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In order to improve the accuracy of signal recovery after transmitting over atmospheric turbulence channel, a deep-learning-based signal detection method is proposed for a faster-than-Nyquist (FTN) hybrid modulated optical wireless communication (OWC) system. It takes advantage of the long short-term memory (LSTM) network in the recurrent neural network (RNN) to alleviate the interdependence problem of adjacent symbols. Moreover, an LSTM attention decoder is constructed by employing the attention mechanism, which can alleviate the shortcomings in conventional LSTM. The simulation results show that the bit error rate (BER) performance of the proposed LSTM attention neural network is 1 dB better than that of the back propagation (BP) neural network and outperforms by 2.5 dB when compared with the maximum likelihood sequence estimation (MLSE) detection method.

Non-orthogonal multiple access (NOMA) has very high spectral efficiency and system capacity. NOMA has become one of the most competitive access solutions in 5G systems. In this article, the principle of NOMA is discussed first. Then, the NOMA system capacity optimisation problems are studied. Signal to interference plus noise ratio (SINR) is an important factor which affects the system capacity. The SINR of current user n is only related to the power allocated to users n+1 to N with high signal-to-noise ratio (SNR) but not interfered by users with low SNR. Therefore, a tree topology power allocation (TTPA) algorithm is introduced. When users are allocated to each layer of the tree structure, the current power allocation of each layer will not be affected by the previous layer. Through theoretical analysis, TTPA can achieve the same performance as the full search power allocation algorithm; however, its computational complexity is reduced from exponential to constant. It can be seen from the numerical simulation results that the proposed algorithm can achieve higher system capacity and has lower computational complexity.

In this letter, an adaptive symbol decomposition with serial transmission (ASDST) scheme is proposed to reduce the effect of non-linear clipping noise for optical orthogonal frequency division multiplexing (O-OFDM) system in visible light communication. The transmitted O-OFDM symbol is adaptively decomposed by amplitude clipping and the decomposed symbols are fed into single light emitting diode (LED) by using serial framing. Adaptive symbol decomposition is the process of repeating the amplitude clipping according to each decomposition symbol amplitude and clipping levels. The simulation results show that the ASDST scheme offers improved transmission performance compared with conventional iterative signal clipping (ISC) scheme, since it eliminates all-zero symbols and transmits the same information with fewer decomposition symbols.

The impact of the traffic characteristics of secondary users (SUs) on the performance of cognitive radio networks (CRNs) should be understood for designing operation rules. This paper focuses on multi-type burst services and network congestion problem in CRNs and evaluates the QoS of SUs based on multiple cross-layer considerations. A two-state Markov-modulate Bernoulli process (MMBP-2) is adopted to model packet flows of SUs with different burst degrees in CRNs. We propose a two-dimensional discrete queuing model to consider spectrum access, burstiness of traffic, network congestion, channel environment, user activity and finite buffer. We construct an iterative algorithm to compute the steady-state distribution of the proposed queuing model and determine the performance metrics like the throughput, the average delay, the average queue length and the total packet loss probability. Numerical analysis evaluates the QoS of SUs under different burst environments.

In this paper, we investigate the transceiver design schemes for the full-duplex (FD) multiple-input multipleoutput (MIMO) relay-assisted K -user single-input multipleoutput (SIMO) interference channels (ICs). Firstly, we propose an iterative optimized reference vector for IA (IORV-IA) algorithm in the perfect channel state information (CSI) scenario. The proposed IORV-IA algorithm not only achieves the alignment of interference signals at each receiver, but also iteratively optimizes the IA reference vector by orthogonalizing the directions of the interference signals and the desired signal. With the optimized IA reference vector, the relay processing matrix and the receiving filter vectors are designed to further improve the system performance. Considering that the relay cannot obtain perfect CSIs in practice due to many factors, and the performance of the IA scheme is very sensitive to this error. Furthermore, we propose a robust transceiver design scheme based on mean square error (MSE) in the imperfect CSI scenario, which minimizes the sum of MSEs in the worst case through iteration. The proposed algorithms are evaluated in terms of the average sum rate and bit error rate (BER) performance and the simulation results show the advantages of the proposed algorithms over existing centralized IA (CIA) and centralized zero-forcing (CZF) algorithms.

