Design of robust differential microphone arrays with the Jacobi–Anger expansion

Due to their small size, differential microphone arrays (DMAs) are very attractive. Moreover, they have been effective in combating noise and reverberation. Recently, a new class of DMAs of different orders have been developed with the MacLaurin’s series and the frequency-independent patterns. However, the MacLaurin’s series does not approximate well the exponential function, which appears in the general definition of the beampattern, when the intersensor spacing is not small enough. To circumvent this problem, we propose in this paper to approximate the exponential function with the Jacobi–Anger expansion. Based on this approximation and the frequency-independent Chebyshev patterns, we derive first-, second-, and third-order DMAs. Furthermore, in order to improve the robustness of DMAs against white noise amplification, we propose to use more microphones combined with minimum-norm filters. It is also shown that the Jacobi–Anger expansion is optimal from a mean-squared error perspective. Simulations are carried out to evaluate the performance of the proposed DMAs.     

分布式目标下行波束形成

研究了智能天线在下行链路的应用。利用上行链路接收数据,建立分布式目标信道模型。估计移动用户的发射角、扩展角度和发射功率以及下行信道相关矩阵,确定下行链路的波束形成方法。即对频分复用（FDD）系统进行上行相关矩阵变换,构建下行信道协方差矩阵,利用最大合并比准则获得下行链路权值。计算机仿真证实了这种方法的有效性。     

Directional neighbor discovery in mmWave wireless networks

The directional neighbor discovery problem, i.e., spatial rendezvous, is a fundamental problem in millimeter wave (mmWave) wireless networks, where directional transmissions are used to overcome the high attenuation. The challenge is how to let the transmitter and the receiver beams meet in space under deafness caused by directional transmission and reception, where no control channel, prior information, and coordination are available. In this paper, we present a Hunting-based Directional Neighbor Discovery (HDND) scheme for ad hoc mmWave networks, where a node follows a unique sequence to determine its transmission or reception mode, and continuously rotates its directional beam to scan the neighborhood for other mmWave nodes. Through a rigorous analysis, we derive the conditions for ensured neighbor discovery, as well as a bound for the worst-case discovery time and the impact of sidelobes. We validate the analysis with extensive simulations and demonstrate the superior performance of the proposed scheme over several baseline schemes.     

Analysis and simulation of QSP beamformer

The real Direction Of Arrival (DOA) varies with time in mobile communication system. In such situation, the performance of conventional beamformers will be degraded obviously. Quantum Signal Processing (QSP) beamformer is insensitive to DOA errors, thus it can achieve stable output performance in such circumstance. This letter verified the effectiveness and feasibility of the QSP beamformer by simulation results.     

模拟退火算法在波束图设计中的应用

摘要本文提出了基于模拟退火算法的波束设计方法。模拟退火算法模拟了固体缓慢退火从而获得最低内能的物理过程，是一种简单而有效的随机性全局优化算法。为证明该设计方法的可行性和有效性，给出了15元平面阵的设计实例以及仿真结果。结果表明，使用该方法设计的波束与常规方法相比，获得了更低的旁瓣级。     

基于相关域的二维自适应波束形成算法

 该文针对使用最小方差无失真响应算法进行2维波束形成时需要大量采样数据和庞大计算复杂度这一问题,提出一种基于相关域的2维自适应波束形成算法。通过将高维权向量分解成两个低维权向量的Kronecker积形式,使用双迭代算法利用相关域信息求解出两个低维权向量,从而降低了估计采样相关矩阵所需的采样数据和计算量。实验仿真表明,所提算法具有良好的收敛性能,在采样数较小的情况下,能够更好地抑制干扰信号。     

冲击噪声背景下基于最小均方归一化误差的波束形成算法

 本文提出一种适用于任意未知统计特性的代数拖尾冲击噪声环境下的MMSNE波束形成算法。算法利用输出信号和参考信号之间的“归一化误差”最小化来求解最优权向量。“归一化误差”定义为接收信号的瞬时自适应无穷范数归一化的形式。与基于最小分数低阶误差波束形成算法相比,MMSNE波束形成算法计算更为简单;不需要噪声特征指数的先验信息或估计;适用于更广的冲击噪声环境;具有更小的估计误差;具有更强的干扰抑制能力。     

Energy-efficient beamforming optimization for MISO communication based on reconfigurable intelligent surface

Reconfigurable intelligent surface (RIS), a planar metasurface consisting of a large number of low-cost reflecting elements, has received much attention due to its ability to improve both the spectrum and energy efficiency (EE) by reconfiguring the wireless propagation environment. In this paper, we propose a base station (BS) beamforming and RIS phase shift optimization technique that maximizes the EE of a RIS-aided multiple-input–single-output system. In particular, considering the system circuits’ energy consumption, an EE maximization problem is formulated by jointly optimizing the active beamforming at the BS and the passive beamforming at the RIS, under the constraints of each user’ rate requirement, the BS’s maximal transmit power budget and unit-modulus constraint of the RIS phase shifts. Due to the coupling of optimization variables, this problem is a complex non-convex optimization problem, and it is challenging to solve it directly. To overcome this obstacle, we divide the problem into active and passive beamforming optimization subproblems. For the first subproblem, the active beamforming is given by the maximum ratio transmission optimal strategy. For the second subproblem, the optimal phase shift matrix at the RIS is obtained by exploiting sine cosine algorithm (SCA). Moreover, for this case where each reflection element’s working state is controlled by a circuit switch, each reflection element’s switch value is optimized with the aid of particle swarm optimization algorithm. Finally, numerical results verify the effectiveness of our proposed algorithm compared to other algorithms.     

基于神经网络的波束形成

本文给出利用神经网络来实现智能天线的波束形成的方法。选取了适当的神经元数目，减少了训练时间。模拟输出的赋形结果与维纳(Wiener)解相吻合，并与传统算法进行性能比较，表明了该方案的有效性。     

二维频域波束形成方法

一般来讲，无论雷达或声纳从基阵接收的信号均是多维信号，本文将在二维频率域对窄带传输信号进行分析与描述，研究线列阵的波束形成问题，根据分析结果并考察了几种特例。