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Wireless power and bidirectional wireless data transfer system using a conventional 2-coil inductive link is presented for Internet-of-Things (IoT) and mobile applications without any additional coil or antenna. The proposed system utilizes the dual-band frequency shift-keying (FSK) and the load shift-keying (LSK) for the downlink and uplink telemetries, respectively, while about 140 mW power is delivered to the Rx in the 2-coil inductive link. The data rates for downlink and uplink telemetries are 800 kbps and 14 kbps with bit error rate (BERs) of 3.1210^(-5) and less than 10^(-6) at 10 mm distance, respectively.

Non-orthogonal multiple access (NOMA) based multiple-input multiple-output (MIMO), which has the potential to provide both massive connectivity and high spectrum efficiency, is considered as one of the efficient techniques for sixth generation (6G) wireless systems. In massive Internet of Things (IoT) networks, user-set selection is crucial for enhancing the overall performance of NOMA based systems when compared with orthogonal multiple access (OMA) techniques. In this paper, we propose a user-set selection algorithm for IoT uplink transmission to improve the sum data rate of the NOMA based MIMO systems. In order to exchange data between the selected IoT pairs, we propose to employ wireless physical layer network coding (PNC) to further improve the spectral efficiency and reduce the delay to fulfill the requirements of future IoT applications. Performance evaluations are provided based on both sum data rate and bit error rate for the proposed NOMA based MIMO with PNC in the considered massive IoT scenarios.

The fifth generation New Radio vehicle-to-everything (5G NR-V2X) has higher requirements for delay and reliability, which brings challenges to the physical layer signal processing. Mobile edge computing (MEC) can provide larger capacity data storage and more efficient computation through localization of on-board unit (OBU) and next generation Node B (gNB) services. This paper combines the channel estimation of New Radio vehicle-to-infrastructure (NR-V2I) communication baseband signal processing with MEC and designs an intelligent channel estimation framework. In the MEC server, this paper proposes a channel estimation algorithm based on deep learning. This algorithm uses a one-dimensional convolutional neural network (1D CNN) to complete frequency-domain interpolation and conditional recurrent unit (CRU) for time-domain state prediction. Additional velocity coding vector and multipath coding vector track changes in the environment, and accurately train channel data in different mobile environments. System simulation and analysis show that the proposed algorithm improves the channel estimation accuracy, reduces the bit error rate, and enhances the robustness compared with the representative channel estimation algorithms for NR-V2I.

Vehicular ad hoc networks (VANETs) have attracted increasing attention in cross-regional communication. The interconnection between VANETs and satellite networks expands their communication range. To improve the transmission performance of heterogeneous networks composed of VANETs and satellite networks, this paper proposes an end-to-end transmission control scheme for satellite network-assisted VANETs, analyzes the bandwidth delay product of multihop VANETs through heterogeneous networks, and establishes a transmission control model applicable to cross-regional environments. To address the long delay and high bit error rate in heterogeneous networks, the model designs the congestion window in the slow start and congestion avoidance of the transmission scheme. The data transmission volume is increased in the slow start, and various packet losses are distinguished in congestion avoidance. The experimental results show that the scheme can achieve good transmission performance in heterogeneous networks composed of VANETs and satellite networks. The results show that VANETs data can be effectively transmitted in heterogeneous networks. Compared with the traditional transmission scheme, this simple and practical end-to-end transmission control scheme can improve speed by 83.49 kbps and reduce transmission duration time of FTP server by 4.72 x 10³ s. The results of this study provide a reference for massive data transmission in heterogeneous networks of VANETs and satellite networks.

The 5G networks promise to use advanced access techniques and modulation formats to achieve new requirements of the huge number of users such as higher data, high speed, and low latency. Millimeter-wave (MMW) signal and new modulation schemes such as universal filtered multicarrier (UFMC) and filtered bank multicarrier (FBMC) are playing a fundamental role to accomplish these requirements. UFMC and FBMC are classified under multicarrier modulation formats which are considered as a suitable modulation scheme in 5G and replacing a well-known modulation format of filtered orthogonal frequency division multiplexing (OFDM) which was used in 4G. This interest in using UFMC and FBMC in 5G wireless systems is the reduction of out-of-band (OOB) spectrum in UFMC and reduction of sidelobe suppression in FBMC. The contribution of this paper is to propose a model of wavelength conversion using a semiconductor optical amplifier (SOA) for both schemes UFMC and FBMC- off-set quadrature amplitude (OQAM). In addition, we analyze and compare their performance in terms of bit error rate (BER) and error vector magnitude (EVM) for a wavelength conversion application. Finally, we investigate the main disadvantage of OFDM which is the high Peak to Average Power Ratio (PAPR) for both schemes, and compare between them. Photonic switching of a 4 Gbps 16-QAM UFMC and FBMC-OQAM signal centered at 50 GHz is performed. The optical single-sideband (OSSB) signal is generated with 18.85 dB of sideband suppression ratio (SSR). The results show that the best values of BER and EVM can be obtained when the injection current (IC) is 0.7–0.9A. For converted signal using FBMC-OQAM, it has power penalty ∼ 2.5 dB at BER threshold 1 × 10 -3 and has also ∼ 2 dB power penalty compared to the UFMC scheme at EVM threshold 5.6%. In addition, the wavelength switching system with FBMC and UFMC modulation schemes achieves the same PAPR.

The concept of drone base stations (DBSs) has been applied to reduce the distance of the wireless link between a macro base station and its active users under diverse scenarios in military communications, smart industries, and high-density networks, and to provide service in topologies with damaged infrastructure. In this paper, we address the optimal positioning of multiple DBSs in a multiple-input multiple-output wireless network setting. We present a low-complexity machine learning-based algorithm to optimize the location of the DBSs by minimizing the collective wireless received signal strength experienced by the active terminals. The proposed algorithm reduces the propagation loss in the system and provides a lower bit error rate when compared with the Euclidean cost benchmark.

