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This work considers minimizing the communications bit error rate (BER) of unmanned aerial vehicle (UAV) when assisted by intelligent reflecting surfaces (IRSs). By noting that increasing the number of IRS elements in the presence of phase errors does not necessarily improve the system’s BER, it is crucial to use only the elements that contribute to reducing such a parameter. To this end, we propose an efficient algorithm to select the elements that can improve BER. The proposed algorithm has lower complexity and comparable BER to the optimum selection process which is an NP-hard problem. The accuracy of the estimated phase is evaluated by deriving the probability distribution function (PDF) of the least-square (LS) channel estimator, and showing that the PDF can be closely approximated by the von Mises distribution at high signal-to-noise ratios (SNRs). The obtained analytical and simulation results show that using all the available reflectors can significantly deteriorate the BER, and thus, partial element selection is necessary. It is shown that, in some scenarios, using about 26% of the reflectors provides more than 10 fold BER reduction. The number of selected reflectors may drop to only 10% of the total elements. As such, the unassigned 90% of the elements can be allocated to serve other users, and the overhead associated with phase information is significantly reduced.

This paper presents the implementation and experimental evaluation of a short-packet physical-layer network coding (PNC) system. Implementation of short-packet PNC systems is challenging. First, short packets may have only a few pilot symbols for synchronization and channel estimation purposes. Increasing the number of pilots increases the overhead; decreasing the number of pilots, on the other hand, degrades the packet error rate performance. Second, many short-packet systems are meant for applications with very stringent delay requirements. Employing advanced but complex PNC channel decoding may result in unacceptable delay due to the processing delay. This work presents a low-complexity and low-overhead physical-layer design of OFDM-based short-packet PNC systems, implemented over the software-defined radio platform. Our design makes use of only a small number of pilots (without separate OFDM preamble symbols) to address issues such as slot synchronization, packet detection, carrier frequency offsets, and mismatched channel state information. Our design employs reduced-complexity XOR channel decoding based code-aided parameter estimation (that includes synchronization and channel estimation) to compensate for the limitations imposed by having a small number of pilots. This is the first demonstration that provides a practical framework for applying PNC to short-packet communications.

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.

In many papers, random modulation of power electronic converters is described as an electromagnetic interference (EMI) mitigation technique, which contributes to the assurance of electromagnetic compatibility (EMC) of systems consisting of power electronic converters and serial transmission-based control and measuring devices. However, experimental results as well as theoretical analyses of physical phenomenon suggest that the EMI reduction is ostensible and results from the measuring procedure adopted in standards. This article presents the first known approach to compare the influence of deterministic and random modulation of transmission errors rate in serial communication systems. The comparison is based on the especially developed mathematical models, which are validated experimentally, using a simple setup with a dc/dc converter injecting a noise into the USB/RS232 converter representing a serial transmission scheme. The comparison reveals that for the studied switching frequency range from 10 kHz to 1 MHz, on average, there is no significant difference between random and deterministic modulations with respect to the probability of error rate in serial communication systems. Thus, in such systems, random modulation should not be considered as a valid EMC-assuring technique.

Diffusion-based molecular communication (DBMC) systems allow messenger molecules to reach the intended receiver using laws of diffusion. The Brownian motion of messenger molecules introduces delay in the system causing the problem of inter-symbol interference (ISI). Along with ISI, the problem of inter-link interference (ILI) comes into picture in the diffusion-based molecular multiple-input multiple-output (DB-MoMIMO) systems. To combat against ISI and ILI issues, index modulation (IM) approaches are recently proposed in the literature for improving the performance of DB-MoMIMO systems. Despite the existence of IM approaches, problems of ISI and ILI still persist due to the slow random motion of molecules in DB-MoMIMO channels. Motivated by this, a novel coded modulation approach called molecular spatio-temporal coded modulation (MSTCM) is proposed in this paper which shows promising improvement in the performance of DB-MoMIMO systems by encoding the information both in space and time axes. Further, if system has access to two types of molecules, the dual-type modulation schemes are discussed for the same. Moreover, the encoder and decoder designs for the proposed mapping strategy are provided. In addition, a theoretical bit error rate expression for the MSTCM scheme is derived and simulation results are shown to corroborate the theoretical ones.

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.

