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您的检索式：作者名="Danping Su"
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| 1 | User Association and Wireless Backhaul Bandwidth Allocation for 5G Heterogeneous Networks in the Millimeter-Wave Band显示文摘The user association and wireless backhaul bandwidth allocation for a two-tier heterogeneous network(Het Net) in the millimeter wave(mm Wave) band is proposed in this article. The two-tier Het Net is built up with a macro base station(MBS) and several small cell SBSs, where the MBS is assumed to be equipped with large-scale antenna arrays but the SBSs only have single-antenna capability and they rely on the wireless link to the MBS for backhaul. The sum of logarithmic user rate, which is established according to the result of multi-user Multiple Input Multiple Output(MIMO) downlink employing Zero-Force Beamforming(ZFBF), is chosen as the network utility for the objective function. And a distributed optimization algorithm based on primal and dual decomposition is used to jointly optimize the user association variable xj,i and the wireless backhaul bandwidth factor β. Simulation results reveal that the distributed optimization algorithm jointly optimizing two variables outperforms the conventional SINR-based user association strategies. | zhenxiang su bo ai yichuan lin danping he ke guan ning wang guoyu ma li niu | 2018 | China Communications2018，15，4： | 2 |
| 2 | How to Deal with the Profits of State-Owned Companies?显示文摘Recently,how to deal with the profits of state-owned companies has become the hottest topic appearing almost all kinds of media.In 2008,Industrial and Commercial Bank of China(ICBC),PetroChina and China Mobile together had a profit of more than RMB 300 billion.However, the three companies turned over | Xiang Kaibiao Su Danping | 2009 | China's Foreign Trade2009，，10： | 0 |
| 3 | Denoising enabled channel estimation for underwater acoustic communications:A sparsity-aware model-driven learning approach显示文摘It has always been difficult to achieve accurate information of the channel for underwater acoustic communications because of the severe underwater propagation conditions,including frequency-selective property,high relative mobility,long propagation latency,and intensive ambient noise,etc.To this end,a deep unfolding neural network based approach is proposed,in which multiple layers of the network mimic the iterations of the classical iterative sparse approximation algorithm to extract the inherent sparse features of the channel by exploiting deep learning,and a scheme based on the Sparsity-Aware DNN(SA-DNN)for UAC estimation is proposed to improve the estimation accuracy.Moreover,we propose a Denoising Sparsity-Aware DNN(DeSA-DNN)based enhanced method that integrates a denoising CNN module in the sparsity-aware deep network,so that the degradation brought by intensive ambient noise could be eliminated and the estimation accuracy can be further improved.Simulation results demonstrate that the performance of the proposed schemes is superior to the state-of-the-art compressed sensing based and iterative sparse recovery schems in the aspects of channel recovery precision,pilot overhead,and robustness,particularly under unideal circumstances of intensive ambient noise or inadequate measurement pilots. | Sicong Liu Younan Mou Xianyao Wang Danping Su Ling Cheng | 2023 | Intelligent and Converged Networks2023，4，1： | 0 |
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