A general form of codebook design for code-domain non-orthogonal multiple access (CD-NOMA) can be considered equivalent to an autoencoder (AE)-based constellation design for multi-user multidimensional modulation (MU-MDM). Due to a constrained design space for optimal constellation, e.g., fixed resource mapping and equal power allocation to all codebooks, however, existing AE architectures produce constellations with suboptimal bit-error-rate (BER) performance. Accordingly, we propose a new architecture for MU-MDM AE and underlying training methodology for joint optimization of resource mapping and a constellation design with bit-to-symbol mapping, aiming at approaching the BER performance of a single-user MDM (SU-MDM) AE model with the same spectral efficiency. The core design of the proposed AE architecture is dense resource mapping combined with the novel power allocation layer that normalizes the sum of user codebook power across the entire resources. This globalizes the domain of the constellation design by enabling flexible resource mapping and power allocation. Furthermore, it allows the AE-based training to approach a global optimal MU-MDM constellations for CD-NOMA. Extensive BER simulation results demonstrate that the proposed design outperforms the existing CD-NOMA designs while approaching the single-user BER performance achieved by the equivalent SU-MDM AE within 0.3 dB over the additive white Gaussian noise channel.

Data-dependent superimposed training (DDST) scheme has shown the potential to achieve high bandwidth efficiency, while encounters symbol misidentification caused by hardware imperfection. To tackle these challenges, a joint model and data driven receiver scheme is proposed in this paper. Specifically, based on the conventional linear receiver model, the least squares (LS) estimation and zero forcing (ZF) equalization are first employed to extract the initial features for channel estimation and data detection. Then, shallow neural networks, named CE-Net and SD-Net, are developed to refine the channel estimation and data detection, where the imperfect hardware is modeled as a nonlinear function and data is utilized to train these neural networks to approximate it. Simulation results show that compared with the conventional minimum mean square error (MMSE) equalization scheme, the proposed one effectively suppresses the symbol misidentification and achieves similar or better bit error rate (BER) performance without the second-order statistics about the channel and noise.

Post-silicon electrical validation of high-speed input/output (HSIO) links is a critical process for product qualification schedules of high-performance computer platforms under current aggressive time-to-market commitments. Improvements in signaling methods, circuits, and process technologies have allowed HSIO data rates to scale well beyond 10 Gb/s. Noise and EM effects can create multiple signal integrity problems, which are aggravated by continuously faster bus technologies. The goal of post-silicon validation for HSIO links is to ensure design robustness of both receiver (Rx) and transmitter circuitry in real system environments. One of the most common ways to evaluate the performance of an HSIO link is to characterize the Rx jitter tolerance (JTOL) performance by measuring the bit error rate (BER) of the link under worst stressing conditions. However, JTOL testing is extremely time-consuming when executed at specification BER considering manufacturing process, voltage, and temperature test coverage. In order to significantly accelerate this process, we propose a novel approach for JTOL testing based on an efficient direct search optimization methodology. Our approach exploits the fast execution of a modified golden section search with a high BER, while overcoming the lack of correlation between different BERs by performing a downward linear search at the actual target BER until no errors are found. Our proposed methodology is validated in a realistic industrial server post-silicon validation platform for three different computer HSIO links: SATA, USB3, and PCIe3.

The paper presents the general requirements and an exemplary design of the RF front-end system that in today4s handset is a key consumer of power. The design is required to minimize the carbon footprint in mobile handsets devices, whilst facilitating cooperation, and providing the energy-efficient operation of multi-standards for 5G communications. It provides the basis of hardware solutions for RF front-end integration challenges and offers design features covering energy efficiency for power amplifiers (PAs), Internet of Things (IoT) controlled tunable filters and compact highly isolated multiple-input and multiple-output (MIMO) antennas. An optimum design requires synergetic collaboration between academic institutions and industry in order to satisfy the key requirements of sub-6 GHz energy-efficient 5G transceivers, incorporating energy efficiency, good linearity and the potential for low-cost manufacturing. A highly integrated RF transceiver was designed and implemented to transmit and receive a picture using compact MIMO antennas integrated with efficient tunable filters and high linearity PAs. The proposed system has achieved a bit error rate (BER) of less than 10-10 at a data rate of 600 Mb/s with a wireless communication distance of more than 1 meter and power dissipation of 18-20 mW using hybrid beamforming technology and 64-QAM modulation.

In this article, we consider secure communication over asymmetric dual-hop simultaneous wireless information and power transfer system having one free-space optical (FSO) link followed by one radio frequency (RF) link. We assume that the optical transmitter conveys secure information to the RF receiver through an intermediate relay, which exploits the decode-and-forward relaying technique. The FSO link encounters Malaga (M) distributed turbulence with pointing error, and RF link suffers double shadowed Rician fading. We investigate the consequences of pointing error, atmospheric turbulence, and energy harvesting on the performance of the proposed mixed FSO/RF SWIPT framework. Specifically, we derive the analytical expressions for statistical characteristics such as probability density function, amount of fading, average bit error rate (BER), outage probability (OP), and ergodic capacity. The asymptotic expression for OP is also derived to obtain the diversity order of the system. Based on these results, the physical layer security analysis is carried out, and the analytical expressions for secure OP and strictly positive secrecy capacity are derived. Herein, the two eavesdroppers are considered. In the first scenario, it is assumed that only the FSO link is overheard, while in the second scenario, both FSO and RF links are under simultaneous eavesdropping attack.

Semiconductor optical amplifier (SOA) is a promising solution for future O-band optical amplification. However, the SOA-induced nonlinearity will affect the quality of the signals and cause bit errors. Nowadays, the neural network is a hot topic in communication networks and has been considered a practical algorithm for signals equalization. In this paper, we investigate the performance of the three types of neural networks: deep neural networks (DNN), convolutional neural network (CNN), and long short term memory (LSTM) neural networks for the compensation of the SOA-induced nonlinearity. We first compare the fitting ability of the three neural networks on the saturated response of SOA. Based on the simulation result, LSTM has the best nonlinear expressiveness for the SOA-induced nonlinearity. Subsequently, we do some experimental validations in an intensity modulation and direct-detection (IM/DD) system, where the 100 Gbit/s pulse-amplitude-modulation-4 (PAM4) signals are transmitted over 80 km at O-band using an 18 GHz electro-absorption modulated laser (EML). The bit-error-ratio (BER) results show that the cell states in LSTM play a crucial role in nonlinearity compensation. Furthermore, LSTM offers the best equalization performance and can achieve a receiver sensitivity of -18.0 dBm.