Intelligent Transportation Systems (ITS) aim at integration of innovative technologies in next-generation vehicles in order to increase the safety and efficiency standards of vehicular traffic fluxes. Although many sensors are currently available in modern cars, mutual data exchange between vehicles in real-time will be crucial in future smart vehicles, but this domain, and in particular bidirectional Vehicle-to-Vehicle (V2V) through Visible Light Communications (VLC), remain relatively unexplored yet. In this paper we present a system for bidirectional data transmission between vehicles through VLC. Specifically, we implement for the first time a bidirectional VLC link using real motorcycle headlights (HL) and rear lights (RL), and we provide a characterization of transmission performances under direct sunlight conditions in an outdoor scenario for realistic distances (up to 30 m) and relative positions between two vehicles. The performance of the VLC system has been evaluated in terms of Signal-to-Noise (SNR) maps and Packet Error Rate (PER), measured in various configurations and for different baudrates (28 kBaud / 57 kBaud). Our result show that a bidirectional error-free communication is possible between two consecutive vehicles for distances up to 12 m, whilst successful transmission could be observed up to 21 m. Finally, we compare our bidirectional intensity and PER data in realistic (flat) configuration against the predictions of a physical model which considers non-ideal orientations of the receiver stage through a novel, simple technique that could also be exploited in different VLC implementations. A very good agreement between the experimental data set and the model is found on the whole measurements grid.

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.

To further mitigate the BER error floor of M-ary differential chaos shift keying modulation for impulsive noise, a low-cost high-reliability coded modulation scheme without equalizations is desirable for impulsive noise. In this paper, a protograph-based low-density parity-check coded MDCSK-based bit-interleaved coded modulation scheme is proposed for the scenario with impulsive noise. Considering the Gaussian distribution of protograph extrinsic information transfer and the benchmark of coding design, the U-shaped non-coherent capacity is derived with optimal code rate for square MDCSK, showing that the code rates are stable with E_b/N_0 increasing but still much lower than that of DS-16DQAM at code rate >0.145. The derived joint probability density function can be considered as approximately a Gaussian distribution, which is used to improve the impulsive noise fitted PEXIT. Finally, a new code under a novel principle is designed for better bit error rate performance based on the improved PEXIT analysis. Both PEXIT analysis and simulation results demonstrate that the proposed scheme achieves a better BER than that with a traditional scheme, and suggesting a research approach based on simple methods. This basic research work provides a guide to establish a framework and optimize the performance of transmission systems over practical power line communication.

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.

In recent years, micro-nano device characteristics like ferroelectrics and resistive switching are being used to build important security primitives such as Physical Unclonable Function (PUF). The micro-nano device-based hardware security primitives, although with higher security, energy efficiency, and integration density, suffer from serious reliability issues caused by process scaling. To mitigate this issue, this paper introduces a reconfigurable weak PUF based on spin-transfer torque magnetoresistive random-access memory (STT-MRAM), which adopts the crossing switches implemented with simple demultiplexes (DEMUXs) to improve the flexibility and reliability. Moreover, two algorithms, \texttt{neighboring bit lines} and \texttt{top-n}, are proposed to enlarge the gap between two parallel reading currents, thus further enhancing the reliability of PUF responses. Experimental results demonstrate that the proposed PUF scheme achieves good uniqueness (50.64\%), uniformity (50.02\%), and bit-aliasing ( $\approx$ 49.80\%). Particularly, the proposed method significantly improves the PUF reliability, achieving low bit error rate (BER $\leq$ 2.13\%) within the range of -20 $^\circ$ C to 90 $^\circ$ C.}

The unmanned aerial vehicle (UAV) assisted communication can significantly improve the coverage and spectrum efficiency of the Internet of Things (IoT). One main feature of IoT is short packet communication (SPC), in which the data transmission uses finite block-length codewords. The transmission rate and the packet error rate will affect the effective throughput of the IoT. In this paper, we investigate the impact of SPC on the performance of UAV-enabled spectrum sharing network. Specifically, the optimization of energy efficiency (EE) in the UAV communication system is considered since the battery of the UAV is usually limited. We design the packet error rate, the sensing duration, the normalized sensing threshold and the UAV’s transmit power to maximize the EE under the constraint that the primary user is sufficiently protected. Since the system parameters are intertwined with each other, we employ a successive optimization algorithm to solve the optimization problem by dividing it into three subproblems. Then, an efficient iterative algorithm is proposed to obtain the optimal parameters. Simulation results reveal that the proposed algorithm can converge to global optimal value and has better EE performance than other benchmark schemes. And there is a fundamental tradeoff between the throughput and the EE.

