OFDM水声通信下行非正交多址接入功率分配方法研究

针对基于功率域非正交多址接入（Power Domain Non-orthogonal Multiple Accesses,PD-NOMA）的正交频分复用（Orthogonal Frequency Division Multiplexing,OFDM）水声下行通信系统的功率分配问题,提出了一种基于中断概率的功率分配方法。用户节点在系统初始化阶段根据源节点广播的组网数据包获取水声信道的统计特征,源节点根据水下用户反馈的信道特征参数建立水下用户的中断概率模型,以最小化两用户的中断概率和为目标建立目标函数,在中断概率区域边界上遍历搜索最优的功率分配系数。仿真结果表明,该方法在保证公平性的条件下,有效降低了用户节点的中断概率,提高了系统的频谱利用率和误码性能。     

主用户链路深度衰落下的认知网络中继

针对主用户链路经历深度衰落而发生通信中断的问题,提出了一种认知网络对主用户进行"透明"中继的方案。在不改变主用户通信协议的前提下,该方案首先感知主用户的状态,以判断其是否需要中继服务。当主用户通信发生中断时,认知网络利用从用户的能量检测器选出一个最优的节点解码转发主用户信号。从中断概率角度证明了这种最优单节点中继具有与多节点中继相同的空间分集作用,能够提高主用户平均传输效率,有较大的中继信道容量。通过仿真分析,验证了其分集效果和传输效率的提升。     

Performance of spatially multiplexed MC-CDM with zero-forcing unified successive interference cancellation detection

Spatially multiplexed multicarrier code-division multiplexing (SM-MC-CDM) is a multiple-input multiple-output, orthogonal frequency division multiplexing (MIMO-OFDM) communication technique with multiple antennas used for spatial multiplexing and with frequency domain spreading on each antenna. Unified successive interference canceller (U-SIC) is an efficient detector recently introduced for SM-MC-CDM. This paper presents an analytical approach to the performance of zero-forcing (ZF) U-SIC for SM-MC-CDM communications. For a system with an equal number of transmit and receive antennas, an approximation for the probability density function of post-detection signal-to-noise ratio (SNR) is used to derive a closed-form analytical upper bound and approximations for the probability of error and ergodic capacity. It is shown that SM-MC-CDM with ZF U-SIC is able to achieve higher diversity order than that achieved by ZF and minimum mean squared error (MMSE) V-BLAST detectors used on each subcarrier of a MIMO-OFDM system with the same number of subcarriers. The diversity order obtained increases with the number of subcarriers. It is also shown that the ergodic capacity of the system decreases with increasing number of subcarriers.     

Diffusion Based Channel Gains Estimation in WSN Using Fractional Order Strategies

In this study, it is proposed that the diffusion least mean square (LMS) algorithm can be improved by applying the fractional order signal processing methodologies. Application of Caputo’s fractional derivatives are considered in the optimization of cost function. It is suggested to derive a fractional order variant of the diffusion LMS algorithm. The applicability is tested for the estimation of channel parameters in a distributed environment consisting of randomly distributed sensors communicating through wireless medium. The topology of the network is selected such that a smaller number of nodes are informed. In the network, a random sleep strategy is followed to conserve the transmission power at the nodes. The proposed fractional order modified diffusion LMS algorithms are applied in the two configurations of combine-then-adapt and adapt-then-combine. The average squared error performance of the proposed algorithms along with its traditional counterparts are evaluated for the estimation of the Rayleigh channel parameters. A mathematical proof of convergence is provided showing that the addition of the nonlinear term resulting from fractional derivatives helps adjusts the autocorrelation matrix in such a way that the spread of its eigenvalues decreases. This increases the convergence as well as the steady state response even for the larger step sizes. Experimental results are shown for different number of nodes and fractional orders. The simulation results establish that the accuracy of the proposed scheme is far better than its classical counterparts, therefore, helps better solves the channel gains estimation problem in a distributed wireless environment. The algorithm has the potential to be applied in other applications related to learning and adaptation.     