This work proposes a sequence-dependent SRAM-based PUF with enhanced reliability. It expands the CPRs by order of (rows(sequencelength+2)× columns) for reliable authentication. The proposed bitcell utilizes split word-lines to control two access transistors separately. The PUF mode turns on two left word-lines and two right word-lines simultaneously, including 18 transistors for generating one-bit data. This proposed technique supports rendering multiple data maps from one chip. Besides, various temperature and voltage combinations can create a reliability map for each data map. A test chip was fabricated in 40 nm CMOS technology. The measured worst bit error rate is 0.8% at the nominal point (1V, 20∘C). From a single chip, the proposed PUF achieved the hamming distances of 41.29% for one sequence with different orders and 44.93% for other sequences, respectively. The measured inter-chip hamming distance is 49.64.

The design of an efficient and scalable Wireless Sensor Network (WSN) to accommodate the fluctuations in topology, node-mobility, node-density, and network-size is an exigent task. A meticulous investigation is necessitated to implement the sensor nodes in an appropriate topology at optimum node-mobility in ZigBee incorporated WSN networks to offer optimum Quality of Services (QoS). Subsequently, an attempt to compute the comprehensive recital of a non-beacon mode based 802.15.4/ZigBee integrated WSN network is demonstrated. An analytical model is designed using parameters such as back-off number, retransmission limit, and back-off exponent considering the impact of node-mobility which has not reported earlier. Further, the investigation is carried out experimentally by evaluating the different QoS metrics, for instance, throughput, network load, bit error rate (BER), received power, signal to noise ratio (SNR) and end-to-end delay for diverse node-density and network-size of a mobile Wireless Sensor Network. Based on the measurements obtained, the authors recommend implementing the mobile sensor nodes in a cluster-tree fashion to afford the best possible QoS services.

A 6 Gb/s 9.8 pJ/b rotatable non-contact connector applicable to industrial robot arms is developed. The proposed non-contact connector enables a high-speed and highly reliable wireless data connection between three-dimensional (3-D) cameras and an edge computer in an autonomously controlled robot. A rotatable transmission line coupler (RTLC) is proposed to accommodate the rotational operation of the robot arm. Since the proposed doughnut-shaped RTLC has a constant overlapped area at any rotation angle, the RTLC has a constant coupling gain at all rotation angles. To remove inter-symbol interference (ISI) occurring at a specific rotation angle, a pulse-equalizing receiver is also developed. An interface bridge IC is proposed to transfer a wide range of interface signals from a slow-control signal such as the control area network (CAN) to a high-speed video interface signal. A signal protocol conversion technique applying on-off keying (OOK) modulation is also developed in order to transfer slow legacy interfaces used in the robot arms that include a dc component. Experiments with a test chip fabricated in a 40 nm CMOS process confirmed that bit error rate (BER) was lower than 10⁻¹² at any rotation angle in a communication distance of 3 mm. The proposed system improves energy efficiency by a factor of 3.7, area efficiency by a factor of 1.8.

Terahertz band with a frequency range from 0.3 to 10 THz has become a promising research field due to its advantages such as high frequency and large available bandwidth. In this paper, we demonstrated the generation of terahertz signals based on the photonics-aided technology and the heterodyne coherent detection mechanism through experiments, and realized the transmission of the 325 GHz 30 Gbaud terahertz quadrature phase shift keying (QPSK) signal with a bit error ratio (BER) less than the 7% hard-decision forward-error-correction (HD-FEC) threshold of 3.810-3, and 325 GHz 16 Gbaud 16-ary quadrature amplitude modulation (16QAM) signal with a BER less than the 20% soft-decision forward-error-correction (SD-FEC) threshold of 2.010-2 over 1 m metallic hollow core fiber. In addition, the performances of the metallic hollow core fiber transmission system under different frequencies from 300 to 380 GHz have also been measured. With the help of the Volterra nonlinearity compensation (VNC) algorithm, the highest net transmission rate can be up to 140.625 Gbit/s for 300 GHz 30 Gbaud 64QAM signal with satisfying the 28% spatially coupled low density parity check (SC-LDPC) threshold of 5.210-2. By comparing the performances of the metallic hollow core fiber transmission system and wireless transmission system, we also proved the superiority of the hollow core fiber to transmit terahertz signals. The experimental results show that compared with the commonly used free space transmission, the hollow core fiber can be a promising candidate to transmit high-frequency terahertz signals with a high speed and a low loss, and is worthy of further study in the future.

In this work, we present a new Nyquist pulse that shows high tolerance to the timing-jitter, which is one of the key factors that ceil the end-to-end bit error rate performance of terahertz communications systems. As a proof-of-concept, an experiment is conducted using a 300 GHz photonics-based terahertz communications link in order to demonstrate the performance of the proposed waveform.

A wireline receiver consisting of a linear equalizer, a decision-feedback equalizer (DFE), a clock and data recovery (CDR) circuit, and a demultiplexer (DMUX) employs new circuit and architecture techniques that afford substantial power savings. Realized in 28-nm technology, the 56-Gb/s receiver has a bit error rate (BER) of less than 10⁻¹² for a channel loss of 25 dB at 28 GHz.

