Wireless Information and Power Transfer: Energy Efficiency Optimization in OFDMA Systems (1303.4006v2)

Abstract: This paper considers orthogonal frequency division multiple access systems with simultaneous wireless information and power transfer. We study the resource allocation algorithm design for maximization of the energy efficiency of data transmission. In particular, we focus on power splitting hybrid receivers which are able to split the received signals into two power streams for concurrent information decoding and energy harvesting. Two scenarios are investigated considering different power splitting abilities of the receivers. In the first scenario, we assume receivers which can split the received power into a continuous set of power streams with arbitrary power splitting ratios. In the second scenario, we examine receivers which can split the received power only into a discrete set of power streams with fixed power splitting ratios. In both scenarios, we formulate the corresponding algorithm design as a non-convex optimization problem which takes into account the circuit power consumption, the minimum data rate requirements of delay constrained services, the minimum required system data rate, and the minimum amount of power that has to be delivered to the receivers. Subsequently, by exploiting fractional programming and dual decomposition, suboptimal iterative resource allocation algorithms are proposed to solve the non-convex problems. Simulation results illustrate that the proposed iterative resource allocation algorithms approach the optimal solution within a small number of iterations and unveil the trade-off between energy efficiency, system capacity, and wireless power transfer.

• The paper introduces a novel power splitting receiver design that enables simultaneous information decoding and energy harvesting to boost efficiency in OFDMA systems.
• It employs fractional programming and dual decomposition to solve a non-convex resource allocation problem while balancing data rate and power constraints.
• Simulation results demonstrate that leveraging interference for energy harvesting and managing system trade-offs significantly enhances overall performance.

Energy Efficiency Optimization in Wireless OFDMA Systems with Power Transfer

The paper addresses a critical issue in modern OFDMA (Orthogonal Frequency Division Multiple Access) systems — optimizing energy efficiency in the context of simultaneous wireless information and power transfer. Researchers Derrick Wing Kwan Ng, Ernest S. Lo, and Robert Schober dive into the engineering of resource allocation within such systems, acknowledging the increasing demand for high data rates and sustainable mobile communication infrastructures.

Key Contributions

The paper's primary focus is on power splitting hybrid receivers capable of dividing incoming signals into multiple power streams, enabling concurrent information decoding and energy harvesting. This dual-functionality tackles a significant challenge: managing the power consumption discrepancies between the transmitter and the limited-energy-supply receivers, i.e., mobile devices with constrained battery life.

Two scenarios are considered:

1. Continuous Power Splitting Ratios: This scenario assumes receivers can optimally adjust their power splitting ratios over a continuous range.
2. Discrete Power Splitting Ratios: Here, receivers are limited to selecting from a finite set of power splitting ratios, a more realistic assumption for practical deployments due to hardware constraints.

Methodology and Solutions

The authors model this allocation challenge as a non-convex optimization problem, taking into account critical factors such as:

• Minimum data rate requirements
• System-wide data rate expectations
• Circuit power consumption constraints
• Minimum power transfer requirements

To solve the non-convexity of the problem, they employ fractional programming and dual decomposition techniques. Iterative algorithms are developed and shown through simulations to approach an optimal solution efficiently in a manageable number of iterations.

Findings and Implications

Simulation results highlight important insights:

• Energy Harvesting Gains: Wireless power transfer significantly boosts energy efficiency, especially in interference-rich environments, as interference can be leveraged as an energy source.
• System Trade-offs: While additional receivers can enhance system capacity through multiuser diversity, this does not directly translate to increased energy efficiency. The system's energy gains approach saturation at higher transmit power levels due to diminishing returns as most of the beneficial power-splitting allocations are achieved.

These insights have profound implications:

• System Design: Suggests an adaptable approach in designing OFDMA systems, balancing between maximizing data throughput and minimizing energy usage.
• Hardware Development: Encourages advancements in energy harvesting circuits and strategies to improve the conversion efficiency of RF signals to usable energy.

Future Directions

The paper lays the groundwork for future investigations into more complex and variable communication environments. There's potential to explore adaptive algorithms that dynamically adjust power splitting depending on real-time channel conditions and device mobility patterns. Furthermore, integrating machine learning techniques to predict optimal resource allocation strategies could significantly improve system performance and adaptability.

In summary, this paper contributes a detailed mathematical and algorithmic framework for enhancing energy efficiency in OFDMA systems, bearing relevance for the future of sustainable wireless networks and the development of energy-self-sufficient mobile devices.