For NAND flash memory, designing a good low-density parity-check (LDPC) decoding algorithm could ensure data reliability. When the decoding algorithm is implemented in hardware, it is necessary to achieve attractive trade off between implementation complexity and decoding performance. In this paper, a novel low bit-width decoding scheme is introduced. In this scheme, the Quasi-Cyclic LDPC (QC-LDPC) is used, and the row-layered normalized min-sum algorithm is improved by restricting the amplitude of minimum and second-minimum values in each check node (CN) updating. The simulation shows that our approach achieves a lower UBER (Uncorrectable Bit Error Rate) with a negligible increase in computational complexity, especially with low precision input log-likelihood ratio (LLR).

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.

A novel analytical propagation model for diffusive molecular communication systems in a three-dimensional fluid environment is derived. The model takes into account the geometry of a spherical receiver, the inclination angle, and the reaction rate of the receiver to accurately model the time-varying distribution and the number of absorbed information molecules at the receiver over a period of time. Accordingly, we derive an expression for the net number of accumulatively-absorbed information molecules at the surface of the receiver. We also study the bit error rate (BER) performance of diffusion-based molecular communications in the presence of the inter-symbol interference. Simulations based on the developed model show the impact of the transmitter-receiver distance, the reaction rate at the surface of the receiver and the diffusion constant of the environment on the fraction of absorbed molecules and the BER performance. A particle-based simulator is implemented to verify the accuracy of the proposed model. Moreover, our results are compared with that of a conventional model, where the geometry of the receiver and the inclination angle are ignored. It is shown that, especially at small transmitter-receiver separation distances, the proposed model predicts a significantly smaller number of absorbed molecules compared to the conventional models.

Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) is presented to enhance the spectral and energy efficiency over the conventional cyclic prefix OFDM and zero padding OFDM, but the interbloc interference (IBI) between the data block and adjacent pilot symbols deteriorates its performance. The IBI is considered as the main TDS-OFDM drawback in the harsh long-delay underwater acoustic (UWA) multipath channel. This article proposes a new scheme called X-transform time-domain synchronous index modulation (IM) OFDM to eliminate the TDS-OFDM IBI, explore the multipath diversity, and reduce the peak-to-average power ratio (PAPR). Particularly, X-transform, which merges the discrete Hartley transform and discrete Fourier transform in a very low-complexity unitary matrix, and IM techniques have been employed to remove the effects of IBI existing in underwater acoustic (UWA) TDS-OFDM. Moreover, compressive sensing has been adopted to guarantee a reliable UWA channel estimation based on a guard interval IBI-free region. The proposed scheme is evaluated over simulated and experimental UWA channels. The computer simulation and the real experiment show the outperformance of the proposed scheme in terms of bit error rate, computational complexity, PAPR, energy efficiency, and spectral efficiency over its conventional benchmarks.

In recent years, LoRa has been deployed in countless Internet of Things (IoT) applications across the globe. However, as LoRa is a proprietary technology, research into its physical-layer performance has been challenging. Implementing LoRa on software defined radio (SDR) platforms yields valuable insight into the physical layer of the LoRa standard and paves the way for improvements in packet reception capabilities for LoRa receivers. This paper presents an independently developed packet reception algorithm, which drastically improves the physical performance of LoRa communication links. The advanced signal presence detection, synchronization and symbol detection strategies are shown to significantly increase packet reception ratios in extremely adverse noise conditions. Multiple algorithm variations are presented and compared in terms of bit error rate (BER) performance and computational cost. In comparison to a theoretical system with perfect channel state information, the simulated bit error rate performance of the best performing algorithm only requires an increase of 1.6 dB in signal-to-noise ratio (SNR) to exhibit the same performance. Finally, SDR implementations of the algorithms exhibit average SNR performance gains up to 4.7 dB when compared to commercially available hardware.

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.

Relay-assisted free space optical (FSO) systems offer several advantages such as cooperative diversity, mitigating turbulence-induced fading, and broad coverage area. Despite these manifold advantages, they can still be affected by unfavorable activities of jammer. Therefore, it is of high importance and need to investigate random jamming specially for security-constrained cooperative FSO communication protocol. This article develops a new system model of relay-assisted FSO system and studies a novel mathematical framework to analyze the performance of decode-and-forward protocol-based cooperative FSO system in presence of random relay jamming effects. In presence of jammer, the probability density functions (pdfs) of different additive noises, i.e., a mixture of negative exponential and Gaussian random variables (RVs) and mixture of negative exponential RVs are derived. A closed-form expression of the average bit error rate (ABER) is analytically evaluated by using the derived pdfs in the presence of random relay jamming effects. In presence of jammer, an approximate and simple expression of a threshold-based detector is obtained. By studying the ABER performance comparison, it is shown that the proposed approximate detector works satisfactorily compared to the maximum-likelihood detector in presence of random relay jammers. In addition to that, ABER performance of a general relay FSO system with an arbitrary number of relays is also obtained.