Reconfigurable intelligent surface (RIS) and spatial scattering modulation (SSM) are promising candidates for future generations of wireless communication. The former provides an enhanced transmission environment by providing an alternative communication path, while the latter boosts spectral efficiency. In this letter, we firstly propose a novel uplink millimeter-wave (mmWave) communication system that utilizes both RIS and SSM to support data transmission over wireless channels. Specifically, we design the reflecting phase shifters at the RIS to support the two-hop communications. Moreover, a maximum likelihood detector is adopted to a new system with RIS-SSM and a new analytical expression for a tight union upper bound on the bit error rate (BER) is derived. Monte Carlo simulation results are provided to verify the accuracy of the derived analytical expression. Numerical results reveal that the proposed RIS-SSM scheme has a significantly lower BER than the traditional SSM.

This paper presents the design and bit error rate (BER) analysis of a phase-independent non-orthogonalmultiple access (NOMA) system. The proposed NOMA system can utilize amplitude-coherent detection(ACD) which requires only the channel amplitude for equalization purposes. In what follows, threedifferent designs for realizing the detection of the proposed NOMA are investigated. One is based on themaximum likelihood (ML) principle, while the other two are based on successive interference cancellation(SIC). Closed-form expressions for the BER of all detectors are derived and compared with the BER ofthe coherent ML detector. The obtained results, which are corroborated by simulations, demonstrate that,in most scenarios, the BER is dominated by multiuser interference rather than the absence of the channelphase information. Consequently, the BER using ML and ACD are comparable for various cases ofinterest. The paper also shows that the SIC detector is just an alternative approach to realize the MLdetector, and hence, both detectors provide the same BER performance.

This paper presents an amplifier-chain-based XOR physical unclonable function (AC-XOR PUF), with the process- and/or bias-dependent voltage and amplification information of two identical amplifier chains serving as the entropy sources. The current-biased PUF cell using only 4 NMOS transistors achieves a small area with reduced temperature and supply sensitivity. Optimization on both the stage gain and stage number can reduce the input-referred noise (IRN) and improve the PUF reliability. We further employ an XOR gate to process the amplifier-chain outputs for the final response to improve the energy efficiency and uniqueness. The process- and bias-dependent stage amplification and the nonlinear amplifier-chain multiplication, which can significantly increase the number of modeling parameters and introduce a complex decision boundary respectively, can effectively resist machine learning (ML) modeling attacks. Fabricated in standard 65nm CMOS, the proposed AC-XOR PUF occupies an active area of 6845μm². Without discarding any challenge-response pairs (CRPs), this work features a measured worst case bit error rate (BER) of 5.70% across 1.06~1.55V and -30~125°C, while demonstrating a reliability (intra-die HD) and uniqueness (inter-die HD) of 0.58% and 49.92%, respectively. It also achieves a ML prediction accuracy of 50.72% using 80x 80x80 artificial neural network (ANN) with 1M CPRs as training set.

Practical realization of decision feedback equalizers (DFEs) has to date been limited to at most two taps in 100-Gb/s long-reach (LR) wireline applications due to significant power, area, and timing costs. This article presents a systolic many-tap low-complexity sliding-block decision feedback equalizer (SB-DFE) that overcomes the implementation challenges of conventional DFEs with no performance loss. A nine-tap configuration is demonstrated in a 112-Gb/s analog-to-digital converter (ADC)-digital signal processing (DSP) four-level pulse amplitude modulation (PAM-4) LR wireline receiver implemented in 7-nm FinFET. The architecture partitions the received signal into overlapping but computationally independent blocks thereby breaking the feedback loop of the DFE and allowing logic pipelining. Unlike existing feedback-breaking techniques, the computational overhead of the SB-DFE can be made arbitrarily small for any tap count--indeed, we show the practicality of SB-DFE implementations exceeding 30 taps. Optimized pipeline cuts are employed to minimize the latency through the SB-DFE while maintaining timing margin. The nine-tap SB-DFE is paired with a five-precursor tap feedforward equalizer (FFE) and compared to a two-tap-DFE 15-tap-FFE reference DSP implemented in the same receiver. A bit error rate of 2 x 10⁻¹² is measured over a 36-dB loss channel--at least an order-of-magnitude reduction compared to the reference DSP. Power is reduced by 0.33 pJ/b. DSP gate area is reduced by 30%. Noise tolerance is improved by 0.2-mV ${_{RMS}}$ . Error-free operation is demonstrated on an RS(544,514) KP4 forward error correction (FEC)-encoded link even when the DFE tap values are manually stressed. Techniques for further reduction in complexity are described.

This chapter discusses techniques to measure the performance of digital fiber-optic systems and subsystems. It provides an overview of digital optical transmission systems and their performance specifications, such as bit error rate (BER), the quality factor ( Q ), and techniques to measure them. In a fiber-optic transmission system, the receiver has to correctly recover the data carried by the optical carrier; receiver sensitivity and receiver OSNR tolerance are two useful receiver specifications. In practical applications, receiver sensitivity is useful for receiver noise-dominated optical systems, whereas required optical signal-to-noise ratio (R-OSNR) is often used in systems with inline optical amplifiers in which performance is mainly determined by the OSNR of the optical signal. In fiber-optic transmission systems, performance degradation can be caused by random noise and deterministic waveform distortion. Time jitter has always been an issue affecting the performance of digital communication systems and networks. There are a number of techniques to detect time jitter; among them the most widely used techniques are sampling oscilloscope measurement, phase detection measurement, and BER-scan measurement. A number of in situ performance-monitoring techniques for optical transmission systems are available, where data traffic carried in the system is used as probing signal for measurement. Physical parameters of the fiber system, such as chromatic dispersion, PMD, and PDL, can be extracted from these measurements without interrupting system operation. Furthermore, the chapter discusses the aspects of nonlinear crosstalk between wavelength channels, modulation instability, transmission performance measurements, and fiber-optic recirculating loops.

