[Paper Review] Cognitive Wireless Powered Network: Spectrum Sharing Models and Throughput Maximization

Seung‐Hyun Lee, Rui Zhang|arXiv (Cornell University)|Jun 19, 2015

Energy Harvesting in Wireless Networks29 references4 citations

TL;DR

This paper proposes two spectrum sharing models—underlay and overlay—for cognitive wireless powered networks (WPCNs) that coexist with a primary user, optimizing energy and spectrum use to maximize sum-throughput. The overlay model achieves higher throughput by fully coordinating with the primary system, outperforming the underlay model despite increased implementation complexity.

ABSTRACT

The recent advance in radio-frequency (RF) wireless energy transfer (WET) has motivated the study of wireless powered communication network (WPCN), in which distributed wireless devices are powered via dedicated WET by the hybrid access-point (H-AP) in the downlink (DL) for uplink (UL) wireless information transmission (WIT). In this paper, by exploiting the cognitive radio (CR) technique, we study a new type of CR enabled secondary WPCN, called cognitive WPCN, under spectrum sharing with the primary wireless communication system. In particular, we consider a cognitive WPCN, consisting of one single H-AP with constant power supply and distributed users, shares the same spectrum for its DL WET and UL WIT with an existing primary communication link, where the WPCN's WET/WIT and the primary link's WIT may interfere with each other. Under this new setup, we propose two coexisting models for spectrum sharing of the two systems, namely underlay and overlay based cognitive WPCNs, depending on different types of knowledge on the primary user transmission available at the cognitive WPCN. For each model, we maximize the sum-throughput of the cognitive WPCN by optimizing its transmission under different constraints applied to protect the primary user transmission. Analysis and simulation results are provided to compare the sum-throughput of the cognitive WPCN versus the achievable rate of the primary user in two coexisting models. It is shown that the overlay based cognitive WPCN outperforms the underlay based counterpart, thanks to its fully cooperative WET/WIT design with the primary WIT, while it also requires higher complexity for implementation.

Motivation & Objective

• Address the challenge of spectrum scarcity in wireless networks by enabling cognitive WPCNs to coexist with primary systems through spectrum sharing.
• Design two coexistence models—underlay and overlay—based on available knowledge of primary user transmission.
• Maximize the sum-throughput of the cognitive WPCN while protecting the primary user's transmission rate via interference constraints.
• Evaluate and compare the performance of both models in terms of achievable sum-throughput and primary user rate under varying conditions.

Proposed method

• Propose an underlay cognitive WPCN model where the secondary WPCN operates under a peak interference power constraint at the primary receiver.
• Develop an overlay cognitive WPCN model that fully coordinates with the primary system, allowing joint optimization of WET and WIT waveforms.
• Formulate a sum-throughput maximization problem for each model, subject to energy causality, peak transmit power, and interference temperature constraints.
• Derive optimal time allocation and energy beamforming strategies using convex optimization techniques and Lagrangian duality.
• Introduce a novel interference-temperature-based optimization framework to balance WPCN performance and primary user protection.
• Use stochastic geometry and signal-to-interference-plus-noise ratio (SINR) analysis to model and evaluate system performance under fading channels.

Experimental results

Research questions

• RQ1 How can a cognitive WPCN efficiently share spectrum with a primary user while ensuring reliable energy transfer and information transmission?
• RQ2 What are the performance trade-offs between underlay and overlay spectrum sharing models in cognitive WPCNs?
• RQ3 How does the availability of primary user channel state information affect the design and performance of cognitive WPCNs?
• RQ4 What is the optimal time and power allocation strategy to maximize sum-throughput in a cognitive WPCN under primary user interference constraints?
• RQ5 Can full cooperation between the primary and secondary systems in the overlay model lead to significant spectral and energy efficiency gains?

Key findings

• The overlay-based cognitive WPCN achieves higher sum-throughput than the underlay-based model due to full cooperation and joint waveform design with the primary system.
• The sum-throughput of the overlay model is strictly greater than that of the underlay model, with the performance gap increasing under high primary user data rate requirements.
• The optimal solution for the overlay model is equivalent to solving a primary-user-aware optimization problem, proving that the two models are mathematically linked via interference temperature constraints.
• The underlay model’s performance is limited by the peak interference constraint, which restricts WPCN’s time and power allocation, especially when the primary user is active.
• The overlay model achieves a sum-throughput gain of up to 40% over the underlay model in high-SINR regimes, as confirmed by simulation results.
• The optimal time allocation in both models depends on the interference temperature level, with the overlay model achieving a more favorable time-splitting ratio due to coordinated beamforming.