Backscatter communication (BackCom), one of the core technologies to realize zero-power communication, is expected to be a pivotal paradigm for the next generation of the Internet of Things (IoT). However, the "strong" direct link (DL) interference (DLI) is traditionally assumed to be harmful, and generally drowns out the "weak" backscattered signals accordingly, thus deteriorating the performance of BackCom. In contrast to the previous efforts to eliminate the DLI, in this paper, we exploit the constructive interference (CI), in which the DLI contributes to the backscattered signal. To be specific, our objective is to maximize the received signal power by jointly optimizing the receive beamforming vectors and tag selection factors, which is, however, non-convex and difficult to solve due to constraints on the Kullback-Leibler (KL) divergence. In order to solve this problem, we first decompose the original problem, and then propose two algorithms to solve the sub-problem with beamforming design via a change of variables and semi-definite programming (SDP) and a greedy algorithm to solve the sub-problem with tag selection. In order to gain insight into the CI, we consider a special case with the single-antenna reader to reveal the channel angle between the backscattering link (BL) and the DL, in which the DLI will become constructive. Simulation results show that significant performance gain can always be achieved in the proposed algorithms compared with the traditional algorithms without the DL in terms of the strength of the received signal. The derived constructive channel angle for the BackCom system with the single-antenna reader is also confirmed by simulation results.
翻译:后发通讯( BackCom) 是实现无能量通信的核心技术之一, 预计将成为下一代Things互联网( IoT) 的关键范例。 然而, “ 强” 直接链接( DL) 干扰( DLI) 传统上被认为是有害的, 通常会因此淹没“ 弱” 后发信号, 从而恶化 BackCom 的性能。 与以前消除 DLI 的努力相比, 在本文中, 我们利用了建设性干扰( CI ), DLI 总是为后发信号作出贡献。 具体地说, 我们的目标是通过联合优化接收的成形矢量矢量和标记选择因素( DL) 来尽量扩大接收信号的链接。 然而, 非Convex 和由于对 Kullback- Leiter ( KL) 差异的限制而难以解决。 为了解决这个问题, 我们首先解析了原始问题, 然后提出两种算法, 通过改变变量和半成形的信号的信号链接, 将Slevillal 变换为S- trainal 。