We demonstrate 100-Gbaud on-off-keying (OOK) transmission driven at a low voltage using an electro-optic (EO) polymer modulator combined with a silicon Mach-Zehnder interferometer waveguide. Various types of organic- and polymer-based modulators have been reported to perform efficient EO modulation and high-speed data transmission at over 100 Gbaud. However, there are critical concerns regarding the practical application of polymer devices in terms of environmental stability. In particular, long-term thermal storage and stability during operation require improvements before EO polymer modulators can be applied in practical systems. We have developed an EO polymer with enhanced thermophysical stability and used it to fabricate an efficient EO polymer modulator. In this study we extend our earlier work on high-speed EO polymer modulators by performing fiber-link 100-Gbaud OOK transmission at various operating temperatures. A thermal stability test revealed that the EO polymer modulator can survive high-temperature exposure up to 110°C. Error-free signal transmissions over a distance of 2.0 km was successfully demonstrated with a driving voltage of 1.9 Vpp and a bit error rate below the 7% overhead forward error correction threshold. The driving voltage, bandwidth, bit error rate, and fiber-link performance of the device are presented.

In this letter, we jointly consider the problems of blind channel estimation (BCE), channel equalization and data detection in underwater visible light communication (UVLC) systems. Specifically, we propose to solve them with a model-driven deep learning (DL) approach. Inspired by the module-based signal processing methodology and communication theory, we devise a new blind receiver architecture called blind detection network (BDNet), which consists of three modules corresponding to BCE, channel equalization, and symbol demapping, respectively. Different from existing BCE schemes, the BDNet does not directly estimate the channel itself, but instead estimates the inverse channel regardless of the scalar ambiguity issue by learning the latent channel features from the received signal only. The UVLC channel effects can then be partially compensated by the zero-forcing equalization module of BDNet. Finally, the symbol demapping module recovers the transmitted symbols with the aid of the learned decision thresholds. Simulation results show the competitive bit error rate performance of BDNet in comparison to conventional pilot-aided schemes.

The most significant challenge of underwater optical wireless communication (UOWC) system is to overcome its limited coverage. To expand the achievable communication range, we investigate the performance of the dual-hop UOWC system with simultaneous lightwave information and power transfer (SLIPT). The time splitting (TS) method is adopted for wireless power transfer in the proposed system, where the information and energy are transmitted in different phases. A suitable transmission strategy is designed for the model without additional power supply, which contains three phases, i.e. information transmission, energy transmission, and forwarding process. The expressions of the average bit error rate (BER) at the target node and the energy harvested by the relay node are derived over underwater attenuation channel. Then, the effects of the TS factor and the distances on the system performance are investigated in two sub-problems, which minimize the average BER while satisfying the energy harvesting and transmitting rate constraints. Numerical results indicate the performance improvement by adopting the relay node with SLIPT.

Labuan Bajo and Komodo National Park (KNP) are the government's agendas in the tourism sector by making the area a premium tourist destination. On that basis, the tourism potential of the region requires infrastructure development to support this plan. One of the critical infrastructures is telecommunications, where the region does not have a direct fiber-optic line. In this paper, the authors propose two scenarios design of fiber-optic networks that also consider the potential for an upward fault earthquake in the northern waters of Labuan Bajo and KNP. The design is analyzed using calculation results of the power link budget, rise time, bit error rate (BER), and Signal to Noise Ratio. The BER value obtained is 5.63 x 10-13, which is still below the parameter threshold of 10-12 with a design that avoids the epicenter of the disaster and a longer route. The SNR value on the longest route (route 7) is 34.69 dB. The SNR value has met the SNR standard, which is 21.5 dB.

In this paper, we study on-axis (point like) scintillation, change in scintillation index depending on receiver aperture radius, and bit error rate evaluation of Lommel beam. Scintillation index formula is derived using well known Rytov method and numerical values are evaluated benefiting from random phase screen approach. We investigate that scintillation indexes of all types of Lommel beams are less than Gauss beam. In addition, raise in asymmetry parameter $$c$$ mitigates on-axis and aperture averaged scintillation. We finally conclude that Lommel beam is well ahead in case of bit error rate(BER) under weak turbulent and low signal to noise ratio(SNR) conditions.

Photon counting detectors such as single-photon avalanche diode (SPAD) arrays can be employed to achieve reliable optical wireless communication at power limited regimes. However, SPAD-based receivers suffer from significant dead time induced intersymbol interference (ISI) especially when the incident photon rate is relatively high and the dead time is comparable or even larger than the symbol duration, i.e., sub-dead-time regime. In this work, we propose a novel time-gated SPAD receiver to mitigate such ISI effects and improve the communication performance. When operated in the gated mode, the SPAD can be activated and deactivated in well-defined time intervals. We investigate the statistics of the detected photon count for the proposed time-gated SPAD receiver. It is demonstrated that the gate-ON time interval can be optimized to achieve the best bit error rate (BER) performance. Our extensive performance analysis illustrates the superiority of the time-gated SPAD receiver over the traditional free-running receiver in terms of the BER and data rate performance and the tolerance to background light.

This paper proposes a 7-dimensional ( 7D ) Cellular Neural Network (CNN) based offset quadrature amplitude modulation filter bank multicarrier (OQAM-FBMC) encryption scheme for seven core fiber. The chaotic sequences generated by 7D CNN are applied to produce the masking vectors to encrypt the phase, carrier frequency, and time. In order to verify the performance of the encryption scheme, 70 Gb/s (7×10 Gb/s) encrypted OQAM-FBMC signal transmission over 2 km 7 core fiber is experimentally demonstrated. The key space of 7D CNN can reach 101575 and the scrambling degree can be maintained at 100% regardless of the number of symbols. The experimental results also show that when some keys are compromised, the system's bit error rate (BER) can still reach above 0.46, which effectively ensures the security of the system. Due to its good performance in security, the proposed scheme has important application prospects in future optical access network.

