针对OFDM(orthogonal frequency division multiplexing)系统中由于时变信道引入的载波间干扰消除问题,分析了MIMO-OFDM系统各接收天线频域中子载波上信号的信噪比,提出了一种基于子载波信噪比最优的联合时域干扰消除方法.分析表明,目标问题是一个广义Rayleigh熵问题,并且利用信道干扰矩阵主要能量分布在对角线的特点可以进一步减少算法的计算量.文中提出的干扰消除方法具有较好的性能,且对信道估计误差不敏感.
In this paper, we study the interconnect buffer and wiresizing optimization problem under a distributed RLC model to optimize not just area and delay, but also crosstalk for RLC circuit with non-monotone signal response. We present a new multiobjective genetic algorithm（MOGA） which uses a single objective sorting（SOS） method for constructing the non-dominated set to solve this multi-objective interconnect optimization problem. The MOGA/SOS optimal algorithm provides a smooth trade-off among signal delay, wave form, and routing area. Furthermore, we use a new method to calculate the lower bound of crosstalk. Extensive experimental results show that our algorithm is scalable with problem size. Furthermore, compared to the solution based on an Elmore delay model, our solution reduces the total routing area by up to 30%, the delay to the critical sinks by up to 25%, while further improving crosstalk up to 25.73% on average.
This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for many series RLC-current chains based on their Norton＇s form companion models in the original networks,and then the precondition conjugate gradient based iterative method is used to solve the reduced networks,which are symmetric positive definite. The solutions of the original networks are then back solved from those of the reduced networks.Experimental results show that the complexities of reduced networks are typically significantly smaller than those of the original circuits, which makes the new algorithm extremely fast. For instance, power/ground networks with more than one million branches can be solved in a few minutes on modern Sun workstations.
