<p>Sparse vector transmission, designed for constructing sparse linear underdetermined systems, has garnered significant interest in short-packet ultra-reliable and low-latency communications (URLLC), owing to its advantages such as simple implementation and reliable transmission. A key challenge in optimizing system performance lies in the construction of short sparse vectors. To address this issue, this paper proposes a novel multi-layer merged sparse vector transmission framework, which partitions the index bits into multiple layers and sequentially determines the non-zero entries of each layer within a predefined sparse vector via layer-wise sparse mapping. By enabling cross-layer sharing of position resources, this structure achieves efficient sparse vector compression and higher resource utilization than conventional global selection. Simulation results demonstrate a clear block error rate (BLER) advantage over prior sparse vector transmission schemes, particularly under high coding rates where sparse vectors contain many non-zero entries.</p>