Throughput Maximization in Wireless Powered Communication Networks (1304.7886v4)

Abstract: This paper studies the newly emerging wireless powered communication network (WPCN) in which one hybrid access point (H-AP) with constant power supply coordinates the wireless energy/information transmissions to/from distributed users that do not have energy sources. A "harvest-then-transmit" protocol is proposed where all users first harvest the wireless energy broadcast by the H-AP in the downlink (DL) and then send their independent information to the H-AP in the uplink (UL) by time-division-multiple-access (TDMA). First, we study the sum-throughput maximization of all users by jointly optimizing the time allocation for the DL wireless power transfer versus the users' UL information transmissions given a total time constraint based on the users' DL and UL channels as well as their average harvested energy values. By applying convex optimization techniques, we obtain the closed-form expressions for the optimal time allocations to maximize the sum-throughput. Our solution reveals "doubly near-far" phenomenon due to both the DL and UL distance-dependent signal attenuation, where a far user from the H-AP, which receives less wireless energy than a nearer user in the DL, has to transmit with more power in the UL for reliable information transmission. Consequently, the maximum sum-throughput is achieved by allocating substantially more time to the near users than the far users, thus resulting in unfair rate allocation among different users. To overcome this problem, we furthermore propose a new performance metric so-called common-throughput with the additional constraint that all users should be allocated with an equal rate regardless of their distances to the H-AP. We present an efficient algorithm to solve the common-throughput maximization problem. Simulation results demonstrate the effectiveness of the common-throughput approach for solving the new doubly near-far problem in WPCNs.

• The paper demonstrates a harvest-then-transmit protocol that maximizes sum-throughput using convex optimization techniques.
• It identifies the doubly near-far problem, where users closer to the H-AP benefit disproportionately from energy transfer.
• The study introduces a common-throughput maximization method to ensure balanced rate allocation among all users.

Throughput Maximization in Wireless Powered Communication Networks

The paper by Hyungsik Ju and Rui Zhang presents a comprehensive paper on throughput optimization in Wireless Powered Communication Networks (WPCNs). The authors propose a "harvest-then-transmit" protocol where a hybrid access point (H-AP) with a continuous power supply facilitates both energy transfer in the downlink (DL) and information transfer in the uplink (UL) to a set of distributed users devoid of other energy sources. The protocol's performance is evaluated in terms of sum-throughput and common-throughput, with notable findings concerning the "doubly near-far" problem inherent in such networks.

Protocol Overview and Problem Formulation

The "harvest-then-transmit" protocol operates in two phases: during the first phase, users harvest energy from the H-AP's wireless energy broadcast in the DL, which is then used for information transmission to the H-AP in the UL during the second phase. The UL transmissions are coordinated through time-division-multiple-access (TDMA).

The main objective is to maximize the sum-throughput of all users under a total transmission time constraint. The authors employ convex optimization techniques to jointly optimize the DL and UL time allocations, obtaining closed-form expressions for the optimal allocations. This analysis reveals a critical insight: the sum-throughput maximization inherently leads to a "doubly near-far" problem due to signal attenuation in both DL and UL. Users farther from the H-AP, receiving less DL energy, must compensate by transmitting with greater power in the UL. Consequently, the optimal time allocation favors users nearer to the H-AP, leading to substantial throughput disparities among users.

Sum-Throughput Maximization

The sum-throughput maximization problem is formalized as a convex optimization task:

$$(\text{P1}): \quad \underset{\boldsymbol{\tau}}{\text{maximize}} \quad R_{\text{sum}}(\boldsymbol{\tau}) = \sum_{i=1}^K R_i (\boldsymbol{\tau}) \quad \text{s.t.} \quad \sum_{i=0}^K \tau_i \le 1, \quad \tau_i \ge 0.$$

By solving this problem, the optimal time allocations for both DL and UL phases are obtained. The results conclusively reflect the "doubly near-far" phenomenon: optimal time allocation is non-uniform and biased towards users closer to the H-AP to maximize the sum-throughput.

Addressing the Doubly Near-Far Problem: Common-Throughput Maximization

To address the unfairness in throughput distribution, the authors propose a common-throughput maximization approach, which ensures equal rate allocation to all users, irrespective of their proximity to the H-AP. The corresponding optimization problem is:

$$(\text{P2}): \quad \underset{\bar{R}, \boldsymbol{\tau}}{\text{maximize}} \quad \bar{R} \quad \text{s.t.} \quad R_i (\boldsymbol{\tau}) \ge \bar{R}, \quad i = 1, \cdots, K, \quad \boldsymbol{\tau} \in \mathcal{D}.$$

An efficient algorithm is devised to solve this problem, ensuring that each user achieves the same throughput, leading to a more balanced rate allocation. Simulation results affirm the efficacy of this approach in mitigating the doubly near-far problem.

Practical Implications and Future Directions

The findings have significant practical implications for the deployment and design of WPCNs, particularly in scenarios where fairness among users is crucial, such as sensor networks distributed in varying proximities to a central access point. The paper further illuminates fundamental trade-offs between maximizing sum-throughput and ensuring fairness, which must be balanced based on specific application requirements.

Potential future work could explore adaptive protocols that dynamically balance between sum-throughput and fair rate allocation, taking real-time channel conditions and user requirements into account. Additionally, extending the analysis to multi-antenna systems and investigating the impacts of more complex channel dynamics would be valuable.

Conclusion

The paper elucidates key aspects of throughput maximization in WPCNs, presenting both theoretical insights and practical solutions. By addressing the doubly near-far problem via common-throughput maximization, the authors contribute significantly to the understanding and improvement of WPCN performance, laying the groundwork for further advancements in this domain.