maximizing the Sum Secret Key Rate for Reconfigurable Intelligent Surface-Assisted Multiuser Systems

Abstract: Channel reciprocity-based key generation (CRKG) has recently emerged as a new technique to address the problem of key distribution in wireless networks. However, as this approach relies upon the characteristics of fading channels, the corresponding secret key rate may be low when the communication link is blocked. To enhance the applicability of CRKG in harsh propagation scenarios, this paper introduces a novel multiuser key generation scheme, which is referred to as RIS-assisted multiuser key generation (RMK) that leverages the reconfigurable intelligent surface (RIS) technology for appropriately shaping the environment and enhancing the sum secret key rate between an access point and multiple users. In the RMK scheme, an RIS-induced channel, rather than the direct channel, serves as the key source. We derive a general closed-form expression of the secret key rate and optimize the configuration of the RIS to maximize the sum secret key rate over independent and correlated fading channels in the presence of multiple users. In the presence of independent fading, we introduce a low-complexity algorithm based on the Karush-Kuhn-Tucker (KKT) condition. In the presence of correlated fading, the optimization problem is non-convex and challenging to solve. To tackle it, we propose a new optimization algorithm based on the semi-definite relaxation (SDR) and successive convex approximation (SCA) methods. Simulation results demonstrate that the proposed RMK scheme outperforms existing RIS-assisted algorithms and achieves a near-optimal sum secret key rate over independent and correlated fading channels.

Achievable Rate Upper-Bounds of Uplink Multiuser OTFS Transmissions

Abstract: In this letter, we study the achievable rates adopting two delay-Doppler (DD) domain multiples access (MA) schemes for uplink orthogonal time frequency space (OTFS) transmissions, namely delay division multiple access (DDMA) and Doppler division multiple access (DoDMA). To shed light on the system performance, we establish the achievable rate upper-bounds for both DDMA and DoDMA in comparisons to that of the conventional orthogonal frequency division multiple access (OFDMA). In particular, we show that both DDMA and DoDMA have more robust signal-to-interference-plus-noise ratio (SINR) performances against channel fluctuations compared to OFDMA and this robustness leads to higher achievable rates for both DDMA and DoDMA. To be more specific, we find that the achievable rate upper-bounds for OTFS depend only on the channel fading coefficients of different paths and the multi-user interference (MUI), while the delay and Doppler shifts also have significant impacts on that of the conventional OFDMA. Our simulation results are consistent with our derivations and demonstrate a noticeable improvement of the achievable rates for both DDMA and DoDMA over OFDMA.

Optimized Power Control Design for Over-the-Air Federated Edge Learning

Abstract: Over-the-air federated edge learning (Air-FEEL) has emerged as a communication-efficient solution to enable distributed machine learning over edge devices by using their data locally to preserve the privacy. By exploiting the waveform superposition property of wireless channels, Air-FEEL allows the “one-shot” over-the-air aggregation of gradient-updates to enhance the communication efficiency, but at the cost of a compromised learning performance due to the aggregation errors caused by channel fading and noise. This paper investigates the transmission power control to combat against such aggregation errors in Air-FEEL. Different from conventional power control designs (e.g., to minimize the individual mean squared error (MSE) of the over-the-air aggregation at each round), we consider a new power control design aiming at directly maximizing the convergence speed. Towards this end, we first analyze the convergence behavior of Air-FEEL (in terms of the optimality gap) subject to aggregation errors at different communication rounds. It is revealed that if the aggregation estimates are unbiased, then the training algorithm would converge exactly to the optimal point with mild conditions; while if they are biased, then the algorithm would converge with an error floor determined by the accumulated estimate bias over communication rounds. Next, building upon the convergence results, we optimize the power control to directly minimize the derived optimality gaps under the cases without and with unbiased aggregation constraints, subject to a set of average and maximum power constraints at individual edge devices. We transform both problems into convex forms, and obtain their structured optimal solutions, both appearing in a form of regularized channel inversion, by using the Lagrangian duality method. Finally, numerical results show that the proposed power control policies achieve significantly faster convergence for Air-FEEL, as compared with benchmark policies with fixed power transmission or conventional MSE minimization.

