Full-Duplex Wireless-Powered Communication Network with Energy Causality (1404.0471v1)

Abstract: In this paper, we consider a wireless communication network with a full-duplex hybrid access point (HAP) and a set of wireless users with energy harvesting capabilities. The HAP implements the full-duplex through two antennas: one for broadcasting wireless energy to users in the downlink and one for receiving independent information from users via time-division-multiple-access (TDMA) in the uplink at the same time. All users can continuously harvest wireless power from the HAP until its transmission slot, i.e., the energy causality constraint is modeled by assuming that energy harvested in the future cannot be used for tranmission. Hence, latter users' energy harvesting time is coupled with the transmission time of previous users. Under this setup, we investigate the sum-throughput maximization (STM) problem and the total-time minimization (TTM) problem for the proposed multi-user full-duplex wireless-powered network. The STM problem is proved to be a convex optimization problem. The optimal solution strategy is then obtained in closed-form expression, which can be computed with linear complexity. It is also shown that the sum throughput is non-decreasing with increasing of the number of users. For the TTM problem, by exploiting the properties of the coupling constraints, we propose a two-step algorithm to obtain an optimal solution. Then, for each problem, two suboptimal solutions are proposed and investigated. Finally, the effect of user scheduling on STM and TTM are investigated through simulations. It is also shown that different user scheduling strategies should be used for STM and TTM.

• The paper presents the sum-throughput maximization problem as convex, deriving an optimal time allocation showing throughput increases monotonically with the number of users.
• For the total-time minimization problem, the authors propose a two-step algorithm and find that users with high signal-to-noise ratios should transmit first.
• Suboptimal strategies are introduced for both problems, demonstrating significant performance improvements and validating the importance of optimization for system performance.

Overview of Full-Duplex Wireless-Powered Communication Networks with Energy Causality

The paper explores a unique aspect of wireless communication networks—a full-duplex wireless-powered communication network (WPCN) endowed with energy causality. This research explores a model that incorporates a hybrid access point (HAP) and multiple users, all equipped with energy harvesting capabilities. The system employs time-division multiple access (TDMA) for efficient uplink information transmission, all while enabling continuous energy harvesting by users until their respective transmission slots. The approach tackles two fundamental optimization problems: sum-throughput maximization (STM) and total-time minimization (TTM).

Key Contributions and Findings

1. Convex Optimization in STM: The authors present the STM problem as a convex optimization problem, successfully deriving a closed-form optimal time allocation strategy. By leveraging convex optimization techniques, they demonstrate that the throughput increases monotonically with the number of users—a noteworthy insight given the constraints of a fixed total time. This signifies that the system's potential can be maximized by strategically increasing the user count.
2. Coupled Constraint Resolution in TTM: The TTM problem is approached by exploiting the properties of coupling constraints among users' energy harvesting and transmission times. A novel two-step algorithm is proposed, which efficiently finds the optimal solution despite the complexities introduced by the constraints. Interestingly, the results suggest that users with high signal-to-noise ratios (SNRs) should transmit first to minimize total charging and transmission time.
3. Suboptimal Strategies: The paper proposes two suboptimal strategies for each optimization problem, designed to offer less complex yet effective solutions. For STM, the suboptimal approaches include equal time allocation and fixed-TDMA allocation, while for TTM, the authors suggest equal time assignments and tangent-point allocations. These suboptimal solutions not only offer significant performance improvements but also validate the importance of optimization in enhancing system performance.
4. Practical Implications and Future Directions: The findings underline the importance of efficient scheduling in maximizing network throughput and minimizing data collection time. Importantly, the paper highlights the necessity of employing different scheduling strategies for STM and TTM, suggesting tailored approaches based on specific network demands. Future research could build upon this by investigating the impact of dynamic channel conditions or user mobility and extending the model to networks with heterogeneous user capacities or demands.

Numerical Insights

The simulated scenarios offer quantitative backing to the theoretical claims. A highlighted numerical result shows that with an increase in HAP transmit power, system throughput consistently rises, substantiating the capacity for high throughput with optimized time allocation. Evidently, the benefits of scheduling become even more pronounced as the number of users grows and HAP power increases.

Conclusion

This paper provides a substantial contribution to the understanding of full-duplex WPCNs with energy causality constraints. It lays the groundwork for future exploration into more complex wireless communication scenarios where energy harvesting is a core component. The incorporation of dual-function HAPs paves the way for more resilient and efficient networks, key to sustaining the ever-growing demand for robust wireless communication solutions. The techniques presented hold promise for advancing how we conceive wireless communication network designs, offering both strategic insights and practical applications.