In this paper, we study the problem of optimizing statistical beamforming design for each user in a two-antenna downlink multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) system. The transmitter only possesses statistical information in the form of covariance matrices for each user’s link. The statistical beamforming designs are derived in maximizing the ergodic sum rate considering both low and high signal-to-interference-plus-noise ratio (SINR) extreme scenarios. In addition to the analytical investigations, we also conduct MonteCarlo simulations in comparison and to affirm the accuracy of the derived ergodic sum rate expressions. Results show that the ergodic sum rate increases with the total transmit power and decreases with the power coefficient of near users. Comparing the optimized MISO-NOMA system with conventional MISO-OMA scheme, it is demonstrated that MISO-NOMA can significantly improve the ergodic sum rate.

Stereo matching of high-resolution satellite images (HRSIs) is still a fundamental but challenging task in the field of photogrammetry and remote sensing. Recently, deep learning (DL) methods have demonstrated the potential for stereo matching on public benchmark datasets. Currently, mainstream stereo matching models depend on quantities of training data with ground truth. However, datasets for stereo matching of satellite images are scarce, which profoundly blocks the application of DL in this field. To facilitate further research, this article publishes a large-scale dataset, termed WHU-Stereo, for stereo matching DL network training and testing. This dataset is created by using airborne light detection and ranging (LiDAR) point clouds and high-resolution stereo imageries taken from the Chinese GaoFen-7 (GF-7) satellite. Occlusions should be seriously considered in the generation of ground-truth disparities. We propose an occlusion removal technique, which can adapt to point clouds with different densities and shows high potential in training data preparation. The WHU-Stereo dataset contains more than 1700 epipolar rectified image pairs, which cover six areas in China and includes various kinds of landscapes. We have assessed the accuracy of ground-truth disparity maps, and it is shown that our dataset achieves comparable precision compared with existing state-of-the-art stereo matching datasets. To verify its feasibility, in experiments, the handcrafted semiglobal matching (SGM) algorithm and recent DL networks have been tested on the dataset. Experimental results show that the WHU-Stereo dataset can serve as a challenging benchmark for stereo matching of HRSIs and performance evaluation of DL models. Our dataset is available athttps://github.com/Sheng029/WHU-Stereo.

In this treatise, we derive tractable closed-form expressions for the outage probability of the single cell multi-carrier non-orthogonal multiple access (MC-NOMA) downlink, where the transmitter side only has statistical CSI knowledge. In particular, we analyze the outage probability with respect to the total data rates (summed over all subcarriers), given a minimum target rate for the individual users. The calculation of outage probability for the distant user is challenging, since the total rate expression is given by the sum of logarithmic functions of the ratio between two shifted exponential random variables, which are dependent. In order to derive the closed-form outage probability expressions both for two subcarriers and for a general case of multiple subcarriers, efficient approximations are proposed. The probability density function (PDF) of the product of shifted exponential distributions can be determined for the near user by the Mellin transform and the generalized upper incomplete Fox's H function. Based on this PDF, the corresponding outage probability is presented. Finally, the accuracy of our outage analysis is verified by simulation results.

In this paper, we analyze the outage probability of the multi-user multiple-input single-output (MISO) downlink system by combining the non-orthogonal multiple access (NOMA) scheme. We derive tractable closed-form outage expressions given a minimum target rate for the individual users for the case of two antennas, by modeling cumulative distribution function (CDF) of received signal-to interference plus noise ratio (SINR). Simulation results illustrate the outage performance for different power allocation scenarios and verify the accuracy of our outage probability analysis.

In this paper, we study power allocation for downlink multi-carrier non-orthogonal multiple access (MC-NOMA)systems and examine the effects of residual cancellation errors resulting from imperfect successive interference cancellation (SIC) on the system performance. In the presence of random SIC errors, we study outage probability of minimum reserved rate for individual user and formulate outage-constrained robust optimization to minimize the total transmit power. Since the problem is non-convex due to probabilistic constraints, complementary geometric programming (CGP) and arithmetic geometric mean approximation (AGMA) technique are employed to transform it into a convex form. An efficient iterative algorithm with low computational complexity is developed to solve the optimization problem. Simulation results demonstrate the performance of robust MC-NOMA with imperfect SIC and compare that to non-robust MC-NOMA and orthogonal multiple access (OMA) schemes.