Harmonic Transfer Function Based Single-input Single-output Impedance Modeling of LCC-HVDC Systems

This study presents a harmonic transfer function(HTF)based single-input single-output(SISO)impedance modeling method.The method converts an HTF from phase domain to sequence domain and then transforms it into an SISO impedance while preserving the frequency coupling information of different sequences and different harmonics.Applications of this method to a line-commutated converter based high-voltage direct current(LCC-HVDC)system are presented.The results demonstrate the accuracy of the derived SISO impedance,and a truncation-order selection is suggested.The case study shows that the proposed method facilitates simpler impedance measurements and associated stability analysis.

Study on Performance of Wireless Multihop Networks Using MIMO MRC and MIMO MRT

This paper presents the concepts of completely connected network,mean path length and cluster for analysis performance of wireless multihop network,where matrix are used to express topology of network and use a new algorithm to compute the number of cluster in the network.Multiple-input/multiple-output(MIMO) communication promises performance enhancement over conventional single-input/single-output(SISO) technology for the same radiated power,if leveraged in multihop network,MIMO may be able to provide significant network performance improvement in network robustness and in power consumption,this paper analyzes three types of multihop networks employing SISO, MIMO with maximum ratio combining(MRC) and MIMO with maximum ratio transmission(MRT) as link model respectively,and get that using MIMO link model can increase robust,decrease mean path length by simulation.

High Speed Digital Oscillator Implementations Based on Advanced Arithmetic and Architecture Techniques

The advances of digital arithmetic techniques permit computer designers to implement high speed application specific chips. The currently produced digital circuits have demonstrated high performance in terms of several criteria, such as, high clock rate, short input/output delay, small silicon area, and low power dissipation. In this paper, we implement several sinusoidal generation methods to optimize their performance and output using advanced digital arithmetic techniques. In this paper, the implementations of advanced digital oscillator structures with and without pipelining are proposed. The synthesis results of the implementation with pipelining have proven that it is superior to other sinusoidal generation methods in terms of the maximum frequency and signal resolution. Hence, this method is used in the design of the proposed digital oscillator chip.

ERGODIC CAPACITY ANALYSIS FOR SIMO COGNITIVE FADING CHANNEL IN SPECTRUM SHARING ENVIRONMENT

In this paper,we consider the spectrum sharing Cognitive Radio(CR) system,wherein Single-Input Multi-Output(SIMO) cognitive fading channel is assumed.Subject to the average in-terference constraint of primary user,the ergodic capacity of cognitive user involving joint beamforming and power control is analyzed.We derive the optimal joint beamforming and power control strategy and deduce the general integral expression for ergodic capacity.Furthermore,under different channel fadings including Raleigh fading,Nakagami-m fading and Lognormal shadowing fading,the specific expressions of ergodic capacity for SIMO cognitive channel are exhibited.Most of the expressions are presented in closed-form or with some special integral functions.Large amount of simulations are conducted to corroborate our theoretical results.

Blind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems

A blind adaptive scheme is proposed for joint maximum likelihood （ML） channel estimation and data detection of singleinput multiple-output （SIMO） systems. The joint ML optimisation over channel and data is decomposed into an iterative optimisation loop. An efficient global optimisation algorithm called the repeated weighted boosting search is employed at the upper level to optimally identify the unknown SIMO channel model, and the Viterbi algorithm is used at the lower level to produce the maximum likelihood sequence estimation of the unknown data sequence. A simulation example is used to demonstrate the effectiveness of this joint ML optimisation scheme for blind adaptive SIMO systems.

Distributed Multi-Cell Multi-User MISO Downlink Beamforming via Deep Reinforcement Learning

The sum rate maximization beamforming problem for a multi-cell multi-user multiple-input single-output interference channel(MISO-IC)system is considered.Conventionally,the centralized and distributed beamforming solutions to the MISO-IC system have high computational complexity and bear a heavy burden of channel state information exchange between base stations(BSs),which becomes even much worse in a large-scale antenna system.To address this,we propose a distributed deep reinforcement learning(DRL)based approach with lim⁃ited information exchange.Specifically,the original beamforming problem is decomposed of the problems of beam direction design and power allocation and the costs of information exchange between BSs are significantly reduced.In particular,each BS is provided with an inde⁃pendent deep deterministic policy gradient network that can learn to choose the beam direction scheme and simultaneously allocate power to users.Simulation results illustrate that the proposed DRL-based approach has comparable sum rate performance with much less information exchange over the conventional distributed beamforming solutions.

