Millimeter wave (mmWave) massive Multiple-Input Multiple-Output (MIMO) systems generally adopt hybrid precoding combining digital and analog precoder as an alternative to full digital precoding to reduce RF chains and energy consumption. In order to balance the relationship between spectral efficiency, energy efficiency and hardware complexity, the hybrid-connected system structure should be adopted, and then the solution process of hybrid precoding can be simplified by decomposing the total achievable rate into several sub-rates. However, the singular value decomposition (SVD) incurs high complexity in calculating the optimal unconstrained hybrid precoder for each sub-rate. Therefore, this paper proposes PAST, a low complexity hybrid precoding algorithm based on projection approximate subspace tracking. The optimal unconstrained hybrid precoder of each sub-rate is estimated with the PAST algorithm, which avoids the high complexity process of calculating the left and right singular vectors and singular value matrix by SVD. Simulations demonstrate that PAST matches the spectral efficiency of SVD-based hybrid precoding in full-connected (FC), hybrid-connected (HC) and sub-connected (SC) system structure. Moreover, the superiority of PAST over SVD-based hybrid precoding in terms of complexity and increases with the number of transmitting antennas.

A method is proposed for improving the accuracy of the characteristic basis function method (CBFM) using the multilevel approach. With this technique, CBFs taking into account multiple scattering calculated for each block (IP-CBFs; improved primary CBFs) are applied to CBFM using a multilevel approach. By using IP-CBFs, the interaction between blocks is taken into account, and thus it is possible to reduce the number of CBFs while maintaining accuracy, even if the multilevel approach is used. The radar cross section (RCS) of a cube, a cavity, and a dielectric sphere were analyzed using the proposed CBFs, and as a result it was found that accuracy is improved over the conventional method, despite no major change in the number of CBFs.

This paper describes a fast and effective algorithm for refining the parameter estimates of multicomponent third-order polynomial phase signals (PPSs). The efficiency of the proposed algorithm is accompanied by lower signal-to-noise ratio (SNR) threshold, and computational complexity. A two-step procedure is used to estimate the parameters of multicomponent third-order PPSs. In the first step, an initial estimate for the phase parameters can be obtained by using fast Fourier transformation (FFT), k-means algorithm and three time positions. In the second step, these initial estimates are refined by a simple moving average filter and singular value decomposition (SVD). The SNR threshold of the proposed algorithm is lower than those of the non-linear least square (NLS) method and the estimation refinement method even though it uses a simple moving average filter. In addition, the proposed method is characterized by significantly lower complexity than computationally intensive NLS methods. Simulations confirm the effectiveness of the proposed method.

Vector precoding is a nonlinear broadcast precoding scheme in the downlink of multi-user MIMO systems which outperforms linear precoding and THP (Tomlinson-Harashima Precoding). This letter discusses the problem of joint receive antenna selection in the multi-user MIMO downlink with vector precoding. Based on random matrix analysis, we derive a simple heuristic selection criterion using singular value decomposition (SVD) and carry out an exhaustive search to determine for each user which receive antenna should be used. Simulation results reveal that receive antenna selection using our proposed criterion obtains the same diversity order as the optimal selection criterion.

In a frequency-selective multiple-input multiple-output (MIMO) channel, the optimum transmission is achieved by beamforming with eigenvectors obtained at each discrete frequency point, i.e., an extension of eigenbeam-space division multiplexing (E-SDM). However, the calculation load of eigenvalue decomposition at the transmitter increases in proportion to the number of frequency points. In addition, frequency-independent eigenvectors increase the delay spread of the effective channel observed at the receiver. In this paper, we propose a pseudo eigenvector scheme for the purpose of mitigating the calculation load and maintaining frequency continuity (or decreasing the delay spread). First, we demonstrate that pseudo eigenvectors reduce the delay spread of the effective channels with low computational complexity. Next, the practical performance of the pseudo E-SDM (PE-SDM) transmission is evaluated. The simulation results show that PE-SDM provides almost the same or better performance compared with E-SDM when the receiver employs a time-windowing-based channel estimation available in the low delay spread cases.

This paper introduces a novel MIMO (Multiple Input Multiple Output) communication system having orthogonal dual polarization diversity branches. We have designed a dual polarized circular patch antenna which has two orthogonal polarization ports such as vertical polarization (V) and horizontal polarization (H) on its metal surface. This design makes it works as two independent antennas in multipath environments. By using two dual polarized antennas at both the transmitter and receiver, we designed a dual-polarization 44 MIMO experiment system. This system can be used to investigate the performance of various MIMO transmission methods as well as the performance of adaptive algorithms in indoor multipath environments. To investigate the performance of our experiment system, we carried out a number of MIMO transmission experiments such as space-time-coded transmission having two parallel streams and MIMO eigenmode transmission. We will show the results of those experiments and discuss the advantages of using polarization diversity in MIMO communication system for next generation broadband wireless communication.

Coexisting with many concurrent narrowband services, the performance of UWB systems will be affected considerably by them. Specifically, IEEE 802.11a systems which operate around 5 GHz and overlap the band of UWB signals will interfere with UWB systems significantly. In this paper, a novel narrow-band interferences (NBI) suppression technique based on singular value decomposition (SVD) algorithm for a direct sequence ultra-wideband (DS-UWB) communication system is presented. SVD is used to approximate the interferences which then are subtracted from the received signals. The proposed technique is simple and robust. Simulation results show that the proposed new technique is very effective.

In this paper, we present our investigation of Latent Semantic Indexing (LSI) on the local query regions for solving the computation restrictions of the LSI on the global information space. Through the experiments with different SVD dimensionality on the local query regions, the results show that low-dimensional LSI can achieve much better precision than VSM and similar precision to global LSI. Such small SVD factors indicate that there is an almost linear surface in the local query regions. The largest or the two largest singular vectors have the ability to capture such a linear surface and benefit the particular query. In spite of the fact that Local LSI analysis needs to perform the Singular Value Decomposition (SVD) computation for each query, the surprisingly small requirements of the SVD dimension resolve the computation restrictions of LSI for large scale IR tasks. Moreover, on the condition that several relevant sample documents are available, application of low dimensional LSI for these documents can obtain comparable precision with the Local RF in a different manner.