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Titlebook: Communications and Networking; 11th EAI internation Qianbin Chen,Weixiao Meng,Liqiang Zhao Conference proceedings 2018 ICST Institute for C

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樓主: 冰凍
31#
發(fā)表于 2025-3-26 22:02:24 | 只看該作者
Conference proceedings 2018ing, ChinaCom 2016, held in Chongqing, China, in September 2016. .The total of 107 contributions presented in these volumes are carefully reviewed and selected from 181 submissions. The book is organized in topical sections on MAC schemes, traffic algorithms and routing algorithms, security, coding
32#
發(fā)表于 2025-3-27 02:17:11 | 只看該作者
Basic Principles of Sol-Gel Chemistrytrategies. As can be seen from the simulation results, the throughput and area spectrum efficiency are obviously improved with the increasingly dense cells. However, as the network densification the positive influence on throughput and spectrum efficiency would be decreased.
33#
發(fā)表于 2025-3-27 06:52:59 | 只看該作者
34#
發(fā)表于 2025-3-27 12:03:30 | 只看該作者
Tantalum Oxide-Polymer Compositess a stochastic network optimization problem. The problem is solved by utilizing Lyapunov optimization and an efficient on-line algorithm with quite low complexity is obtained. Simulation results illustrate that the proposed algorithm has the same performance as the optimal one with giving statistical knowledge of the stochastic processes.
35#
發(fā)表于 2025-3-27 15:29:06 | 只看該作者
36#
發(fā)表于 2025-3-27 18:03:02 | 只看該作者
37#
發(fā)表于 2025-3-27 23:05:33 | 只看該作者
38#
發(fā)表于 2025-3-28 04:57:15 | 只看該作者
39#
發(fā)表于 2025-3-28 08:29:41 | 只看該作者
Dynamic Power Control for Throughput Maximization in Hybrid Energy Harvesting Nodes a stochastic network optimization problem. The problem is solved by utilizing Lyapunov optimization and an efficient on-line algorithm with quite low complexity is obtained. Simulation results illustrate that the proposed algorithm has the same performance as the optimal one with giving statistical knowledge of the stochastic processes.
40#
發(fā)表于 2025-3-28 12:14:53 | 只看該作者
Coverage and Capacity Optimization Based on Tabu Search in Ultra-Dense Networkr to optimize the performance. Simulation results show that our proposed algorithm gets significant improvement in network performance and outperforms the adaptive simulated annealing in convergence speed while optimizing.
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