The domain of underwater wireless communication (UWC) link is gaining much attention due to an increase in various underwater activities such as offshore hydrocarbon exploration, underwater unmanned vehicles (UUV), and military practices. Increased bandwidth and a reliable data link are mainly required for such activities. Both requirements of the domain are heavily affected by the highly conductive property of the seawater. This paper demonstrates the performance evaluation of radiofrequency-UWC, focusing on surface wave analysis, to propose a reliable solution for offshore activities. A constructive interference scheme can be useful due to the sharp difference in the properties of the two mediums (air and seawater). To that end, an experimental setup is created, and a corresponding finite element method (FEM) based simulation of the radio-based wireless link is run. This is because it has higher bandwidth and speed than acoustic and optical approaches. A conduction current mechanism transmits and receives data in a synthetic water tank containing a prepared conductive media (saltwater). The study of changing depths of transmitter-receiver nodes in saltwater shows that surface waves cause significant noise reception in shallow water (less than dipole length, below water level). During a series of experiments in the tank, the lowest bit error rate (BER) is observed only when the node’s submerged height was greater than dipole length. As a result, it is meant to provide a genuine data channel model. The discovery and analysis will aid in the development of a dependable underwater data link, with applications including short-range diver-to-diver communication, and UUV capability.

5G defines below 100 GHz as the millimeter-wave bands, whereas 100 GHz - 3 THz is categorized as THz band in 6G. Deep leraning (DL) is expected to enable a significant paradigm shift in 6G wireless networks. In this paper, D-band 90-Gbps single channel PAM-4 signal generation and transmission over 10-km SMF and 3-m wireless link at 140-GHz can be achieved. A novel complex-valued neural network (CVNN) equalizer using ‘CReLU’ activation function to directly recover PAM-4 signals from received noised signals is demonstrated. There are three DSP options in the experiment. In Opt .1, firstly conducted cascaded multi-modulus algorithm (CMMA) pre-equalization (pre-EQ) at transmitter, then processed via frequency offset estimation (FOE), carrier phase recovery (CPR) and finally real-valued neural network (RVNN) equalization at receiver. Here, the RVNN equalizers include DNN with a softmax output layer, two-step joint-DNN equalizer and LSTM. The experimental results show that LSTM-based equalizer outperforms the other real NN-based equalizers by average 0.5 to 1.5 dB at BER of 10−3 magnitude. Differently from Opt . 1, real-valued CMMA pre-EQ at transmitter is unexpected for CVNN in the other two options. In Opt . 2, we only combine down-conversion and CVNN regarded as ‘pure data-driven’ training at receiver. This pure data-driven CVNN equalizer improves BER a lot and also has a larger computation burden, especially BER is as low as 1 × 10−4 with n 0 = 571 and n 1 = 200 training cells and the time complexity reaches 350000 in one iteration. Thanks to the aid of traditional mathematical-oriented models including FOE and CPR, the computation burden of CVNN in Opt . 3 is released significantly. Furthermore, we compare the performance of CVNN and RVNN in terms of BER decision accuracy, time complexity and receiver sensitivity. Followed by the same DSP with the same complexity, the comparison result between DNN and CVNN in the same structure of [371-260-1] with 11000 samples and 300 epochs shows that CVNN performs better due to its reservation of phase information. Therefore, we believe that the joint use of model-based, e.g., FOE, CPR steps and complex DL-based techniques has a potential for the future 6G wireless physical layer algorithms.

In this letter, an enhanced machine learning (ML) framework combining radial phase grating (RPG) and channel information has been proposed for underwater wireless optical orbital angular momentum (OAM) communications. The optical irradiance profile and diffraction pattern are simulated by the combination of split-step angular-spectrum propagation and Monte Carlo methods, then they were embedded by the convolution and fully connected layers. The transfer learning-based ML architectures are trained by the image features and the embedding channel information with fine-tuning. The impacts of oceanic turbulence, seawater types, and transmission distance are considered. Results show that the transfer learning-based OAM detectors could achieve the order-of-magnitude gain in the bit error rate. Besides, the proposed ML framework could combine with a variety of state-of-the-art methods and thus improve the system performance. This work indicates transfer learning-based ML frameworks have great potential in ML-based OAM communication systems.

This letter addresses a problem of differential demodulation in a 2-source Hierarchical MAC (H-MAC) in the context of a Wireless Physical Layer Network Coded system with Hierarchical Decode and Forward strategy. We assume a parametric H-MAC with known attenuations but unknown phases. Component phases have generally strong impact on the resulting superposed constellation which poses high demands on the accuracy of their estimation. In this letter we propose multiple suboptimal closed-form differential demodulation methods which do not require explicit phase estimation and thus substantially simplify the receiver processing. We analyze and compare their performance. Particularly we measure the resulting hierarchical bit error rate for all proposed demodulation methods for different scenarios of a particular symbol alphabet and channel attenuation values. For comparison we include a reference scenario of a fully coherent demodulation.

Orthogonal frequency division multiplexing (OFDM) is a popular multicarrier technique in communication system owing to its robustness against multipath fading and less complexity. Deep learning (DL...

A silicon Mach Zehnder modulator (MZM) with high modulation efficiency was designed using a core-based split PN junction phase shifter. The novel design of the phase shifter improves the optical confinement, reduces the optical loss. The use of the travelling wave electrode improves the coupling between the microwave and optical mode. The proposed design achieved a high modulation efficiency of 0.75V.cm with 1.5mm phase shifter. With this modulation efficiency, an extinction ratio of 7.37dB and 1.69 × 10− 12 bit error rate was achieved at a bit rate of 90Gbps. The energy per bit transmission of the data was 3.91pJ/bit. The phase shifter in silicon MZM (PS-MZM) was analysed for its supporting transmission distance and bit rate at ITU-T recommended DWDM wavelength of 1552.5 nm. It ensures that PS-MZM is suitable for on-chip and off-chip communication data centre application in unguided (free space optics (FSO)) and guided (optical fibre) transmission medium. The proposed device can also be implemented in delay lines, switches etc.