Sparse vector coding (SVC) is emerging as a key enabler for short packet ultra-reliable and low latency communications (URLLC), since it displays good block error rate (BLER) performance and can achieve low transmission latency. In this paper, we propose a SVC-based sparse superimposed transmission (SVC-ST) coding scheme to further enhance the BLER performance of SVC scheme. At the encoding side, a portion of transmission bits is represented by non-zero position indices of sparse vector. The remaining bits are equally split into multiple streams and then mapped into the non-zero positions of sparse vector via quadrature amplitude modulation (QAM) with constellation rotation (CR). We afterwards adopt the multipath matching pursuit-based soft decoding (MMP-SD) to recover the transmission packet. The BLER and bit error rate (BER) analysis of SVC-ST scheme demonstrate the validity and rationality of our study. Moreover, we find from the simulation results that the proposed SVC-ST scheme outperforms SVC and its enhanced version (ESVC) schemes in terms of BLER and latency performance.

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.

In this paper, we investigate the grant-free communications with adaptive period for industrial Internet of Things, where only a fraction of devices are active at a time. To the best of our knowledge, this is the first work to exploit the non-continuous temporal correlation of the received signal for joint user activity detection (UAD), channel estimation and signal detection, while all the previous work requires continuous transmission. Two schemes are proposed toward this purpose, namely periodic block orthogonal matching pursuit (PBOMP) and periodic block sparse Bayesian learning (PBSBL), which outperform the previous schemes in terms of the success rate of UAD, bit error rate and accuracy in period estimation and channel estimation. The CramC)r-Rao lower bounds (CRLBs) of channel estimation by PBOMP and PBSBL are derived. It is shown that the two proposed approaches have close CRLBs and normalized mean square error at high SNR.

We present a silicon photonic based stacked die assembly (SDA) compatible with the commercial complementary metal-oxide-semiconductor process. The SDA consists of a driver die and a transimpedance amplifier die, both populated onto a photonic integrated circuit die with a dimension of 5mm9mm. The SDA is designed to be an O-band optical engine for a 4200-Gbit/s parallel single-mode fiber short-reach transmission system. Performance of several pulse amplitude modulation (PAM) formats are evaluated and compared for the feasibility of 200-Gbit/s transmission. Aided by a Volterra nonlinear equalizer, the system experiment demonstrated that PAM-8 is a promising candidate for single lane 200-Gbit/s transmission with achieved bit error rate (BER) floor of 1.410-3. Instead of using costly optical amplifier, the system relies on the transimpedance amplifier on the SDA to boost up receiver sensitivity, which is shown to be -2.6dBm and -2.0dBm for 2-km and 10.5-km fiber transmissions respectively. The system impairments and noise sources are quantitatively discussed to facilitate further hardware improvement. We believe this is the first demonstration of net 200-Gbit/s transmission over 10km without optical amplification, accomplished with silicon photonic integrated circuit and offline processing.

The growing interests in Internet of Underwater Things (IoUT) put forward more demands for underwater acoustic (UWA) communication technologies. However, the conventional orthogonal frequency division multiplexing (OFDM) technology underperforms in terms of the resistance to carrier frequency offset (CFO), symbol time offset (STO), and applicability to multiple application scenarios. To remedy the deficiencies, this paper introduces the emerging universal filtered multi-carrier (UFMC) technology into UWA communications and devises a two-stage index modulated UFMC (TSIM-UFMC) system for performance improvement. In addition, a deep learning-aided signal detector termed as TSIMNet is proposed for the TSIM-UFMC system over multipath UWA channels. Specifically, at the transmitter, the TSIM-UFMC system adopts two-stage index modulation to characterize the different position information of data, pilot, and inactive subcarriers in each subblock for ameliorating the bit error rate (BER) performance under channel interferences. At the receiver, the TSIMNet detector exploits configurable deep neural networks to encapsulate the index demodulation, channel estimation, and constellation demodulation for optimizing the system structure. Furthermore, TSIMNet can be deployed to detect the received signal online for the TSIM-UFMC system after trained by offline data. Numerical results reveal that the proposed TSIM-UFMC system exhibits achievable advantages in combating CFO and STO, and the TSIMNet detector actualizes a near-optimal performance on BER with preferable computational complexity.

