In this letter, a combination of characteristic mode (CM) and compressive sensing (CS) is utilized to accelerate the solution of bistatic scattering problems of three-dimensional (3-D) objects. The surface induced currents discretized by Rao–Wilton–Glisson basis functions are successfully sparsely transformed by CM basis functions based on domain decomposition. Different from the dense matrix equation of traditional method of moments (MoM), a low-rank CS model with smaller size is constructed in the proposed method, wherein the induced currents can be reconstructed efficiently. Due to partially filling of the impedance matrix and efficient recovery algorithm, the time cost in the proposed method is reduced dramatically. Last, the results from several numerical simulations validate the efficiency and accuracy of the proposed method.

A compact wideband printed antenna with deca-band 4G/5G/WLAN for mobile phone devices is proposed in this paper. The complete structure is composed of a monopole antenna and a coupling strip, occupying a small C-shape PCB area of 27 × 10.8 mm². This antenna, which is printed on FR4 substrate with 0.8 mm thickness and fed by a coaxial cable, can provide three wide operating bandwidths that cover 685–1012 MHz, 1596–2837 MHz, and 3288–3613 MHz for 4G/5G/WLAN communication systems. The gains and total radiation efficiencies of the antenna in the low, middle, and high bands are 1.4 dBi–2.5 dBi and 38%–47%, respectively. Besides, the measured results are in good agreement with the simulated results. Further experiments demonstrate that the proposed antenna exhibits a good performance for mobile phones.

To improve the efficiency of constructing basis function in the method of moments combining compressive sensing and Krylov subspace for solving electromagnetic scattering problems of objects, this letter proposes a novel method, in which the blocking technique is employed to construct Krylov subspace basis. Firstly, the object is divided into some small blocks, and each block is extended to ensure the continuity of the current. Then the Krylov subspace basis on each block is calculated. Furthermore, the orthogonality of the basis functions is enhanced by the singular value decomposition technique to achieve higher accuracy. The corresponding numerical calculation shows that the proposed method can achieve significant time efficiency.

A novel method using the compressive sensing (CS) technique to accelerate the multilevel characteristic basis function method (MLCBFM) is proposed in this letter for the solution of electrically large scattering problems. According to the MLCBFM, the solution process involves the full filling of the impedance matrix as well as the construction and solution of the reduced matrix equation on each level, which is time-consuming. Unlike this, we use the CS technique on each level, except for the bottom level, to recover the coefficients of CBFs and total current, through which both memory consumption and computation time would enjoy a significant reduction. Furthermore, we optimize the generalized orthogonal matching pursuit recovery algorithm to the least squares method which achieves more stable recovery accuracy and higher efficiency. The results of numerical simulations indicate that the proposed method is much more efficient and less memory-consuming compared to the MLCBFM while obtaining a higher level of accuracy.