Variance analysis of identified linear MISO models having spatially correlated inputs,with application to parallel Hammerstein models

This contribution concerns variance analysis of linear multi-input single-output models when the inputs are temporally white but where different inputs may be correlated. An expression is provided for the variance of a linearly parametrized estimate of the frequency response function from one block, i.e. from one input to the output. In particular, this expression reveals that the variance increases in one block when the number of estimated parameters in another block is increased, but levels off when the number of parameters in the other block reaches the number of parameters in the block in question. It also quantifies exactly how correlation between inputs affects the resulting accuracy and a graphical representation is provided for this purpose. The results are applicable to parallel MISO Hammerstein models when the nonlinearities are known and generalize an existing variance expression for this type of model.     

Joint optimization of spectrum sensing and accessing in multiuser multiple‐input single‐output cognitive networks

In this paper, a joint spectrum sensing and accessing optimization framework for a multiuser cognitive network is proposed to significantly improve spectrum efficiency. For such a cognitive network, there are two important and limited resources that should be distributed in a comprehensive manner, namely feedback bits and time duration. First, regarding the feedback bits, there are two components: sensing component (used to convey various users' sensing results) and accessing component (used to feedback channel state information). A large sensing component can support more users to perform cooperative sensing, which results in high sensing precision. However, a large accessing component is preferred as well, as it has a direct impact on the performance in the multiuser cognitive network when multi‐antenna technique, such as zero‐forcing beamforming, is utilized. Second, the tradeoff of sensing and accessing duration in a transmission interval needs to be determined, so that the sum transmission rate is optimized while satisfying the interference constraint. In addition, the aforementioned two resources are interrelated and inversive under some conditions. Specifically, sensing time can be saved by utilizing more sensing feedback bits for a given performance objective. Hence, the resources should be allocation in a jointly manner. Based on the joint optimization framework and the intrinsic relationship between the two resources, we propose two joint resource allocation schemes by maximizing the average sum transmission rate in a multiuser multi‐antenna cognitive network. Simulation results show that, by adopting the joint resource allocation schemes, obvious performance gain can be obtained over the traditional fixed strategies.Copyright © 2014 John Wiley & Sons, Ltd.     

Secrecy sum rate optimization in MISO nonorthogonal multiple access systems with orthogonal space‐time block coding

In this paper, we investigate the secrecy sum rate optimization problem for a multiple‐input single‐output (MISO) nonorthogonal multiple access (NOMA) system with orthogonal space‐time block codes (OSTBC). This system consists of a transmitter, two users, and a potential eavesdropper. The transmitter sends information by orthogonal space‐time block codes. The transmitter's precoder and the power allocation scheme are designed to maximize achievable secrecy sum rate subject to the power constraint at the transmitter and the minimum transmission rate requirement of the weak user. We consider two cases of the eavesdropper's channel condition to obtain positive secrecy sum rate. The first case is the eavesdropper's equivalent channel is the weakest, and the other is the eavesdropper's equivalent channel between the strong user and weak user. For the former case, we employ the constrained concave convex procedure (CCCP)‐based iterative algorithm with one‐dimensional search. While for the latter, we adopt the method of alternating optimization (AO) between precoder and power allocation. We solve a semidefinite programming to optimize the precoder and drive a closed‐form expression of power allocation. The simulation results obtained by our method demonstrate the superiority of our proposed scheme.     

Multi-input single-output control for extending the operating range: Generalized split range control using the baton strategy

Split range control is used to extend the steady-state operating range for a single output (controlled variable) by using multiple inputs (manipulated variables). The standard implementation of split range control uses a single controller with a split range block, but this approach has limitations when it comes to tuning. In this paper, we introduce a generalized split range control structure that overcomes these limitations by using multiple independent controllers with the same setpoint. Undesired switching between the controllers is avoided by using a baton strategy where only one controller is active at a time. As an alternative solution we consider model predictive control (MPC), but it requires a detailed dynamic model and does not allow for using only one input at a time.     

