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This letter proposes a joint-sparse index removal (JSIR) based algorithm to detect the index of space-frequency index modulation (SFIM) signal for MIMO-OFDM cognitive radio (MIMO-OFDM-CR) system. At first, the proposed algorithm calculates the inner-product matrix of the received signal and channel gain to measure the index information of each subcarrier on each antenna. Then, an antenna index metric is computed through a definition which is given by summing the metrics of all subcarriers on the antenna. According to the metric, the silent antenna indices are acquired by comparing the metric with a threshold derived from statistical distribution. Next, the index detection problem is simplified by removing the silent antenna indices, i.e., the joint-sparse indices of SFIM signal matrix. At last, the indices of active subcarriers on active antennas are obtained through solving the simplified problem via a compressed sensing reconstruction algorithm. The complexity analysis shows that the proposed JSIR algorithm has lower complexity under certain conditions, compared with other related methods. The simulation results verify the accuracy of the proposed method in terms of bit error rate (BER). [ABSTRACT FROM AUTHOR]

Hybrid precoding based on the sub-connected structure is one of promising technologies for millimeter-wave communications. Whereas, the existing hybrid designs of the sub-connected structure are all based on the linear precoding, which may suffer from a noise enhancement and performance deterioration. To tackle this issue, this letter proposes a novel nonlinear hybrid Tomlinson-Harashima (TH) precoding algorithm. In the proposed algorithm, a column-wise refinement procedure is firstly developed to update the radio frequency (RF) precoding and combining matrices column by column via Schur complement. Such a refinement procedure can effectively obtain the optimal solutions of each columns of the RF precoding and combining matrices, however, it requires matrix inversions with high complexity. Thus a recurrence relation of the matrix inversion is further established, which can reduce the complexity of the aforementioned refinement procedure greatly. Finally, the digital precoding and combining matrices are given by QR decomposition. Simulations show that the proposed algorithm can effectively improve the spectral efficiency with lower complexity. [ABSTRACT FROM AUTHOR]

In this paper, we present systematic micromagnetic modeling investigation on recording process of segmented thin-film media with circularly polarized magnetic field at microwave frequencies. This paper provides insightful understanding about the segmented medium stack design in microwave-assisted magnetic recording (MAMR) by exploring the impact of signal-to-noise (SNR) ratio and recording track width. By utilizing segmentation of grains with exchange breaking layers, the ac magnetic field generated from spin torque oscillator can be best exploited. Via optimized medium stack design, MAMR is able to achieve both high SNR and areal density gain with the proposed notched-structure medium (top and bottom segments have the strongest crystalline anisotropy) compared with conventional graded medium (with gradually increasing anisotropy from top to bottom). By tuning crystalline anisotropy strength in top and bottom segment, we studied the MAMR behavior of SNR and track width under different ac frequencies. This provides a novel view for future segmented media design. [ABSTRACT FROM AUTHOR]