In this work, the deep learning (DL)-based fifth-generation (5G) non-orthogonal multiple access (NOMA) detector is investigated over the independent and identically distributed (i.i.d.) Nakagami- m fading channel conditions. The end-to-end system performance comparisons are given between the DL NOMA detector with the existing conventional successive interference cancelation (SIC)-based NOMA detector and from results, it has been proved that the DL NOMA detector performance is better than the convention SIC NOMA detector. In our analysis, the long-short term memory (LSTM) recurrent neural network (RNN) is employed, and the results are compared with the minimum mean square estimation (MMSE) and least square estimation (LS) detector’s performance considering all practical conditions such as multipath fading and nonlinear clipping distortion. It has been shown that with the increase in the relay to destination (RD) channel gain, the bit error rate (BER) improves. Also, with the increase in fading parameter m, the BER performance improves. The simulation curves demonstrate that when the clipping ratio (CR) is unity, the performance of the DL-based detector significantly improves as compared to the MMSE and LS detector for the signal-to-noise ratio (SNR) values greater than 15 dB and it proves that the DL technique is more robust to the nonlinear clipping distortion.

In 5G massive machine-type communication (mMTC), power-limited or battery-free parasite devices such as radio frequency identification (RFID) tags, can use the transmitted signals from host devices as ambient signals for backscatter communications to send information to a base station (BS). Unmanned aerial vehicles (UAVs) can be employed as host devices to help transmissions of parasite devices due to the advantages of high mobility and low operating cost. In this paper, we propose a signal detection approach based on the central limit theorem to detect the presence of parasite devices and separate parasite signals from host signals. Then, closed-form expressions for the probability of error detection and the bit error rate (BER) are derived. Moreover, the trajectory planning of multiple UAVs is optimized with the consideration of minimizing the energy consumption of UAV swarms to serve parasite devices. Theoretical and simulation results show that our proposed method provides good detection performance for parasite devices. It also shows that the trajectory planning of multiple UAVs is optimized.

In this letter, a novel hybrid code-domain index modulation (CDIM) scheme is proposed for future multi-domain communications, where the indices of the interleaving and spreading codes are exploited for information transmission. Specifically, we first provide a general design framework for CDIM, including the bit-to-symbol mapping rule and the detector. Then, we propose a code optimization method to select the utilized interleaver sequence and spreading code, with the objective of significantly improving the bit error ratio (BER) performance. Moreover, an intelligent detector is also proposed for CDIM in complicated wireless communication scenarios, e.g., non-Gaussian wireless channels. Simulation results show that the proposed CDIM is capable of substantially improving the system error performance compared with the conventional coded wireless communication systems.

Hollow-core fibers offer a range of beneficial properties for high-speed optical communication applications, including low latency, low chromatic dispersion and nonlinearity. Based on a system employing a ~5-km span of hollow-core nested antiresonant nodeless fiber (NANF), we demonstrate in this paper, penalty-free Nyquist 4-ary pulse amplitude modulation transmission relative to the back-to-back at 80, 100 and 112 Gb/s over the S+C+L-bands. Furthermore, using multi-carrier direct-detection optical orthogonal frequency division multiplexing, we show that compared to a standard single-mode fiber of a similar length, the NANF exhibits a significantly better bit error rate (BER) performance at 1550 nm and offers more than 20% capacity enhancement. Consequently, up to 138.09-Gb/s capacity has been achieved at a BER threshold of 3.8×10-3 after ~5-km transmission. We conclude that the use of NANF offers a promising solution for achieving simultaneously high capacity and low latency in future short-reach optical interconnects.

Optical superchannels provide a route to obtaining the highest achievable data rates in optical fiber systems. Here, we investigate the role of optical filtering on system performance and required optical signal-to-noise ratio, when receiving a single sub-band from an optical superchannel, where the dominant noise source changes from optical to transceiver noise. We find that optical filtering can provide improvement up to 3 dB in signal quality and around 1 b/symbol in information rate, in an experiment where transceiver noise is dominant.

Non-orthogonal multiple access based cooperative relaying system (NOMA-CRS) has been proposed to alleviate the decay in spectral efficiency of the conventional CRS. However, existing NOMA-CRS studies assume perfect successive interference canceler at the relay and mostly investigate sum-rate whereas the error performance has not been taken into consideration. In this paper, we analyze error performance of the NOMA-CRS and the closed-form bit error probability (BEP) expression is derived over Nakagami-m fading channels. Then, thanks to the high performance of machine learning (ML) in challenging optimization problems, a joint power sharing-power allocation (PS-PA) scheme is proposed to minimize the bit error rate (BER) of the NOMA-CRS. The proposed ML-assisted optimization has a very low online implementation complexity. Based on provided extensive simulations, theoretical BEP analysis is validated. Besides, the proposed ML-aided PS-PA provides minimum BER (MBER) and outperforms previous PA strategies for the NOMA-CRS notably., Comment: accepted by IEEE TVT

Ambient backscatter communication (AmBC) leverages the existing ambient radio frequency (RF) environment to implement communication with battery-free devices. The key challenge in the development of AmBC is the very weak RF signals backscattered by the AmBC Tag. To overcome this challenge, we propose the use of orthogonal space-time block codes (OSTBC) by incorporating multiple antennas at the Tag as well as at the Reader. Our approach considers both coherent and non-coherent OSTBC so that systems with and without channel state information can be considered. To allow the application of OSTBC, we develop an approximate linearized and normalized multiple-input multiple-output (MIMO) channel model for the AmBC system. This MIMO channel model is shown to be accurate for a wide range of useful operating conditions. Two coherent detectors and a non-coherent detector are also provided based on the proposed AmBC channel model. Simulation results show that enhanced bit error rate performance can be achieved, demonstrating the benefit of using multiple antennas at the Tag as well as the Reader., 13 pages, 10 figures