A digital clock/data recovery (CDR) circuit with a one-tap speculative decision feedback equalizer (DFE) and a calibration circuit is presented. This CDR circuit is fabricated in 40-nm CMOS technology and its active area is 0.1 mm2. For a channel loss of -10.31dB at 10GHz and a 20Gb/s PRBS of 27-1, the measured bit error rate is less than 10-12. By the proposed calibration circuit, the measured high-frequency jitter tolerance is improved. The measured convergence time of the calibration circuit is less than 5μs. The power of this CDR circuit is 55.4mW at 20 Gb/s, and the calculated energy efficiency is 2.77pJ/b.

In order to expand the application of differential chaos shift keying (DCSK) technology in Internet of Things, a novel ambient backscatter communication system is proposed. In this system, the ambient short reference DCSK (SR-DCSK) signal is ultilized as radio frequency (RF) source, and the modulation waveform design can be easily generated by the state transition of the SR-DCSK modulation symbol according to the transmitted information bit, so as to eliminate strong direct-link interference. Furthermore, a noise reduction method based on averaging operation at the detector is designed for enhancing the bit error rate (BER) performance. Theoretical BER expression over Rayleigh fading channel is derived and validated via simulation. Moreover, the performance of the proposed system is compared with those of other DCSK-based systems.

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 work, we implement a complete probabilistic amplitude shaping (PAS) architecture on a field-programmable gate array (FPGA) platform to study the interplay between probabilistic shaping (PS) and forward error correction (FEC). Due to the fully parallelized inputoutput interfaces based on look up table (LUT) and low computational complexity without high-precision multiplication, hierarchical distribution matching (HiDM) is chosen as the solution for real time probabilistic shaping. In terms of FEC, we select two kinds of the mainstream soft decision-forward error correction (SD-FEC) algorithms currently used in optical communication system, namely Open FEC (OFEC) and soft-decision quasi-cyclic low-density parity-check (SD-QC-LDPC) codes. Through FPGA experimental investigation, we studied the impact of probabilistic shaping on OFEC and LDPC, respectively, based on PS-16QAM under moderate shaping, and also the impact of probabilistic shaping on LDPC code based on PS-64QAM under weak/strong shaping. The FPGA experimental results show that if pre-FEC bit error rate (BER) is used as the predictor, moderate shaping induces no degradation on the OFEC performance, while strong shaping slightly degrades the error correction performance of LDPC. Nevertheless, there is no error floor when the output BER is around 10-15. However, if normalized generalized mutual information (NGMI) is selected as the predictor, the performance degradation of LDPC will become insignificant, which means pre-FEC BER may not a good predictor for LDPC in probabilistic shaping scenario. We also studied the impact of residual errors after FEC decoding on HiDM. The FPGA experimental results show that the increased BER after HiDM decoding is within 10 times compared to post-FEC BER.

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.

This paper presents a four-level pulse amplitude modulation (PAM-4) receiver that incorporates a continuous time linear equalizer, a variable gain amplifier, a phase interpolator-based clock and data recovery, and a 4-tap direct decision feedback equalizer (DFE) for moderate channel loss applications in wireline communication. A dynamic current-mode logic comparator (DCMLC) is proposed and employed in the DFE. The DCMLC, which adopts dynamic logic, breaks the trade-off between the bandwidth and the clock to Q delay in the traditional current-mode logic comparator (CMLC). Compared with the traditional CMLC, the DCMLC reduces the clock to Q delay by 36%, which allows the implementation of a 4-tap direct DFE. Moreover, the first tap feedback signals are directly tapped from the output of the DCMLC, allowing the first tap feedback current to initiate 0.5UI before the decision clock. The PAM-4 receiver prototype is fabricated in a 65nm CMOS process. At a data rate of 56-Gbps, it can compensate for up to 20.17dB loss and achieve a bit error rate < 1E-10 with a power efficiency of 4.75 pJ/bit.

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.

Filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) is a promising candidate for 5G mobile fronthaul system. Due to the inherent imaginary interference of FBMC/OQAM signals, an accurate channel estimation is particularly indispensable. In this paper, an efficient method is proposed based on complex-valued neural networks (CVNN) for an accurate channel estimation of FBMC/OQAM signals with low computational complexity and pilot overhead. Here, the channel frequency response (CFR) is first calculated for training the CVNN. Next, the CFR estimated from the extracted pilots is exploited as the input of the trained CVNN to yield the CFR of data symbols. We experimentally demonstrate a 12.5-GBd intensity modulation direct detection (IM/DD) FBMC/OQAM transmission system over 30-km and 50-km standard single mode fibers (SSMF). The experimental results show that the proposed method achieves 3-dB and 1-dB receiver sensitivity improvement at the bit error ratio (BER) of 3.810-3 with only 5% pilot overhead respectively, compared to the conventional least square (LS) and linear minimum mean error (LMMSE) methods. When the pilot overhead decreases from 10% to 1%, its BER performance is always better than LS and LMMSE. For the computational complexity, its complexity is the same order of magnitude as LS and lower than LMMSE. On the other hand, the CVNN requires less hidden neurons to keep the similar BER performance as real-valued neural networks (RVNN). Meanwhile, it has excellent resilience to fiber chromatic dispersion over 30-km and 50-km SSMF.

We investigate the performance of a dual-hop mixed radio frequency (RF)/free space optical (FSO) system with variable-gain relaying. The RF link is modeled by the κ-μ shadowed distribution, which unifies popular RF channel models. The FSO link is subject to atmospheric turbulence with non-zero boresight pointing errors. The atmospheric turbulence channel is modeled by the Fisher-Snedecor 𝓕 distribution, which fits well with the measurement data under weak-to-strong turbulence conditions. The pointing error is modeled by the Beckmann distribution, which includes popular pointing error models. We propose an approximation method to approximate the κ-μ shadowed distribution using an α-μ distribution, which is more accurate than that using a gamma distribution in the existing literatures. Then, we derive closed-form expressions for the probability density function (PDF) and the cumulative distribution function (CDF) for the irradiance fluctuations. Based on these expressions, we derive closed-form approximate expressions for the CDF, the PDF, the moment generating function (MGF), the average bit error rate (BER), and the ergodic capacity (EC) of the considered system in terms of the bivariate Fox's H function. Furthermore, asymptotic expressions for the CDF and the average BER at high signal-to-noise ratio (SNR) are derived in terms of simple elementary functions. Finally, numerical results and Monte Carlo (MC) simulations are provided to verify the derived approximate expressions.

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.

This letter presents a new approach to construct space-time block codes (STBCs) based on the Kronecker product. The proposed Kronecker-structured STBCs (K-STBCs) are specially designed for constant modulus constellations and include the classical linear dispersion (LD) codes as a special case. Its inherent Kronecker structure offers additional coding gains due to the mutual spreading of multiple space-time codewords. At the receiver, an efficient algorithm is derived by recasting the decoding of the K-STBCs as a rank-one tensor approximation problem. The proposed decoding algorithm provides a good bit error ratio (BER) performance especially, in the low signal-to-noise ratio (SNR) regime. In particular, our numerical results show that K-STBCs outperform the existing quasi-orthogonal STBCs due to the denoising gain offered by the proposed rank-one approximation based detector.

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.

This brief discusses the limitation of previously published statistical decision feedback equalizer (DFE) models when residual inter-symbol interference (ISI) is present and proposes a method that overcomes this limitation. The paper presents an accurate closed-form expression for the DFE with residual ISI and additive white Gaussian noise (AWGN). The analysis is extended to 4-level pulse amplitude modulation (PAM-4) to cover serial links of current interest. The results verify that the proposed model estimates an accurate bit error rate (BER).

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 paper, we propose a pre-coded multi-carrier M-ary chaotic vector cyclic shift keying (PC-MC-M-CVCSK) transceiver for reliable information transmissions. In this design, we exploit the principle of diagonalization to combat noises and interferences. At the PC-MC-M-CVCSK transmitter, we propose to precode the M-ary modulated symbols based on the discrete Fourier transform (DFT) and the reverse matrix of an eigenvalue matrix. Meanwhile, the chaotic generator outputs chaotic sequences, which are then cyclicly shifted and used to modulate precoded symbols. At the receiver, reverse operations are conducted to recover the data. Moreover, we prove that a circulant matrix can be constructed by selecting the cyclic shift length, while the DFT aided processing will diagonalize the circulant matrix. Thanks to the diagonalization design, the inner product of information-bearing chaotic vectors becomes zero, thus signals can be orthogonalized to suppress interferences. Furthermore, theoretical performances of the proposed transceiver, including the bit error rate (BER), the symbol rate, the energy efficiency and the spectrum efficiency, and the computational complexity are analyzed. Simulation results validate the exact analysis. Furthermore, the results demonstrate that the proposed PC-MC-M-CVCSK system outperforms the counterpart schemes, which can provide M-ary high symbol rate transmission services with enhanced reliability performances.

