Sunday 02 February 2025
The quest for efficient wireless communication has led researchers to explore innovative techniques, and one such approach is simultaneous wireless information and power transfer (SWIPT). This technology allows devices to harvest energy while receiving data, reducing the need for battery replacements or recharging. However, optimizing SWIPT in multiuser scenarios poses significant challenges.
A recent study tackled this problem by developing a dynamic grouping mechanism that schedules users to receive either information or energy, depending on their needs and availability. The researchers created a mathematical framework to optimize the transmission covariance matrices, taking into account various constraints such as power limits and data rates.
The team’s approach involves dividing users into groups based on their battery levels and data requirements. They then use a scheduling algorithm to allocate resources among these groups, ensuring that each user receives either information or energy during its designated time slot. The researchers also proposed three different algorithms for implementing this mechanism: RR-SF (round-robin-based), Ra-SF (random-based), and LB-SF (least battery level-based).
Simulation results demonstrated the effectiveness of the proposed approach in achieving efficient SWIPT. In scenarios with varying numbers of users, distance to the base station, and relative sizes of harvesting user groups, the algorithms consistently outperformed a baseline scenario without SWIPT.
One notable finding was that the LB-SF algorithm performed best in terms of both system sum rate and harvested power, particularly when the number of users increased. This is likely due to its ability to adapt to changing battery levels and data requirements.
The researchers also investigated the impact of distance to the base station on SWIPT performance. They found that as the distance increased, the expected system sum rate decreased, but the sum of harvested powers by all users remained relatively constant.
In addition, the team analyzed the effect of varying the relative size of the harvesting user group on system performance. They discovered that increasing the proportion of harvesting users led to a decrease in system sum rate but an increase in harvested power.
The computational complexities of each algorithm were also evaluated. The results showed that LB-SF/CHS-F required the least amount of computational resources, making it a more practical choice for implementation.
While SWIPT still faces several challenges before becoming a reality, this study provides valuable insights into optimizing its performance in multiuser scenarios. As wireless communication technology continues to evolve, researchers will likely explore new ways to harness energy while transmitting data, paving the way for more efficient and sustainable communication systems.
Cite this article: “Optimizing Simultaneous Wireless Information and Power Transfer in Multiuser Scenarios”, The Science Archive, 2025.
Swipt, Wireless Power Transfer, Simultaneous Information And Energy Transfer, Multiuser Optimization, Dynamic Grouping, Transmission Covariance Matrices, Power Limits, Data Rates, Scheduling Algorithm, Harvesting User Groups.
