Integrated visible light positioning and communication (VLPC), capable of combining advantages of visible light communications (VLC) and visible light positioning (VLP), is a promising key technology for the future Internet of Things. In VLPC networks, positioning and communications are inherently coupled, which has not been sufficiently explored in the literature. We propose a robust power allocation scheme for integrated VLPC Networks by exploiting the intrinsic relationship between positioning and communications. Specifically, we derive explicit relationships between random positioning errors, following both a Gaussian distribution and an arbitrary distribution, and channel state information errors. Then, we minimize the Cramer-Rao lower bound (CRLB) of positioning errors, subject to the rate outage constraint and the power constraints, which is a chance-constrained optimization problem and generally computationally intractable. To circumvent the nonconvex challenge, we conservatively transform the chance constraints to deterministic forms by using the Bernstein-type inequality and the conditional value-at-risk for the Gaussian and arbitrary distributed positioning errors, respectively, and then approximate them as convex semidefinite programs. Finally, simulation results verify the robustness and effectiveness of our proposed integrated VLPC design schemes.

翻译：集成可见光定位与通信（VLPC）技术兼具可见光通信（VLC）与可见光定位（VLP）的优势，是未来物联网领域极具前景的关键技术。在VLPC网络中，定位与通信之间天然存在耦合关系，但这一特性在现有文献中尚未得到充分探讨。本文通过挖掘定位与通信之间的内在关联，提出了一种面向集成VLPC网络的鲁棒功率分配方案。具体而言，我们分别推导了遵循高斯分布与任意分布的随机定位误差与信道状态信息误差之间的显式关系。随后，在满足速率中断约束与功率约束的条件下，最小化定位误差的克拉美-罗下界（CRLB）。该问题属于机会约束优化问题，通常难以直接计算求解。为克服非凸性挑战，我们针对高斯分布与任意分布的定位误差，分别利用伯恩斯坦型不等式与条件风险价值将机会约束保守地转化为确定性形式，进而将其近似为凸半定规划问题。最后，仿真结果验证了所提出集成VLPC设计方案的鲁棒性与有效性。