Tomlinson-Harashima precoding with imperfect channel state information

Nonlinear Tomlinson-Harashima precoding (THP) is an attractive solution for a scenario where the transmission system employs multiple antennas at transmitter and multiple users with a single antenna at the receiver, so that the cooperation among the receive antennas are impossible (downlink scenario). THP solution based on zero forcing (ZF) and minimum mean square error (MMSE) criteria is one of the important techniques to achieve near multiple input multiple output channels capacity with reasonable complexity. In this paper, the effect of channel imperfection on THP is considered. At first, the achievable rate of THP with respect to ZF criterion in an imperfect channel state information (CSI) scenario is calculated. Moreover, based on MMSE criterion, a new robust solution is derived which provides a significant improvement with respect to the conventional optimisation method. Then, the effect of channel estimation error on THP is considered as an improved optimisation where THP filters are optimised together with a channel estimator. Spatial power loading is found to be important to the THP performance. This loading for robust/joint optimisation of MMSE THP is developed by minimum average symbol error rate sense. Simulation results show the capacity loss, the performance advantage attained by the robust/joint optimisation and the power loading in an imperfect CSI scenario.     

Antenna parameter effects on spatial channel models

The comparison of the outage capacity for multiple-input multiple-output (MIMO) channel models based on different underlying approaches is made. Three different channel models are considered: the 3GPP empirical spatial channel model (SCM), a multi-element transmit and receive antenna (METRA) analytical spatial channel model (A-SCM) and the correlation-based long-term evolution (LTE) channel model. The authors evaluate the models' predicted channel capacity for different antenna element separation, array orientation and angle spread, with and without mutual coupling. The authors compare these results with measurement campaigns from the literature. The authors also derive an effective distance term that combines the antenna element separation, array orientation and angle spread parameters. The authors use this value to describe the effect on the signal correlation of the antenna output, and thereby explain the outage capacity dependence on the variables. Among the considered channels, the SCM showed the best agreement with the measurement literature, followed by the A-SCM and then the LTE model. The SCM was also the most computationally involved, followed by the A-SCM and then the LTE model. Our analysis showed that the mutual coupling had a small impact on the performance of all channel models, especially for antenna element separations greater than half a wavelength.     

Outage Capacity Analysis for Cognitive Non-Orthogonal Multiple Access Downlink Transmissions Systems in the Presence of Channel Estimation Error

In this paper, we propose a downlink cognitive non-orthogonal multiple access (NOMA) network, where the secondary users (SUs) operate in underlay mode. In the network, secondary transmitter employs NOMA signaling for downlink transmission, and the primary user (PU) is interfered by the transmission from SU. The expressions for the outage probabilities are derived in closed-form for both primary and secondary users in the presence of channel estimation error. Numerical simulation results show that the channel estimation error and the inter-network interference cause degradation of the downlink outage performance. Also the power allocation and the location have a significant impact on the outage probability. The numerical experiments demonstrate that the analytic expressions of the outage probabilities match with the simulation results.     

Adaptive pseudo-noise code acquisition scheme using automatic censoring for DS/SS communication in frequency-selective Rayleigh fading channel

An adaptive pseudo-noise code acquisition scheme based on automatic multipath signal cancellation for mobile communication systems in frequency-selective Rayleigh fading channel is proposed. The proposed system combines a serial strategy and an automatic censored cell-averaging constant false alarm rate (CFAR) detector based on ordered data variability. This system does not require any a priori information about the number of interferences caused by the presence of multipath signals in the reference channel. The mean acquisition time and the detection performances of the proposed processor are evaluated and compared with those of the conventional adaptive acquisition scheme based on fixed-censoring point detector. It is shown that the considered scheme outperforms significantly the conventional one. The effects of various channel parameters on the acquisition performance, namely the number of resolvable paths, the partial correlation length and the signal-to-noise ratio are also investigated.     

基于海面散射的莱斯MIMO信道容量研究

通过相关莱斯信道模型对海面散射水声多入多出(MIMO)信道容量进行了研究。从Helmholtz-Kirchhoff积分和Fresnel近似出发,得到海面散射信号的空间相关性,由于信道的协方差矩阵不可以表示成发射相关矩阵和接收相关矩阵的Kronecker积,通过Monte Carlo仿真研究了莱斯因子、接收信噪比和空间相关性对MIMO信道容量的影响。从对outage capacity和信道容量的CCDF(Complementary Cumulative Distribution Function)的仿真计算结果可以看出,莱斯衰落的MIMO信道容量并不总是小于瑞利衰落MIMO信道容量,当信道的空间相关性较大和接收信噪比较小时,由于信道的衰落作用将起主要作用,对于较小的收发阵元数,以非衰落的直达信号为主的莱斯MIMO信道容量将大于瑞利衰落的MIMO信道容量。     