In this paper, an adaptive iterative symbol clipping scheme for OFDM-based visible light communication systems is proposed. This scheme can avoid the disadvantages of the conventional iterative signal clipping (ISC) scheme that produces all-zero symbols due to the fixed iterative clipping times, and also avoids the information transmission rate degradation due to an adaptive symbol decomposition with serial transmission (ASDST) scheme using serial transmission. In the proposal, optical orthogonal frequency division multiplexing (O-OFDM) symbols are decomposed into multiple O-OFDM symbols that are in the linear range of the LEDs after adaptive iterative clipping according to the signal amplitude and clipping threshold, thereafter simultaneously transmitted through multiple LEDs. When the number of LEDs is large enough, clipping distortion can be significantly reduced or even completely eliminated. In addition, the all-zero symbols existing in the ISC scheme can be completely eliminated. Experimental results show that the proposed scheme can not only improve the BER performance and the optical power efficiency, but also reduce the clipping times compared with the traditional ISC scheme. Besides,our proposed scheme could achieve higher information transmission rate compared with the ASDST scheme.

International audience; The core problem of cognitive radio networks is the accurate sensing and the efficient use of spectrum holes without interfering the communication of the primary system. This paper proposes a cooperative strategy with two full-duplex cognitive base stations (FDCBS) where in-band full-duplex technology and cognitive radio are integrated. If the primary channel is in the “busy” state, the FDCBS assist the primary system in the retransmission of the failed packet and receive the cognitive packets simultaneously. We derive the outage probability and the average spectral efficiency of the primary system and the cognitive system for two scenarios where the 2-state Discrete Markov Chain describes the primary system behaviour (2-SDMC) and a non-identically distributed Nakagami

In this paper, we present a precoding scheme of unitary space-time modulation (USTM) system considering that the fading channel is spatial-temporal correlated, which is a typical wireless communication scenario for high speed railway. The design of the precoder uses transmit correlation matrix of the channel, aiming at minimizing the mean-square error of channel estimation, where the receiver utilizes all of channel correlation information to the non-coherent detection method. Simulation results show that the proposed scheme can significantly outperform the non-coherent receiver without precoding.

The feasibility of rapid analysis of glucose and fructose in lotus root powder by Fourier transform near-infrared (FT-NIR) spectroscopy was studied. Diffuse reflectance spectra were collected between 4000 and 12,432cm(-1). Calibration models established by partial least-squares regression (PLSR), interval PLS of forward (FiPLS) and backward (BiPLS), back propagation-artificial neural networks (BP-ANN) and least squares-support vector machine (LS-SVM) were compared. The optimal models for glucose and fructose were obtained by LS-SVM with the first 10 latent variables (LVs) as input. For fructose the correlation coefficients of calibration (rc) and prediction (rp), the root-mean-square errors of calibration (RMSEC) and prediction (RMSEP), and the residual predictive deviation (RPD) were 0.9827, 0.9765, 0.107%, 0.115% and 4.599, respectively. For glucose the indexes were 0.9243, 0.8286, 0.543%, 0.812% and 1.785. The results indicate that NIR spectroscopy technique with LS-SVM offers effective quantitative capability for glucose and fructose in lotus root powder.

V-BLAST is a technology combined space multiplexing with space diversity. It has high spectrum efficiency, so, it is available to free space optical communication. In this paper, according to the characteristic of atmosphere channel, channel model in the free space optical communication is described, and the coding and decoding principle of V-BLAST fit for free space optical communication is proposed and its channel capacity was analyzed. Moreover, the V-BLAST channel capacity and error rate was compared to the system which did not use V-BLAST structure by emulation experiment. The result shows that when the number of receiver antenna is more than the number of transmit antenna, the channel capacity will be improved direct proportion with transmit antenna number, and the BER capability will be improved effectively. It has better performance to overcome the scintilla effect caused by atmospheric turbulence.

Nowadays, information technology is becoming more and more important to improve the productivity of agriculture, especially for real time environment monitoring. However, the traditional method of environmental data collection is unable to provide real-time and highly accurate data of the monitored region to meet the requirements of precision agriculture. As wireless sensor networks(WSNs) has profound impacts on many fields due to its promising capability, in this paper, a WSN-based environment monitoring system is proposed. A prototype of the system that utilizes GAINSJ nodes based on Zigbee communication protocol has been implemented, and its packet error rate in different conditions was evaluated. Based on the proposed system architecture and technologies, the real time data can be measured, transmitted and stored in high accuracy. Moreover, the system was applied in upland grassland in Yushu, Qinghai province, and compared the results with the data acquired by local weather station. The system evaluation and experimental results show the effectiveness and reliability of the system in measuring the variations of temperature and humidity data within monitored region.

For the sake of the quality of practice teaching, deepening the understanding of communication system. The paper firstly introduces EDA technology in the course of digital communication. Secondly, it uses examples to introduce the realization of C/A code by using MATLAB and analyze its performance. Finally, it compares the C/A codes generated by using MATLAB and Verilog-HDL to verify the correctness of implementation. In addition, the paper aims at making students understand the implementation of digital communication system, and know how to use MATLAB and EDA technology and cultivating students’ creativity and practice ability.