Performance Analysis of the Hybrid Satellite-Terrestrial Relay Network With Opportunistic Scheduling Over Generalized Fading Channels

Abstract: A hybrid satellite-terrestrial relay network (HSTRN) has been envisioned as a promising communication architecture for future wireless communications, which can prominently reduce the impact of shadow fading and expand service coverage. In this paper, we conduct theoretical performance analysis for a dual-hop communication system, consisting of multiple relays and multiple users in the HSTRN with the amplify-and-forward protocol. For the shadowing effect and the multipath effect, we introduce the shadowed-Rician distribution and Nakagami-$m$ fading to characterize the channel models for the satellite-relay and the relay-user links, respectively. Additionally, the opportunistic scheduling scheme is employed, where the optimal relay and the optimal user are selected from the alternative nodes with the maximum instantaneous signal-to-noise ratio. Thereafter, the analytical expressions including ergodic capacity and average symbol error rate (SER) are derived. More specifically, we also present the asymptotic behavior of the average SER at the high signal-to-noise ratio (SRN) regime. The theoretical analysis is validated by the numerical results. Moreover, the results also reveal that the performance of the system can be improved by increasing the number of relays and users under different channel parameters and various modulation schemes.

TransNet: Full Attention Network for CSI Feedback in FDD Massive MIMO System

Abstract: Channel state information (CSI) is a key aspect of massive multi-input multi-output (MIMO) system. It depicts important properties of transmission channels such as scattering, fading, the attenuation of power with distance, etc. The quality and cost of CSI feedback between user equipment (UE) and base station (BS) play vital roles in the quality of the whole communication system. In this letter, a new deep learning (DL) method based on Google’s famous Transformer architecture is presented for CSI feedback in frequency division duplex (FDD) massive MIMO system. Simulation results show that the presented inception network named TransNet outperforms other DL methods on the quality of CSI feedback.

Resilient Model-Free Adaptive Iterative Learning Control for Nonlinear Systems Under Periodic DoS Attacks via a Fading Channel

Abstract: This article studies the resilient control problem for a class of unknown nonlinear systems with fading measurements under malicious denial-of-service (DoS) attacks. The system output is assumed to be transmitted through a fading channel, where the fading phenomenon is described by a Rice fading model. The strategy of the attacker is to periodically interfere with the networked channels to reduce the success rate of data transmissions. First, a dynamic linearization method along the iteration domain is introduced to convert the nonlinear system into an equivalent data-related model. Then, a model-free adaptive iterative learning control (MFAILC) scheme is presented, which is independent of model information. The convergence of the MFAILC scheme is deduced theoretically and the influence of DoS attacks and stochastic fading phenomenon on system stability are also analyzed. Finally, the effectiveness of the design is verified by a numerical simulation and a trajectory tracking example of wheeled mobile robots (WMRs).

Secrecy Performance Analysis of Parallel FSO/mm-wave System Over Unified Fisher-Snedecor Channels

Abstract: This paper presents a secrecy performance analysis of a parallel free-space optical/millimeter-wave (mm-wave) communication system with a selection-combining receiver over a unified Fisher-Snedecor $\mathcal{F}$-distribution channel. The $\mathcal{F}$-distribution model, with the proper parameters, may be used to describe both the mm-wave and optical channels. The security performance is specifically evaluated by deriving closed-form expressions for the average secrecy capacity, secrecy outage probability, and strictly positive secrecy capacity. We examine the three following distinct security scenarios: 1) An FSO-link eavesdropping attack, 2) mm-wave-link eavesdropping attacks, and 3) eavesdropping attacks on FSO and mm-wave links at the same time. Furthermore, to better understand the influence of various system and channel parameters, asymptotic analysis is performed at high signal-to-noise ratio values. Our developed analytical expressions provide an efficient tool for examining the influence of various system and channel parameters on the secrecy performance, including the atmospheric turbulence severity, pointing errors of the FSO link, fading severity, the shadowing parameters, as well as the number of diversity branches of the mm-wave links. Monte-Carlo simulations are used to verify the correctness of the numerical findings.

Event-Triggered Model-Free Adaptive Iterative Learning Control for a Class of Nonlinear Systems Over Fading Channels

Abstract: This article investigates the problem of event-triggered model-free adaptive iterative learning control (MFAILC) for a class of nonlinear systems over fading channels. The fading phenomenon existing in output channels is modeled as an independent Gaussian distribution with mathematical expectation and variance. An event-triggered condition along both iteration domain and time domain is constructed in order to save the communication resources in the iteration. The considered nonlinear system is converted into an equivalent linearization model and then the event-triggered MFAILC independent of the system model is constructed with the faded outputs. Rigorous analysis and convergence proof are developed to verify the ultimately boundedness of the tracking error by using the Lyapunov function. Finally, the effectiveness of the presented algorithm is demonstrated with a numerical example and a velocity tracking control example of wheeled mobile robots (WMRs).

