基于突发传输的平均速率优化算法

随着互联网和移动通信的快速发展，对数据传输速率的要求也越来越高。本文针对总功率有限的慢衰落系统，在短期功率约束和长期功率约束下，提出了实现最大平均速率的优化方案。在短期功率约束下，通过研究信道增益进而得出突发传输下的最优量化方案；在长期功率约束下，提出了基于注水算法的改进功率分配算法，进而实现最大速率。理论分析及仿真结果显示，本文算法对改善传输速率有较好的表现。

Optimization Algorithm of Expected Rate Based on Bursty Transmission

With the rapid development of internet and mobile communication, the higher and higher transmission rate is required. The transmission rate is one of important indicators for wireless communication network and the maximum transmission rate is decided by signal-to-noise ratio (SNR). In order to achieve the maximum expected rate, it is necessary to know the channel state information (CSI). Besides, bursty transmission can improve the reliability of the wireless transmission under low SNR. Since many systems have limited power, we should consider how to maximize transmission rate under the condition of power constraint. To this end, this paper investigates the expected rate with quantized feedback over a fading channel subject to power constraints. For systems with a short-term power constraint, we can derive an equality about channel gain by using a period power. And then, we obtain the optimum quantization schemes with bursty transmission. For systems with a long-term power constraint, we use alternating minimization ideas to find the optimization solutions, which includes two parts:In the first part, system power is fixed, then we analyze the change of channel gain and find the optimization scheme. This case is similar to short-term power constraint. In the second part, channel gain is fixed, then we analysis the power allocation of parallel channel. For this case, we propose a two-step power allocation method based on the traditional water-filling followed by a water adjustment step, which can achieve the maximum expected rate. From the analysis and simulation results, it can be known that the proposed algorithm based on traditional water-filling can achieve a higher transmission rate than traditional water-filling algorithm under the same power constraint. Hence, the proposed algorithm has better performance for improving the transmission rate.