Visible light communication (VLC) has been recognized as a promising technology for handling the continuously increasing quality of service and connectivity requirements in modern wireless communications, particularly in indoor scenarios. In this context, the present work considers the integration of two distinct modulation schemes, namely spatial modulation (SM) with space time block codes (STBCs), aiming at improving the overall VLC system reliability. Based on this and in order to further enhance the achievable transmission data rate, we integrate quasi-orthogonal STBC (QOSTBC) with SM, since relaxing the orthogonality condition of OSTBC ultimately provides a higher coding rate. Then, we generalize the developed results to any number of active light-emitting diodes (LEDs) and any $M$-ary pulse amplitude modulation size. Furthermore, we derive a tight and tractable upper bound for the corresponding bit error rate (BER) by considering a simple two-step decoding procedure to detect the indices of the transmitting LEDs and then decode the signal domain symbols. Notably, the obtained results demonstrate that QOSTBC with SM enhances the achievable BER compared to SM with repetition coding (RC-SM). Finally, we compare STBC-SM with both multiple active SM (MASM) and RC-SM in terms of the achievable BER and overall data rate, which further justifies the usefulness of the proposed scheme.

Voronoi constellations (VCs) are finite sets of vectors of a coding lattice enclosed by the translated Voronoi region of a shaping lattice, which is a sublattice of the coding lattice. In conventional VCs, the shaping lattice is a scaled-up version of the coding lattice. In this paper, we design low-complexity VCs with a cubic coding lattice of up to 32 dimensions, in which pseudo-Gray labeling is applied to minimize the bit error rate. The designed VCs have considerable shaping gains of up to 1.03 dB and finer choices of spectral efficiencies in practice. A mutual information estimation method and a log-likelihood approximation method based on importance sampling for very large constellations are proposed and applied to the designed VCs. With error-control coding, the proposed VCs can have higher achievable information rates than the conventional scaled VCs because of their inherently good pseudo-Gray labeling feature, with a lower decoding complexity., Comment: 10 pages, 6 figures

This paper introduces a new burst-mode coherent receiver configuration that drastically widens the receiver input dynamic range. Its key advance is a fast feed forward gain control scheme for both a semiconductor optical amplifier (SOA) used as a preamplifier and trans-impedance amplifiers (TIAs) set at the coherent receiver. The two-stage optical and electrical gain control greatly decreases the received burst signals power variations and increases the receiver dynamic range which attenuates the quantization errors in analogue-to-digital conversion (ADC). To elucidate the receiver sensitivity characteristics, bit error rate (BER) calculations are conducted on 10 Gbit/s single polarization quadrature phase shift keying (SP-QPSK) signal coherent reception. The calculations focus on two significant parameters that greatly impact the quantization noise; ADC vertical resolution and received signals state of polarization (SOP). The calculation results confirm that the proposed configuration achieves high sensitivity, better than -44 dBm, and wide dynamic range of 30 dB in the worst SOP condition, even when 5-bit ADC is used. Transmission experiments verify the calculated sensitivities and extremely high loss budget of 48.6 dB is achieved in 40-km single mode fiber (SMF) transmission. These results show that the proposal has the potential to realize 10 Gbit/s class long-reach and high splitting ratio PONs; the extremely wide dynamic range yields 40 km reach PON systems with 512- or 1024-way splits with no change in receiver configuration.

This article presents design techniques for a continuous-rate reference-free clock and data recovery (CDR) circuit employing a stochastic frequency-phase detector (SFPD). By taking a histogram-based design methodology, optimal weights for both frequency and phase detection are obtained by utilizing the same information as the Alexander phase detector. The design methodology is inductive and stochastic, distinguished from the conventional, deductive, and procedural methods. To verify a robust operation, the effects of varied data patterns, noise, and channel loss are examined, together with the avoidance of harmonic locking. In addition, a consideration of a sample window is analyzed by fast Fourier transform (FFT) simulation. Fabricated in 40-nm low-power (LP) CMOS technology, the proposed CDR circuit achieves a capture range from 6.4 to 32 Gb/s and a lock time of less than 11 μs. The measured frequency acquisition behavior shows that harmonic locking is avoided with a seamless transition to the fundamental mode. The CDR circuit tested over a 10-dB loss channel achieves a bit error rate (BER) less than 10⁻¹² and energy efficiency of 0.96 pJ/b.