Asynchronous Frequency-Dependent Fault Detection for Nonlinear Markov Jump Systems Under Wireless Fading Channels

Abstract: In this article, the asynchronous fault detection (FD) strategy is investigated in frequency domain for nonlinear Markov jump systems under fading channels. In order to estimate the system dynamics and meet the fact that not all the running modes can be observed exactly, a set of asynchronous FD filters is proposed. By using statistical methods and the Lynapunov stability theory, the augmented system is shown to be stochastic stable with a prescribed l2 gain even under fading transmissions. Then, a novel lemma is developed to capture the finite frequency performance. Some solvable conditions with less conservatism are subsequently deduced by exploiting novel decoupling techniques and additional slack variables. Besides, the FD filter gains could be calculated with the aid of the derived conditions. Finally, the effectiveness of the proposed method is shown by an illustrative example.

Unsourced Random Access Over Fading Channels via Data Repetition, Permutation, and Scrambling

Abstract: We focus on an unsourced random access (URA) system for communication over fading channels where the payload of each packet is encoded for error-correction, repeated, permuted, and scrambled. Each packet is also equipped with a preamble that is used for channel estimation and detection of permutation and scrambling sequences utilized for payload encoding. We propose an algorithm to resolve multiple-access preamble transmission, based on the approximate message-passing (AMP), that is capable to support high numbers of active users and achieve low probabilities of miss-detection. We also develop a parallel interference cancellation technique for payload reception that iteratively refines the channel estimates and attempts to minimize the mean squared error (MSE) of the users’ data via selective error-correction decoding. Finally, we derive a detailed system performance analysis that closely matches the obtained numerical results. We demonstrate that the presented system can more than double the number of active users, supported by the state-of-the-art systems. Large gains in terms of the minimal required signal-to-noise ratios (SNR)s are also demonstrated for a wide range of active user numbers.

Secure Transmission in Cell-Free Massive MIMO With Low-Resolution DACs Over Rician Fading Channels

Abstract: This paper investigates the secure transmission in downlink cell-free massive multiple-input multiple-output (MIMO) systems in the presence of an active multi-antenna eavesdropper (Eve) over Rician fading channels, assuming that each access point (AP) possesses multiple antennas which are connected with low-resolution digital-to-analog converters (DACs). Closed-form expressions of the achievable secrecy rate relied on the additive quantization noise model are derived. Based on these analytical results, we quantify the impacts of key system parameters, such as the antenna array number, DAC resolution, Rician $\mathcal K$ -factor, and balance factor between data and artificial noise power on secrecy enhancement. Several interesting insights are attained by assuming that Eve can or cannot perfectly remove inter-mobile-terminal interference. Moreover, we also propose a power control algorithm that maximizes the achievable secrecy rate, which can be represented as a series of second-order-cone programs for which efficient solvers exist. All the theoretical analyses and the effectiveness of the proposed algorithm are corroborated by simulation experiments.

A Novel Differential Chaos Shift Keying Scheme With Transmit Diversity

Abstract: A novel differential chaos shift keying scheme with transmit diversity, referred to as TD-DCSK scheme, is proposed in this letter. The proposed TD-DCSK scheme can achieve full diversity and high data rate by advisably designing the space-time (ST) block of the transmitted signal. With the designed ST block, the transmitter with multiple transmit antennas in the TD-DCSK scheme requires only one radio frequency chain, which is particularly important for keeping low hardware complexity. We derive the theoretical expression of bit-error rate (BER) and diversity order of the TD-DCSK scheme over multipath Rayleigh fading channels, and analyze its hardware complexity. Simulation results illustrate the superiority of the proposed scheme and validate the accuracy of the theoretical derivation. The proposed TD-DCSK scheme stands out as a promising solution for low-power and low-cost short-range wireless communications.

