Information and Energy Cooperation in Cognitive Radio Networks (1403.5648v1)

Abstract: Cooperation between the primary and secondary systems can improve the spectrum efficiency in cognitive radio networks. The key idea is that the secondary system helps to boost the primary system's performance by relaying and in return the primary system provides more opportunities for the secondary system to access the spectrum. In contrast to most of existing works that only consider information cooperation, this paper studies joint information and energy cooperation between the two systems, i.e., the primary transmitter sends information for relaying and feeds the secondary system with energy as well. This is particularly useful when the secondary transmitter has good channel quality to the primary receiver but is energy constrained. We propose and study three schemes that enable this cooperation. Firstly, we assume there exists an ideal backhaul between the two systems for information and energy transfer. We then consider two wireless information and energy transfer schemes from the primary transmitter to the secondary transmitter using power splitting and time splitting energy harvesting techniques, respectively. For each scheme, the optimal and zero-forcing solutions are derived. Simulation results demonstrate promising performance gain for both systems due to the additional energy cooperation. It is also revealed that the power splitting scheme can achieve larger rate region than the time splitting scheme when the efficiency of the energy transfer is sufficiently large.

• The paper introduces dual cooperation schemes that integrate energy harvesting with information relay.
• It details power splitting and time splitting mechanisms, with power splitting achieving superior secondary user rates.
• Simulation results show a significant expansion in the achievable rate region for both primary and secondary systems.

Information and Energy Cooperation in Cognitive Radio Networks: An Overview

The paper "Information and Energy Cooperation in Cognitive Radio Networks" by Gan Zheng et al. addresses a pertinent topic in cognitive radio systems, focusing on enhancing spectrum efficiency through strategic collaboration between primary and secondary networks. While most existing research primarily considers information exchange for such cooperation, this paper introduces a novel perspective by examining the potential benefits of joint information and energy cooperation.

Key Contributions

The paper explores three distinct cooperation schemes between primary and secondary systems:

1. Ideal Cooperation: This involves a scenario where the secondary system has access to non-causal information about the primary signal, combined with direct energy sharing via cable. Although not practical, this model serves as a theoretical benchmark, providing a performance upper bound.
2. Power Splitting Scheme: Under this paradigm, the secondary system employs a power splitting mechanism to simultaneously relay primary information and harvest energy from the RF signals transmitted by the primary system. This method enables the secondary system to acquire additional power to aid in its transmission processes, effectively mitigating its energy constraints.
3. Time Splitting Scheme: Here, the secondary system dedicates part of the communication time to energy harvesting and the remainder for information relay. By adapting time slots specifically for energy and information tasks, this approach synchronizes usage phases efficiently but tends to offer less flexibility compared to power splitting.

Numerical Results and Insights

The paper presents simulation results that highlight substantial performance improvements for both primary and secondary systems when additional energy cooperation is employed. Specifically:

• The proposed energy cooperation schemes significantly increase the achievable rate region compared to traditional information-only cooperative methods.
• Among practical schemes, power splitting consistently outperforms time splitting in terms of achievable SU rate, especially when the efficiency of energy transfer is sufficiently high.
• The feasibility of each cooperation scheme and respective optimization approaches is thoroughly analyzed to ensure realistic applicability in cognitive radio networks. The research also provides closed-form solutions based on Zero-Forcing (ZF) criteria to offer simplified insights into system parameters.

Theoretical and Practical Implications

The integration of energy cooperation into cognitive radio systems presents theoretical advancement by redefining cooperation paradigms to accommodate energy exchange alongside information sharing. Practically, such cooperation can manifest as a win-win strategy for systems operating in environments typically characterized by energy constraints, such as wireless sensor networks or specific indoor applications.

By facilitating energy harvesting capabilities, secondary systems can enhance their operational capabilities without compromising their primary objectives. This offers an incentivized model for participation in spectrum sharing agreements, potentially transforming how cognitive radio networks approach efficiency optimization.

Future Directions

The findings raise several avenues for future research:

• Further exploring hybrid schemes that blend both power and time splitting approaches could yield even more efficient cooperation paradigms, particularly if adaptive mechanisms are introduced based on real-time network conditions.
• Investigations into the security implications of joint information and energy transfer, considering potential vulnerabilities introduced by this dual-mode operation.
• Practical deployments in real-world scenarios could leverage energy cooperation to reduce operational costs, enhance QoS for secondary users, and streamline spectrum utilization across diverse network setups.

In conclusion, the paper delivers a comprehensive exploration into augmented cognitive radio cooperation, proposing energy as a critical component in achieving enhanced network performance. This dual-faceted approach is poised to influence the design and implementation of next-generation cognitive networks, fostering a more symbiotic relationship between system actors.