Wireless Body Area Networks (WBANs) consist of tiny Biomedical Wireless Sensors (BWSs) and a Gate Way (GW) to connect to the external databases in the hospital and medical centres. The GW could connect the BWSs, to a range of wireless telecomnumication networks. These wireless telecommunication networks could be either a mobile phone network, a standard telephone network a dedicated medical centre or using public Wireless Local Area Networks (WLANs) nodes also known a Wi-Fi system. The electrocardiogram (ECG) signals are widely used in health care systems because they are non-invasive mechanisms to establish medical diagnosis of heart diseases. The current ECG systems suffer from important limitations: limited patient's mobility, limited energy, limited on wireless applications. The main drawback of current EGG systems is the location-specific nature of the systems due to the use of fixed/wired applications. That is why; there is a critical need to improve the current ECG systems to cover security handling and to achieve extended patient's mobility. With this in mind, Compressed Sensing (CS) procedure and the collaboration of Block Sparse Bayesian Learning (BSBL) framework is used to provide a robust low sampling-rate approach for normal and abnormal ECG signals. Advanced WBANs based on our approach will be able to deliver healthcare not only to patients in hospital and medical centres; but also in their homes and workplaces thus offering cost saving, and improving the quality of life. Our simulation results based on two proposed algorithms illustrate 15% incensement of Signal to Noise Ratio (SNR) and a good level of quality for the degree of incoherence between the random measurement and sparsity matrices.

Optical wireless communications (OWC) has emerged as a strong candidate for wireless communications, due to the capacity limitation in the radio frequency (RF) spectrum. Especially visible light communication (VLC) has great potential for short-range outdoor vehicular communications, as vehicle LED lights also transmit data. However, outdoor VLC channels vary fast and, experience multipath scattering and reflection resulting in time domain dispersion. Outdoor VLC links are also subjected to high levels of ambient noise, especially from the sun. Orthogonal frequency-division multiplexing (OFDM), which has proven robustness to multi path fading and noise effects in RF links can also be deployed in VLC links. In this paper, optical OFDM (O-OFDM) along with adaptive modulation scheme is investigated in VLC for vehicle to vehicle (V2V) communications. A (2 x 2) multiple input multiple output (MIMO) channel, with multiple polarimetric bidirectional reflections and realistic sunlight interference is considered. Two schemes of O-OFDM; direct current biased optical OFDM (DCO-OFDM) and asymmetrically clipped optical OFDM (ACO-OFDM) are investigated. Simulation results of the proposed model show increase in data rates up to 50 Mbps along with reduced bit error rate (BER) under both line of sight (LOS) and non-LOS and high noise conditions.

The transmission of the high data rate and information over the optical fiber is restricted by various dispersion phenomenon which further results into intersymbol interference (ISI). This article proposes two different methodologies for optical fiber deformation aiding vibration monitoring one using the pin diode as a photo-detector device and another manifesting the avalanche photo-detector. The novelty of this article lies in optical signal conversion using photo-detector processing followed by low pass Gaussian filter in order to reduce the extra contortion. This work is approaching electronic dispersion compensation technique (EDC) for compensation of chromatic dispersion at two distinct bit rates of 25 and 30 Gbps over 120 km of single mode fiber. Both the diodes have tested for theory performance using factors like Q-factor, bit error rate and eye height. It is found that pin diode is exhibiting a quality factor of 67.150 and 40.5944 at 25 and 30 Gbps, respectively. When avalanche pin diode is used at the same data rates, quality factor of 73.0240 and 43.3523 are obtained, respectively. Hence, use of avalanche photodiode at high bit rates is utilized and the simulations showed the optimum photo-diode for efficacious dispersion compensation at such a long transmission distance.

In this paper, an enhanced independent component analysis (ICA) method is proposed for blind separation of noisy mixture signals. Considering the conventional ICA methods always have an inadequate capacity of resisting noisy effect. This phenomenon is usually encountered in wireless receiving processing. To obtain the improved separation quality, two mechanisms are conducted to formulate the modified cost function and the powerful optimization learning for investigating an enhanced ICA method.The fundamental of the proposed method is derived from the minimum bit error rate (BER) criterion and the Nesterov-accelerated adaptive moment estimation (Nadam) optimization approach. The main work of this paper includes the following facets. Firstly, a maximum likelihood (ML) principle cost function with minimum BER constraint is derived. Secondly, the modified cost function is by utilizing Nadam learning processing. Lastly, theoretical analysis and experiment results verify the improved performance quality of the proposed enhanced ICA method compared with popular representative ICA methods.

With the advancements and increase in the transportation system in the current scenario, making transports intelligent is an important aspect for enhancing the safety, security and related commercial applications. Vehicular ad-hoc network has been evolved for the implementation of intelligent transportation systems. Vehicular scenario comprising of multipath fading, interference, dispersion and mobility distort the communication among the vehicles and between vehicles and surroundings. This work implements adaptive modulation and coding technique in the existing vehicular communication transmission process. Simulations were carried out for different transmission schemes with different code rate over several wireless channels for varying signal-to-noise ratio for performance evaluation. The results of this simulation testify that the proposed technique serves better than fixed transmission scheme in terms of bit error rate and spectral efficiency. Adaptive modulation together with turbo coding shows an approximate gain of 10 dB signal-to-noise ratio relative to fixed schemes.

Current research emphasis on IoT (Internet-of-Things) to enable physical objects to connect, co-ordinate among themselves in a ubiquitous manner. Specifically, for this type of applications, the quality of wireless communication is indeed considered vital to enhance the reliability of battery operated IoT devices. Moreover, these devices operate on unlicensed bands creating heavy congestion on spectrum. Interestingly operating these devices on Cognitive Radio band avoids the spectrum shortage problem by exploiting the dynamic spectrum access capabilities. Cognitive relaying for IoT applications ensures reliable communication through interference mitigation among co-existing IoT devices. In this paper, we therefore propose spectrally efficient two-path decode and amplify relaying technique in three time slots through network-coded co-operation of Primary user and Secondary User. To address the interference issues, optimum power allocation is formulated as a convex optimization problem solved through a modeling system named CVX. Thereby we achieve co-operative diversity without the need for additional antennas for IoT networks. Performance evaluation compares the Bit Error Rate for different relaying schemes with and without optimum power allocation. Our simulation results ensure that the probability of error is minimized and rate is maximized by our proposed algorithm.