Enhancing QoS Through Fluid Antenna Systems over Correlated Nakagami-m Fading Channels

Abstract: Fluid antenna systems (FAS) enable mechanically flexible antennas that offer adaptability and flexibility for modern communication devices. In this work, we present a conceptual model for a single-antenna N-port (SANP) FAS over spatially correlated Nakagami-m fading channels and compare it with the traditional diversity schemes in terms of outage probability. The proposed FAS model switches to the best antenna port and resembles the operation of a selection combining (SC) diversity. FAS improves the quality of service (QoS) of the network through antenna port selection. The advantage of FAS is the ability to fit hundreds of antenna ports into a half-wavelength antenna size at the cost of spatial channel correlation. Simulation results demonstrate the superior outage probability performance of FAS at several tens of antenna ports compared to the traditional diversity schemes such as maximum ratio combining, equal gain combining, and SC. Moreover, the novel probability and cumulative density functions for the land mobile correlated Nakagami-m random variates are evaluated in this paper.

Physical Layer Security of Intelligent Reflective Surface Aided NOMA Networks

Abstract: Intelligent reflective surface (IRS) technology is emerging as a promising performance enhancement technique for next-generation wireless networks. Hence, we investigate the physical layer security of the downlink in IRS-aided non-orthogonal multiple access networks in the presence of an eavesdropper, where an IRS is deployed for enhancing the quality by assisting the cell-edge user to communicate with the base station. To characterize the network's performance, the expected value of the new channel statistics is derived for the reflected links in the case of Nakagami- $m$ fading. Furthermore, the performance of the proposed network is evaluated both in terms of the secrecy outage probability (SOP) and the average secrecy capacity (ASC). The closed-form expressions of the SOP and the ASC are derived. We also study the impact of various network parameters on the overall performance of the network considered. To obtain further insights, the secrecy diversity orders and the high signal-to-noise-ratio (SNR) slopes are obtained. We finally show that: 1) the expectation of the channel gain in the reflected links is determined both by the number of IRS elements and by the Nakagami- $m$ fading parameters; 2) If the Nakagami- $m$ parameter is no less than 2, the SOP of both User 1 and User 2 becomes unity, when the number of IRS elements tends to infinity; 3) The secrecy diversity orders are affected both by the number of IRS elements and by the Nakagami- $m$ fading parameters, whereas the high-SNR slopes are not affected by these parameters. Our Monte-Carlo simulations perfectly demonstrate the analytical results.

End-to-End Learning for OFDM: From Neural Receivers to Pilotless Communication

Abstract: The benefits of end-to-end learning has been demonstrated over AWGN channels but has not yet been quantified over realistic wireless channel models. This work aims to fill this gap by exploring the gains of end-to-end learning over a frequency- and time-selective fading channel using OFDM. With imperfect channel knowledge at the receiver, the shaping gains observed on AWGN channels vanish. Nonetheless, we identify two other sources of performance improvements. The first comes from a neural network-based receiver operating over a large number of subcarriers and OFDM symbols which allows to reduce the number of orthogonal pilots without loss of BER. The second comes from entirely eliminating orthogonal pilots by jointly learning a neural receiver together with either superimposed pilots (SIPs), combined with conventional QAM, or an optimized constellation. The learned constellation works for a wide range of signal-to-noise ratios, Doppler and delay spreads, has zero mean and does hence not contain any form of SIP. Both schemes achieve the same BER as the pilot-based baseline with 7% higher throughput. Thus, we believe that a jointly learned transmitter and receiver are a very interesting component for beyond-5G communication systems which could remove the need and associated overhead for demodulation reference signals.

Outage Probability for OTFS Based Downlink LEO Satellite Communication

Abstract: As an important technique of enabling global access for 6G, low earth orbit satellite (LEO-Sat) communication is still facing the challenges of large path-loss, and severe Doppler effect. This paper studies the reliability performance of a downlink LEO-Sat communication system, where the orthogonal time frequency space (OTFS) scheme is employed to combat severe Doppler effect. Further, the unmanned aerial vehicle (UAV) based cooperative transmission is developed, in order to compensate for the large margin of path-loss caused by the long transmission distance. In particular, the closed-form expression for the outage probability of the OTFS based LEO-Sat transmission is derived, where the novel moment matching approach is used to closely approximate the PDF of a sum of shadowing Rician (SR) variables. Further, the condition of using UAV cooperation is obtained so that the positive reliability gain is guaranteed. Finally, both the theoretical analysis and simulation results show that, the OTFS scheme can significantly outperform the traditional OFDM scheme, while demanding to carefully address the trade-off between reliability improvement and implementation complexity determined by modulation size.

