论文标题
二进制序列集优化针对CDMA应用程序通过混合二级二次编程
Binary sequence set optimization for CDMA applications via mixed-integer quadratic programming
论文作者
论文摘要
发现具有低自动和互相关属性的二进制序列集是许多应用程序的硬组合优化问题，包括多输入 - 型 - 次数输出（MIMO）雷达和全局导航卫星系统（GNSS）。平方相关的总和有时称为集成的侧lobe级（ISL），是变量中的四分之一函数，是序列集质量的常用度量。在本文中，我们表明，ISL最小化问题可以作为混合二次二次程序（MIQP）提出。然后，我们提出了一个块坐标下降（BCD）算法，该算法迭代地对变量子集进行了优化。子集优化子问题也是MIQPS，可以使用专用求解器更有效地处理，而不是使用详尽的搜索。这使我们能够对比以前可能更大的可变子集执行BCD。我们的方法用于查找与使用现有BCD方法找到的金代码和序列集更好的ISL性能的四个长度的二进制序列。
Finding sets of binary sequences with low auto- and cross-correlation properties is a hard combinatorial optimization problem with numerous applications, including multiple-input-multiple-output (MIMO) radar and global navigation satellite systems (GNSS). The sum of squared correlations, sometimes referred to as the integrated sidelobe level (ISL), is a quartic function in the variables and is a commonly-used metric of sequence set quality. In this paper, we show that the ISL minimization problem may be formulated as a mixed-integer quadratic program (MIQP). We then present a block coordinate descent (BCD) algorithm that iteratively optimizes over subsets of variables. The subset optimization subproblems are also MIQPs which may be handled more efficiently using specialized solvers than using exhaustive search; this allows us to perform BCD over larger variable subsets than previously possible. Our approach was used to find sets of four binary sequences of lengths up to 1023 with better ISL performance than Gold codes and sequence sets found using existing BCD methods.
