Kernel methods have been successfully applied to nonlinear problems in machine learning and signal processing. Various kernel-based algorithms have been proposed over the last two decades. In this paper, we investigate the kernel conjugate gradient (KCG) algorithms in both batch and online modes. By expressing the solution vector of CG algorithm as a linear combination of the input vectors and using the kernel trick, we developed the KCG algorithm for batch mode. Because the CG algorithm is iterative in nature, it can greatly reduce the computations by the technique of reduced-rank processing. Moreover, the reduced-rank processing can provide the robustness against the problem of over-learning. The online KCG algorithm is also derived, which converges as fast as the kernel recursive least squares (KRLS) algorithm, but the computational cost is only a quarter of that of the KRLS algorithm. Another attractive feature of the online KCG algorithm compared with other kernel adaptive algorithms (KAF) is that it does not require the user-defined parameters. To control the growth of data size in online applications, a simple sparsification criterion based on the angles among elements in reproducing kernel Hilbert space (RKHS) is proposed. The angle criterion is equivalent to the coherence criterion but does not require the kernel to be unit-norm. Finally, numerical experiments are provided to illustrate the effectiveness of the proposed algorithms.

As the backbone of the fifth-generation (5G) cellular network, massive multiple-input multiple-output (MIMO) encounters a significant challenge in practical applications: how to deploy a large number of antenna elements within limited spaces. Recently, holographic communication has emerged as a potential solution to this issue. It employs dense antenna arrays and provides a tractable model. Nevertheless, some challenges must be addressed to actualize this innovative concept. One is the mutual coupling among antenna elements within an array. When the element spacing is small, near-field coupling becomes the dominant factor that strongly restricts the array performance. Another is the polarization of electromagnetic waves. As an intrinsic property, it was not fully considered in the previous channel modeling of holographic communication. The third is the lack of real-world experiments to show the potential and possible defects of a holographic communication system. In this paper, we propose an electromagnetic channel model based on the characteristics of electromagnetic waves. This model encompasses the impact of mutual coupling in the transceiver sides and the depolarization in the propagation environment. Furthermore, by approximating an infinite array, the performance restrictions of large-scale dense antenna arrays are also studied theoretically to exploit the potential of the proposed channel. In addition, numerical simulations and a channel measurement experiment are conducted. The findings reveal that within limited spaces, the coupling effect, particularly for element spacing smaller than half of the wavelength, is the primary factor leading to the inflection point for the performance of holographic communications.

Phase-only beamforming (POB) plays an important role in modern radar and communication systems. The NP-hard nature of POB makes it difficult to be solved for large-scale antenna arrays. This paper studies two fast and simple GP algorithms for the problem of POB. First we give a new interpretation of the GP method under the framework of sequential quadratic programming (SQP). Then we prove that the GP operation gives a strict global minimizer of the subproblem of SQP. Moreover, the larger the step size in GP operation, the smaller the minimum value of the subproblem. Based on this observation we design two variable step size GP (VSGP) algorithms that improve the convergence speed of the GP method significantly. Furthermore, the VSGP algorithms have a simple structure, making them easy to be implemented in chips. Finally, we derive a necessary and sufficient condition for the Karush-Kuhn-Tucker (KKT) points of the POB problem. We also prove that, for any initialization, all limit points of the iterates generated by the VSGP algorithms converge to the KKT points. Simulation results show that the proposed algorithms outperform the state-of-the-art algorithms in terms of convergence speed and computational cost.

The previous experimental studies on angular spectra of reverberation chambers (RCs) were conducted by either rotating a directive horn antenna (which suffers from low resolution) or using conventional beamforming (whose beam varies with frequency), resulting in inaccurate characterizations of angular statistics of the broadband channel in the RC. To avoid this problem, we resort to a frequency-invariant beamformer for the evaluation of the angular–temporal spectra of the RC. Contrary to the previous studies, it is found that modest loading does not increase the statistical anisotropy in the delay domain (after the ramp-up stage of the power delay profile) as compared with the unloaded case, implying that modest loading does not alter RC’s angular statistics for over-the-air testing.

It has been experimentally demonstrated that the antenna pattern can be reconstructed using correlation coefficients and spherical wave expansion in a well-stirred large reverberation chamber (RC) when the antenna under test (AUT) has little impact on the testing environment, but the method becomes ineffective for loaded RCs. To solve this problem, we apply a compensation method to the pattern reconstruction process by using a reference antenna, enabling AUT pattern reconstruction in a loaded RC. In the proposed method, the original radiation pattern of the reference antenna is measured in an anechoic chamber (AC), and the transmission coefficients of the reference antenna are obtained according to the spherical wave coefficient expansion theory. Then, by rotating the reference antenna in the RC, the corresponding antenna correlation and autocorrelation coefficients are obtained, and the radiation pattern of the AUT is reconstructed by using the least square method. Finally, the near-field spherical scattering signals of the reference antenna are used to compensate for the reconstructed results of the AUT spherical wave coefficients, and an improved far-field radiation pattern of the AUT is obtained. The feasibility and effectiveness of the proposed method are verified by simulation and measurement in a loaded RC.