A hybrid multiuser detector for DS-UWB systems with matched filter and error-bit recognizer

In this article, we propose a hybrid algorithm of multiuser detection (MUD) for direct sequence ultra-wideband (UWB) communication systems, based on matched filters (MF) and error-bit recognizers (ER). The ER embraces three steps: bit mapping, K-means clustering, and sign judgment. In this detector, we construct a mapping function and map the output base-band bits from MFs into a one-dimensional feature space to get the amplitude information. After that, we set an initial value and classify the bits into right bits and wrong ones by K-means clustering. Finally, we make the sign judgment to prevent some right bits being picked out as wrong bits and correct the wrong bits to reduce the bit error rate (BER) of the system. Compared to a conventional detector based on MFs and minimum mean square error detector, to a large extent, our detector can improve the BER performance of a system because of high recognition probability of the wrong bits in K-means clustering. What is more, the simulation results show that the proposed hybrid MUD is not sensitive to the number of users. It can achieve a good BER performance and low computational complexity when there are 20 UWB transmitters in the channel.     

Joint power allocation and relay positioning in multi-relay cooperative systems

The authors consider a dual-hop multi-relay cooperative relay system in this study. Both decode-and-forward (DF) and amplify-and-forward (AF) protocols are considered. Under different relay selection strategies, the authors derive closed-form outage probability expressions. With the second-order channel statistics, the authors propose to jointly optimise power allocation (PA) and relay positions in order to minimise the system outage probability. Simulation results show that the proposed adaptive allocation algorithms significantly outperform fixed allocation algorithms. With the proposed joint optimisation algorithm, AF relaying outperforms DF relaying when multiple relays are selected to help. When only the best relay is selected to help, DF relaying is shown to have better performance.     

车载自组织网络信息流量特性分析

为了揭示车载自组织网络动态拓扑特性,预测车载自组织网络行为和缓解网络拥堵,本文从微观角度分析了信息流量分布的一般特性,研究了在不同交通需求下车载自组织网络信息流量分布特性及信息流量与节点度值之间的关系.首先提出度、度分布指数与信息流量的关系,用复杂网络理论以静态、动态两种方式建立无容量限制的无标度网络模型,采用数值模拟实验和仿真实验方法讨论了参数变化时车载自组织网络信息流量变化规律;其次,借助非线性动力学理论研究了考虑容量限制的信息流量分布特性.研究结果表明,信息流量分布指数是无标度网络的通用特征参数,度值大的节点对网络影响较大,传播信息更快,信息流量与度值之间满足幂律分布规律;当信息流量需求增大时,Hub节点可能负担过重,许多信息流量可能会选择其他节点避免与Hub节点连通,这时较小度值的节点承担这部分信息流量.     

Exact error rate analysis of free-space optical communications with spatial diversity over Gamma–Gamma atmospheric turbulence

The error rate performances and outage probabilities of free-space optical (FSO) communications with spatial diversity are studied for Gamma–Gamma turbulent environments. Equal gain combining (EGC) and selection combining (SC) diversity are considered as practical schemes to mitigate turbulence. The exact bit-error rate (BER) expression and outage probability are derived for direct detection EGC multiple aperture receiver system. BER performances and outage probabilities are analyzed and compared for different number of sub-apertures each having aperture area A with EGC and SC techniques. BER performances and outage probabilities of a single monolithic aperture and multiple aperture receiver system with the same total aperture area are compared under thermal-noise-limited and background-noise-limited conditions. It is shown that multiple aperture receiver system can greatly improve the system communication performances. And these analytical tools are useful in providing highly accurate error rate estimation for FSO communication systems.     

无背景噪声下的光MPPM信道容量分析

基于多脉冲位置调制(MPPM)在无背景噪声下的信道模型,根据信息理论,推导了有保护时段的光MPPM信道容量的表达式,在此基础上又推出了MPPM的信息传输速率和容量能量效率的表达式.分析并比较了MPPM和PPM的信道容量、信息传输速率以及信道容量能量效率.仿真结果表明,在对光脉冲功率、系统带宽倒数、单个脉冲所含光子教等参数进行适当的选取以后,MPPM在信道容量方面的特性优于PPM.     

