To reduce the pilot overhead, compressive sensing techniques have been widely adopted for sparse channel estimation. In this paper, we explore the spatial common sparsity across different channels and investigate the deterministic pilot design with superimposed pattern for the downlink channel estimation in multi-input single-output systems. Previous works generally allocate pilots randomly when using the superimposed pilots to estimate the jointly sparse channels, which is storage-hungry and time-consuming. For the joint optimization of pilot locations and symbols, this paper proposes two pilot design schemes, named by Algorithms 1 and 2, to minimize the intrablock and interblock coherence simultaneously. Algorithm 1 sequentially optimizes pilot locations and symbols, while Algorithm 2 integrates the allocation of pilot symbols into the optimization of pilot locations and alternately optimizes the pilot locations and symbols. Both schemes can flexibly select the design criteria to ensure the small intrablock and interblock coherence. Simulation results show that the proposed pilot designs outperform the existing ones in terms of channel estimate mean-squared-error and bit-error-rate.

为了减少导频开销，压缩感测技术已被广泛地用于稀疏信道估计。在本文中，我们探索了跨不同信道的空间稀疏性，并研究了具有叠加模式的确定性导频设计，用于多输入单输出系统中的下行链路信道估计。以前的工作通常在使用叠加导频估计联合稀疏信道时随机分配导频，这既耗时又费力。为了联合优化导频位置和符号，本文提出了两种导频设计方案，分别用算法1和2命名，以同时最小化块内和块间的相干性。算法1依次优化飞行员位置和符号，而算法2将导频符号的分配集成到导频位置的优化中，并交替优化导频位置和符号。两种方案都可以灵活选择设计标准，以确保较小的块内和块间一致性。仿真结果表明，所提出的导频设计在信道估计均方误差和误码率方面优于现有设计。