• Chinese Journal of Lasers
  • Vol. 49, Issue 23, 2306003 (2022)
Yanan Xin1, Qilie Liu1, Qian Liu1, Qianbin Chen1, Hongmei Xue2、*, Ziyan Li1, and Kui Cheng3
Author Affiliations
  • 1Key Laboratory of Mobile Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • 2School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, Hebei, China
  • 3Faculty of Artificial Intelligence and Big Data, Yibin University, Yibin 644000, Sichuan, China
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    DOI: 10.3788/CJL202249.2306003 Cite this Article Set citation alerts
    Yanan Xin, Qilie Liu, Qian Liu, Qianbin Chen, Hongmei Xue, Ziyan Li, Kui Cheng. Robust Energy Efficiency Resource Allocation Algorithm for Heterogeneous VLC/RF Network Based on Bounded Channel State Information Uncertainty[J]. Chinese Journal of Lasers, 2022, 49(23): 2306003 Copy Citation Text show less

    Abstract

    Objective

    Recently, with the rapid increase in mobile devices and applications, how to meet people’s increasing demand for wireless data has become a hotly debated issue. Due to its many inherent benefits, including license-free spectrum, low cost, high security, strong antielectromagnetic interference capability, and high-speed short-range wireless communication, the visible light communication (VLC) system has received a lot of attention. The performance of the VLC system will be significantly impacted by non-line-of-sight, and the radio frequency system must also take into account the restricted spectrum resources despite having the advantage of wide coverage. Therefore, combining the characteristics of the RF system and the VLC system, a heterogeneous VLC/RF hybrid network is proposed.

    Methods

    An energy efficiency (EE) maximization-based resilient resource allocation algorithm is proposed to address imperfect channel state information (CSI) and low system EE for a heterogeneous VLC/radio frequency (RF) network with channel uncertainty. Considering the constraints of the maximum transmit power of the VLC access point (AP) and the RF AP, the transmit time of each user, the system band, the quality-of-service requirement of VLC and RF users, and the rate outage probability constraint with random channel uncertainty, a robust efficiency maximization resource allocation problem is established under random channel uncertainties based on rate outage probability. Using Dinkelbach’s method, the original optimization problem based on the outage probability is converted into an equivalent deterministic one, which is transformed into two convex optimization subproblems using the alternating optimization algorithm. This thesis proposed an EE maximization algorithm based on alternate iteration.

    Results and Discussions

    The performance of the proposed strategy for the heterogeneous VLC/RF hybrid network is simulated and examined using MATLAB. The higher the maximum transmission power of VLC AP, the higher the system’s EE (Fig. 3). As the RF/VLC subsystem estimation error increases, the outage probability increases. Because the larger the estimation error, the larger the difference between the actual value of the channel gain and the estimated value, and the probability of system user interruption increases. Moreover, the rate-maximum robust algorithm has the lowest outage probability, followed by the proposed robust resource allocation algorithm, while the power-minimum robust algorithm has the highest outage probability over threshold. The power-minimum algorithm is 16.7% more robust than the algorithm proposed in this thesis (Fig. 4). In the RF subsystem, EE increases with the channel estimation error. Additionally, the EE increases with the increase of RF channel estimation error under the same VLC channel estimation error condition (Fig. 5). Under the same VLC outage probability threshold condition, the system EE also decreases with the increase in the RF outage probability threshold. Simultaneously, under the condition of the same RF interruption probability threshold, if the VLC interruption probability threshold increases, the EE of the system will also decrease (Fig. 6). With the increase in the user’s minimum demand rate, the system EE of the four algorithms decreases slowly. The system EE is not affected by the rate demand constraint because the user’s minimum demand rate is small. However, as the minimum required rate increases, the system will use a larger transmission power to meet the user rate. At this time, the power consumption ratio is greater than the rate increase ratio, thus resulting in a decrease in the overall EE of the system (Fig. 7).

    Conclusions

    This thesis studies a heterogeneous VLC/RF network based on imperfect CSI. Under the conditions of maximum transmission power, system time slot, bandwidth, and minimum required rate, this thesis analyzes the transmission power of the VLC and RF systems and the transmission time of the VLC system. To maximize the EE of the system, a joint optimization with the RF system’s bandwidth allocation problem was performed. A corresponding model was created for the proposed optimization problem, and the objective function was then transformed into the form of parameter subtraction using the Dinkelbach method. The problem was then solved using the alternating optimization algorithm. The problem is decomposed into two subproblems; the locally optimal solution is obtained based on the Lagrangian duality principle, and the complexity of the proposed algorithm is analyzed. Simulations verify that the proposed algorithm has high EE and good robustness.

    Yanan Xin, Qilie Liu, Qian Liu, Qianbin Chen, Hongmei Xue, Ziyan Li, Kui Cheng. Robust Energy Efficiency Resource Allocation Algorithm for Heterogeneous VLC/RF Network Based on Bounded Channel State Information Uncertainty[J]. Chinese Journal of Lasers, 2022, 49(23): 2306003
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