基于零相关区序列集的空时自适应处理地面运动目标检测算法

在多发单收的合成孔径雷达-地面运动目标检测(SAR鄄GMTI)雷达系统中,虽然多颗卫星之间不需要数据传送就能在接收卫星上实现地面运动目标检测,但存在由于空间发射互相正交的一组波形而导致SAR 成像相干积累的积分旁瓣过高的问题,从而影响对后续的图像域杂波相消性能。因此,文中提出了将空时自适应处理算法用于发射零相关区序列集(ZCZcodes)信号的星载多入单出系统,这样不用考虑积分旁瓣对SAR 成像质量和图像域杂波相消性能带来的影响,且计算量较SAR鄄GMTI 算法小,同样不需要数据传送也在接收卫星上实现了地面运动目标检测。仿真结果和性能分析验证了该方法的有效性。     

基于接收信号的多用户密钥生成方案

基于信道特征生成密钥的方案为通信安全带来了新思路。但在多用户慢衰落条件下,基于信道特征的密钥生成方案由于参数变化慢,导致密钥更新慢。针对此问题,提出了基于接收信号的多用户密钥生成方案,即通过块对角化预编码实现多个随机信号流的分发,使基站与用户能够从用户接收信号中提取密钥。仿真结果表明,提出的基于接收信号的多用户密钥生成方案能够有效提高多用户在准静态及慢衰落条件下的密钥速率。     

基于高阶累积量的空时分组码盲识别算法研究

针对MISO通信系统的空时分组码盲识别问题,提出了一种基于高阶累积量的空时分组码盲识别算法。首先,给出了MISO接收信号模型,利用高阶累积量的性质分析得到接收信号的四阶累积量的表达式;然后,利用编码矩阵的特性,证明接收信号在不同时延向量下的四阶累积量呈现非零值,其非零值取决于STBC的类型;最后,采用四阶累积量的实验值与理论值的最小欧式距离盲识别空时分组码的类型。仿真结果表明,即使在低信噪比条件下,所提方法能够较好地识别空时分组码。     

多入单出正交空时分组码系统的调制识别

在现代无线通信系统中,采用正交空时分组码(STBC)的多天线发射技术是提高通信速率和可靠性,并且能够实现简单译码的关键技术。该文针对瑞利信道系统模型,提出一种适用于多入单出正交空时分组码(OSTBC)的调制识别算法。该算法通过对接收到的数据进行重排,将多入单出的系统模型转化为类似多入多出的系统模型,并且根据信源的特殊性用最大似然的思想实现调制类型的识别。仿真结果验证了所提算法的有效性。     

OFDMA系统中多波束机会波束成形研究

机会波束成形（Opportunistic Beamforming,OBF）技术通过加大、加快信道的波动来提高多用户分集增益,将之使用在正交频分复用多址接入（OFDMA）系统中,可以使得系统的吞吐量最大化。在OFDMA系统中,通过对所有子载波进行分簇,可以实现在牺牲系统性能很少的情况下,大大降低系统反馈量。研究了对分簇OFDMA系统使用OBF技术来提高系统吞吐量,并进一步研究了在训练阶段使用多个随机加权向量进行多波束成形,然后从中选择最好的一个来实现数据阶段的波束成形。仿真证明,采用多波束机会波束成形技术能提高OFDMA系统吞吐量。     

混合噪声环境下正交空时分组码误符号率的分析

对于脉冲和高斯加性混合噪声环境下正交空时分组码的性能进行了研究,建立了采用最大似然译码的混合噪声多发单收近似等效模型．利用矩母函数分析方法,推导出了Rayleigh衰落信道下空时分组码误符号率闭式表达式的渐近解．对采用M-PSK 和M-QAM调制方式的不同空时分组编码方案在混合噪声环境下误符号率的性能进行了分析,蒙特卡洛仿真结果与解析性能结果吻合良好．