基于GA的地面数字电视单频网覆盖率优化

提出了一种地面数字电视单频网覆盖率预算方法，该方法考虑实际接收机干扰模型，采用k-LNM法进行信号合成，利用CCDF函数计算覆盖小区的地点概率，预算结果更实际，计算量小.单频网本身产生“人工多径”，为最小化自干扰区域，基于遗传算法求解单频网中各个发射机附加延时的最优组合，该方法无需改变发射台功率、站址、天线等参数，成本为0，克服了发射机数目较多时人工调整发射机附加延时的难点，且准确度高.将该方法应用于我国某地区地面数字电视单频网规划的实际场景中，优化后覆盖率明显提高，验证了该方法的有效性和可行性.

GA-based optimization of SFN coverage probability for DTMB

A method to predict single frequency network (SFN) coverage probability for terrestrial digital multimedia broadcasting (DTMB) was presented. It considers actual receiver interference model. The signal summation method is k-LNM. The location probability for coverage cell is calculated by complementary cumulative distribution function (CCDF). It has less calculation and more practical results. SFN causes artificial multi-path. An optimization approach based on genetic algorithm (GA) was proposed, which dealt with the optimal adjustment of internal delays at the transmitters to minimize self-interference area. It doesn-t need to change power, site and antenna of transmitters. The cost is zero. It overcomes the difficulty with manual adjustment of the delays with large numbers of transmitters and has high degree of precision. It was applied to realistic scenarios of DTMB SFN planning in a certain area of China. The coverage probability is greatly improved after optimization, which verifies the effectiveness and feasibility of this method.