In this paper, based on second-order cross-partial derivative (CPD), we propose an efficient blind image deblurring algorithm for uniform blur. The proposed method consists of two stages. We first apply a novel blur kernel estimation method to quickly estimate the blur kernel. Then, we use the estimated kernel to perform non-blind deconvolution to restore the image. A key discovery of the proposed kernel estimation method is that the blur kernel information is usually embedded in the cross-partial-derivative (CPD) image of the blurred image. By exploiting this property, we propose a pipeline to extract a set of kernel candidates directly from the CPD image and then select the most suitable kernel as the estimated blur kernel. Since our kernel estimation method can obtain a fairly accurate blur kernel, we can achieve effective image restoration using a relatively simple Tikhonov regularization in the subsequent non-blind deconvolution process. To improve the quality of the restored image, we further adopt an efficient filtering technique to suppress periodic artifacts that may appear in the restored images. Experimental results demonstrate that our algorithm can efficiently restore high-quality sharp images on standard CPUs without relying on GPU acceleration or parallel computation. For blurred images of approximately $800\times 800$ resolution, the proposed method can complete image deblurring within 1 to 5 seconds, which is significantly faster than most state-of-the-art methods. Our MATLAB codes are available at https://github.com/e11tkcee06-a11y/CPD-Deblur.git.

In this paper, we propose a low-complexity distributed stable subchannel allocation algorithm combined with a low-cost reconfigurable switched multi-beam directional antenna to improve the capacity and the fairness performance for the orthogonal frequency division multiple access (OFDMA)-based femtocell systems. With the proposed deferred acceptance algorithm, the stable subchannel allocation scheme can achieve a better tradeoff between capacity and fairness. Numerical results show that the proposed stable subchannel allocation scheme with the switched multi-beam antenna can significantly improve femtocell capacity compared to the traditional user-oriented subchannel allocation scheme and ensure the fairness as compared to the traditional channel-oriented subchannel allocation scheme.

Femtocells are low-power, low-cost and user-deployed home base stations that can improve poor indoor coverage and enhance system capacity. However, as femtocells are deployed extensively, the two-tier interference will become serious, including the interference from macrocells and that from femtocells. Thanks to the low side lobe, the E-plane horns based reconfigurable antenna can be used to reduce the interference and enhance the capacity. In this paper, we investigate the effects of applying E-plane horns based reconfigurable directional antenna on link reliability and capacity of the orthogonal frequency-division multiple access (OFDMA) based femtocell systems. We compare our newly designed E-plane horns based reconfigurable antenna,and the sector antenna provided in the IEEE 802.16 m, as well the omni-directional antenna. It is shown that E-plane horns based reconfigurable antenna system has higher femtocell capacity than the IEEE 802.16 m sector antenna system due to the advantages of low side lobe and high main-lobe gain.