Robust Recursive Filtering for Stochastic Systems With Time-Correlated Fading Channels

Abstract: This article is concerned with the robust recursive filtering (RF) problem for a class of stochastic uncertain systems subject to time-correlated fading channels. The measurement received by the sensor is transmitted to the remote filter through the time-correlated fading channel where the channel coefficient evolves according to a certain dynamics and hence exhibits a time-correlated nature. The parameter uncertainties of the system are described by norm-bounded unknown matrices. By introducing a class of auxiliary variables, an augmented system is constructed to reflect the dynamics of the fading coefficient and state simultaneously. Then, a recursive filter is designed which is capable of online computation. Furthermore, an upper bound is guaranteed for the filtering error covariance (FEC) for the possible parameter uncertainties as well as the time-correlated fading channels. With the help of the completing-the-squares technique, filter gains are parameterized by minimizing the obtained upper bound. Finally, two examples are employed to verify the effectiveness of the proposed robust RF method.

Joint Energy and Correlation Detection Assisted Non-Coherent OFDM-DCSK System for Underwater Acoustic Communications

Abstract: A joint energy and correlation detection aided orthogonal frequency division multiplexing differential chaos shift keying (JECD-OFDM-DCSK) system is presented in this paper, where the reference and information-bearing signals of JECD-OFDM-DCSK are superimposed in the same time slot so that the phase offset between the reference and information-bearing signals is addressed. In JECD-OFDM-DCSK, only some subcarriers are activated and additional information bits are transmitted by the indices of these activated subcarriers, thereby improving the data rate while reducing the energy consumption. The energy efficiency, peak to average power ratio (PAPR) performance and system complexity of JECD-OFDM-DCSK are analyzed and then compared to other systems. The comparison results show JECD-OFDM-DCSK can obtain higher energy efficiency and better PAPR performance compared to its competitors at the cost of higher system complexity. Furthermore, the bit error rate (BER) expressions of JECD-OFDM-DCSK are derived in additive white Gaussian noise (AWGN) and multipath fading channels. Simulation results show that the BER performance of JECD-OFDM-DCSK outperforms that of other OFDM-based DCSK systems. Finally, JECD-OFDM-DCSK performs much better than other systems over the underwater acoustic (UWA) channel, which validates the robustness of JECD-OFDM-DCSK.

Optimizing Memory in Reservoir Computers

Abstract: A reservoir computer is a way of using a high dimensional dynamical system for computation. One way to construct a reservoir computer is by connecting a set of nonlinear nodes into a network. Because the network creates feedback between nodes, the reservoir computer has memory. If the reservoir computer is to respond to an input signal in a consistent way (a necessary condition for computation), the memory must be fading; that is, the influence of the initial conditions fades over time. How long this memory lasts is important for determining how well the reservoir computer can solve a particular problem. In this paper, I describe ways to vary the length of the fading memory in reservoir computers. Tuning the memory can be important to achieve optimal results in some problems; too much or too little memory degrades the accuracy of the computation.

Design and Implementation of Optimum LSD Coded Signal Processing Algorithm in the Multiple-Antenna System for the 5G Wireless Technology

Abstract: The 5G system requires an optimum coding technique to achieve the high diversity gain, low bit error rate (BER), and low detection complexity. Various coding techniques were developed in recent times for improving the diversity performance of the MIMO systems. Space-time-coding (STC) is used to fulfill the requirement of handling large data flow in the 5G wireless communications. It is highly required to optimize the orthogonal nature of STC. The paper proposed a novel design of the optimum linearly scalable dispersion code (O-LSDC). In this paper, an optimum coefficient-based O-LSDC is designed based on the elementary matrix operations, unitary matrix normalization technique, and coefficient mapping strategy. Mapped coefficients are linearly solved for optimum value estimation. To find the optimum solution of the LSDC codes, five cases of LSDC are defined based on the scaling coefficients and then performance is evaluated against the BER vs. SNR. Evaluating the simulation results in terms of error probabilities for the five different orthonormal LSDC, this work simulates the system for multiple antennas using the Rayleigh fading MIMO system model. Also, evaluating the impact of the proposed LSDC over the BER performance for the varied number of Monte Carlo iterations, then the performance graph is plotted for multiple-antennas system. The proposed O-LSDC under Rayleigh fading channel using the M-PSK modulation enhances the performance of the 5G and beyond communication system in terms of BER and SNR.