Performance analysis of free-space optical communication systems over atmospheric turbulence channels

Turbulence fading is one of the main impairments affecting the operation of free-space optical (FSO) communication systems. The authors study the performance of FSO communication systems, also known as wireless optical communication systems, over log-normal and gamma-gamma atmospheric turbulence-induced fading channels. These fading models describe the atmospheric turbulence because of its very good agreement with experimental measurement data. Closed-form expressions for the average (ergodic) capacity and the outage probability are derived for both statistical models. Another contribution of this work is a study of how the performance metrics are affected by the atmospheric conditions and other parameters such as the length of the link and the receiver's aperture diameter. The derived analytical expressions are verified by various numerical examples and can be used as an alternative to time-consuming Monte-Carlo simulations.     

Turbo channel estimation and equalisation for a superposition-based cooperative system

This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.     

Optimization of Channel Estimation Using ELMx-based in Massive MIMO

In communication channel estimation, the Least Square (LS) technique has long been a widely accepted and commonly used principle. This is because the simple calculation method is compared with other channel estimation methods. The Minimum Mean Squares Error (MMSE), which is developed later, is devised as the next step because the goal is to reduce the error rate in the communication system from the conventional LS technique which still has a higher error rate. These channel estimations are very important to modern communication systems, especially massive MIMO. Evaluating the massive MIMO channel is one of the most researched and debated topics today. This is essential in technology to overcome traditional performance barriers. The better the channel estimation, the more accurate it is. This paper investigated machine learning (ML) for channel estimation. ML channel estimations based on the Extreme Learning Machine (ELMx) group are also implemented. These estimations, known as the ELMx group, include Regularized Extreme Learning Machine (RELM) and Outlier Robust Extreme Learning Machine (ORELM). Then, it was compared with LS and MMSE. The simulation results reveal that the ELMx group outperforms LS and MMSE in channel capacity and bit error rate. Additionally, this paper has proven complexity for verified computational times. The RELM method is less time consuming and has low complexity which is suitable for future use in large MIMO systems.     

Nodal probabilistic production cost simulation considering transmission system unavailabilty

A nodal probabilistic production cost simulation method is described for power system long-term expansion planning considering unavailability and delivery limitation constraints of the transmission system. This new nodal production cost simulation model includes capacity constraints and unavailabilities of generators as well as transmission lines. This simulation methodology comes from the nodal composite power system equivalent load duration curve (CMELDC), based on a new effective load model at load points developed by the authors. The nodal CMELDC can be obtained from convolution integral processing of the outage capacity probability distribution function of the fictitious generator and the original LDC. It is expected that the new simulation model based on the nodal CMELDC proposed here will provide solutions to many problems based on nodal and decentralised operation and control of electric power systems under a competition environment. The nodal CMELDC based on the new model at load points can extend application areas of nodal probabilistic production cost simulation, probabilistic congestion cost assessment, analytical outage cost assessment and nodal reliability evaluation and so on at load points. The characteristics and effectiveness of this new proposed methodology are illustrated by a small system case study using a network flow and enumeration method.     

Comparison Between Viterbi Detectors for Magnetic Recording Channels Based on Regressive and Autoregressive Noise Models

A recent work presents a regressive noise model for the data-dependent correlated noise, at the output of a magnetic recording channel detector. We have generalized this channel model, considering digital equalization and a more efficient correlation matrix, in order to make a comparison with the usual detector in a more realistic environment. Simulation results show that the regressive detector performs better when the number of trellis states is lower than needed, while both approaches are comparable when the number of states matches the channel memory.     

Outage capacity and outage rate performance of MIMO free-space optical system over strong turbulence channel

Abstract

In this paper, we investigate outage capacity, outage probability, and outage rate performance of multiple-input multiple-output (MIMO) free-space optical system operating over strong turbulence channels. The MIMO optical system employs intensity modulation direct detection with on-off signaling, and equal gain combining technique at the receiver. We derived novel closed-form expressions for three system metrics, namely, outage capacity, outage probability, and outage rate. Expressions derived here are based on the generalized Gamma–Gamma channel model, which is based on scintillation theory that assumes that the irradiance of the received optical wave is modeled as the product of small-scale and large-scale turbulence eddies. The results are evaluated for different values of received signal-to-noise ratios, strong turbulence conditions, and several values of transmit/receive diversity.