Recovery of Image through Alamouti Channel with Incorporation of RSA Algorithm

In many applications, it is necessary to transmit images at a remote station, where wired Internet service is not available. In this case, wireless local loop (WLL) can help in making wireless link between one end node of the internet and remote service center. In such link, the communication is heavily affected by large and small scale fading;hence the received signal experiences huge distortion in case of forward error correction. Otherwise, huge service delay arises due to frequent negative acknowledgements. To combat the situation, we can choose Alamouti channel of full rate and fully orthogonal space-time block code (OSTBC). Our aim is to transmit images through Alamouti channel and to observe the quality of the recovered image, in context of bit error rate (BER). We have also observed the impact of fading and additive white Gaussian noise (AWGN) on the image without application of error correction or detection technique of channel coding. To ensure security, we apply the RSA algorithm on each pixel prior transmitting and decrypt them at the receiving end, where we found no impairment from the algorithm. Finally, we observe that the relative performance of the system changes digital modulation schemes.

Ergodic secrecy capacity of MRC/SC in single-input multiple-output wiretap systems with imperfect channel state information

This paper investigates the secrecy performance of maximal ratio combining （MRC） and selection combining （SC） with imperfect channel state information （CSI） in the physical layer. In a single-input multiple- output （SIMO） wiretap channel, a source transmits confidential messages to the destination equipped with M antennas using the MRC/SC scheme to process the received multiple signals. An eavesdropper equipped with N antennas also adopts the MRC/SC scheme to promote successful eavesdropping. We derive the exact and asymptotic closed-form expressions for the ergodic secrecy capacity （ESC） in two cases： （1） MRC with weighting errors, and （2） SC with outdated CSI. Moreover, two important indicators, namely high signal-to-noise ratio （SNR） slope and high SNR power offset, which govern ESC at the high SNR region, are derived. Finally, simulations are conducted to validate the accuracy of our proposed analytical models. Results indicate that ESC rises with the increase of the number of antennas and the received SNR at the destination, and fades with the increase of those at the eavesdropper. Another finding is that the high SNR slope is constant, while the high SNR power offset is correlated with the number of antennas at both the destination and the eavesdropper.

Visible light communication for Vehicle to Everything beyond 1 Gb/s based on an LED car headlight and a 2 × 2 PIN array

Visible light communication(VLC) shows great potential in Internet of Vehicle applications. A single-input multi-output VLC system for Vehicle to Everything is proposed and demonstrated. A commercial car headlight is used as transmitter. With a self-designed 2 × 2 positive-intrinsic-negative(PIN) array, four independent signals are received and equalized by deep-neural-network post-equalizers, respectively. Maximum-ratio combining brings high signal-to-noise ratio and data rate gain. The transmission data rate reaches 1.25 Gb/s at 1 m and exceeds 1 Gb/s at 4 m. To the best of our knowledge, it is the first-time demonstration of beyond 1 Gb/s employing a commercial car headlight.

Nonlinear coded nonuniform superposition QAM by trellis-coding for MISO system in visible light communication

In this paper,we propose a 36-quadrature amplitude modulation(QAM)superposition modulation technique that is featured with uneven symbol probability by nonlinear precoding,named nonlinear coded nonuniform superposition(NCNS)QAM.Its aim is to alleviate the nonlinearity effect caused by high instantaneous power in multi-input single-output(MISO)visible light communication(VLC)system,with an uneven probabilistic-shaped constellation.The transmitter includes two LEDs to send signals independently,and the receiver uses a photo detector to receive the superposed QAM signal.The experiment results show that NCNS has a better robustness against nonlinearity than pulse amplitude modulation 4,approximately gaining a 16% increase in maximum usable peak-to-peak voltage and a 33% enlargement in dynamic range area.It is a simple but effective approach to solve the bandwidth limits related to signal power and hopefully be applied in large power VLC systems such as underwater VLC,or to improve the robustness against power fluctuation.

Capacity of orthogonal space-time block codes in MISO fading channels with co-channel interference and noise

Orthogonal space-time block codes （OSTBCs） are an efficient mean in order to exploit the diversity offered by the wireless multiple-input multiple-output （MIMO） channel. This paper considers capacity problems of OSTBCs over spatially correlated multiple-input single-out （MISO） Rayleigh fading channels in the presence of spatially correlated Rayleigh co-channel interference and additive Gaussian noise, and derives exact expressions of the ergodic capacity and outage probability （capacity distribution） for such OSTBCs. Some numerical examples are given to illustrate the effect of co-channel interference on the ergodic and outage capacity of OSTBCs.