Spectrum sharing backscatter communication systems are among the most prominent technologies for ultra-low power and spectrum efficient communications. In this paper, we propose an underlay spectrum sharing backscatter communication system, in which the secondary network is a backscatter communication system. We analyze the performance of the secondary network under a transmit power adaption strategy at the secondary transmitter, which guarantees that the interference caused by the secondary network to the primary receiver is below a predetermined threshold. We first derive a novel analytical expression for the cumulative distribution function (CDF) of the instantaneous signal-to-noise ratio of the secondary network. Capitalizing on the obtained CDF, we derive novel accurate approximate expressions for the ergodic capacity, effective capacity and average bit error rate. We further validate our theoretical analysis using extensive Monte Carlo simulations.

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.

Deep learning-aided optical orthogonal frequency division multiplexing (O-OFDM) is proposed for intensity modulated direct detection transmissions, which is termed as O-OFDMNet. In particular, O-OFDMNet employs deep neural networks (DNNs) for converting a complex-valued signal into a non-negative signal in the time-domain at the transmitter and vice versa at the receiver. The associated frequency-domain signal processing remains the same as in conventional radio frequency (RF) OFDM. As a result, our scheme achieves the same spectral efficiency as the RF scheme, which has never been attained by the existing O-OFDM schemes, because they have relied on the Hermitian symmetry of the spectral-domain signal to guarantee that the time-domain signal becomes real-valued. We show that O-OFDMNet can be viewed as an autoencoder architecture, which can be trained in an end-to-end manner in order to simultaneously improve both the bit error ratio (BER) and the peak-to-average power ratio (PAPR) for transmission over both additive white Gaussian noise and frequency-selective channels. Furthermore, we intrinsically integrate a soft-decision aided channel decoder with our O-OFDMNet and investigate its coded performance relying on both convolutional and polar codes. The simulation results show that our scheme improves both the uncoded and coded BER as well as a reducing the PAPR compared to the benchmarks at the cost of a moderate additional DNN complexity. Furthermore, our scheme is capable of approaching the throughput of RF-OFDM, which is notably higher than that of conventional O-OFDM. Finally, our complexity analysis shows that O-OFDMNet is suitable for real-time operation.

Digital predistortion (DPD) technique is an effective means to alleviate the nonlinearity of power amplifiers (PAs) and improve transmitter efficiency. However, for orthogonal frequency division multiplexing (OFDM) systems with a high peak-to-average power ratio (PAPR), the PAPR reduction needs to be deployed in combination with DPD, to maximize transmitter efficiency. The extra complexity caused by the introduction of PAPR reduction on the main road has become a non-negligible defect. To address this issue, this letter proposes a joint PAPR reduction and DPD model based on the generalized memory polynomial (GMP). To train the joint GMP model, this letter improves the ping-pong joint optimization (P2JO) approach under the offline case, to obtain accurate training data. The comparative experimental results based on 100-MHz Doherty PA show that the proposed joint model significantly reduces the model complexity on the main road, while ensuring adjacent channel power ratio (ACPR) and bit error rate (BER).

Bit error rate (BER) is an important figure of merit to evaluate the performance of a communication system. Analyzing the BER of a linear-time-invariant system has been extensively studied. However, analyzing the BER of nonlinear circuits and systems is challenging because it cannot rely on linear time invariant (LTI) principles, while an exhaustive nonlinear simulation is computationally prohibitive. To find BER, an exhaustive approach requires nonlinear simulations of $2^m$ bit patterns for a channel of m-bit memory, where m can be larger than 100 in today's high-speed and high-performance design. In this work, we develop a fast and accurate method to analyze the BER of large-scale nonlinear circuits. Only O(k) nonlinear simulations are required, with k much less than 2^m and independent of $2^m$ . While performing O(k) nonlinear simulations only, we find a method to determine the probability density function of the nonlinear responses, from which accurate BER results can be obtained. An error assessment method is also developed to evaluate the true error of the nonlinear signaling analysis without the need for knowing the entire nonlinear responses of the channel. Simulations of large-scale real-world nonlinear circuits have demonstrated the accuracy, efficiency, and capacity of the proposed method. A BER as low as $10^{-56}$ is accurately predicted.