State Observer Based Dynamic Fuzzy Logic System for a Class of SISO Nonlinear Systems

This paper presents an observer based dynamic fuzzy logic system （DFLS） scheme for a class of unknown single-input single-output （SISO） nonlinear dynamic systems with external disturbances. The proposed approach does not need the availability of the state variables. Within this scheme, the DFLS is employed to identify the unknown nonlinear dynamic system. The control law and parameter adaptation laws of the DFLS are derived based on Lyapunov synthesis approach. The control law is robustfied in H∞ sense to attenuate external disturbance, model uncertainties, and fuzzy approximation errors. It is shown that under appropriate assumptions, it guarantees the boundedness of all the signals in the closed-loop system and the asymptotic convergence to zero of tracking errors. The proposed method is applied to an inverted pendulum system to verify the effectiveness of the proposed algorithms.

Design of Energy Modulation Massive SIMO Transceivers via Machine Learning

This paper considers a massive single-input multiple-output(SIMO)system,where multiple singleantenna transmitters simultaneously communicate with a receiver equipped with a large number of antennas.Different from the conventional noncoherent transceivers which require a certain level of the statistical information on the channel fading,we propose a joint transceiver design method based on machine learning,requiring a limited number of channel realizations.In the proposed method,the multiple transmitters,the channel,and the receiver are represented with a deep neural network(NN),and an autoencoder is adopted to minimize the end-to-end transmission error probability.Besides,the relationship between the number of training samples and the transmission error probability is analyzed based on the confidence interval method.Simulation results show that the proposed NN-based transceiver achieves lower transmission error probability in typical scenarios,and is more robust against the channel parameters variation compared with the existing methods.

Developing a Super-lift Luo-converter with Integration of Buck Converters for Electric Vehicle Applications

In this paper,a DC-DC multi-port converter is introduced by integrating a super-lift and a buck converter(SLBC).The proposed single-input dual-output(SIDO)converter has conventional positive output voltage super-lift advantages while simultaneously generating a step・up voltage by Luo・converter and a step-down voltage by the buck converter.In this structure,without utilizing electromagnetic components to generate a dual output,the ripple in output voltages is kept low.Meanwhile,the introduced SLBC has a simple structure and an appropriate control method providing a wide range of output voltages.Besides,to illustrate the advantages of the proposed SIDO converter,a comparison with other similar configurations is carried out.Also,simulation and experiment results indicate a considerable reduction in conduction losses compared to other SIDO converters in the same situations.The operation accuracy of SLBC is validated by performing several simulations in PSCAD/EMTDC software and testing a 150W prototype in the laboratory.

Robust Precoding Schemes for Multi-User MISO-OFDM Downlink with Limited Time-Domain Feedback

In multi-user multiple-input single-output orthogonal frequency-division multiplexing （MISO-OFDM） downlinks with limited feedback, both linear precoders （LP） and Tomlinson-Harashima precoders （THP） experience performance degradation due to inaccurate channel state information at the transmitter （CSIT）. This analysis treats the downlink channels as random quantities and exploits their second order statistics in robust precoding schemes to correct the errors introduced in the feedback procedure. The time-domain channel vectors are found to reduce the feedback overhead more than the frequency-domain vectors. A compression and restoration method and a codebook design are also given to obtain compact feedback quantities. Simulations show that the robust LP and THP are superior to the previous methods with tradeoffs possible between performance and feedback overhead.

Physical layer security of underlay cognitive radio using maximal ratio combining

We investigate the secrecy outage performance of maximal ratio combining(MRC) in cognitive radio networks over Rayleigh fading channels. In a single-input multiple-output wiretap system, we consider a secondary user(SU-TX) that transmits confidential messages to another secondary user(SU-RX) equipped with M(M ≥ 1)antennas where the MRC technique is adopted to improve its received signal-to-noise ratio. Meanwhile, an eavesdropper equipped with N(N ≥ 1) antennas adopts the MRC scheme to overhear the information between SU-TX and SU-RX. SU-TX adopts the underlay strategy to guarantee the service quality of the primary user without spectrum sensing. We derive the closed-form expressions for an exact and asymptotic secrecy outage probability.