[Paper Review] Cognitive Energy Harvesting and Transmission from a Network Perspective

Seunghyun Lee, Kaibin Huang+1 more|arXiv (Cornell University)|Sep 16, 2012

Energy Harvesting in Wireless Networks9 references4 citations

TL;DR

This paper proposes a cognitive radio network where secondary transmitters (STs) harvest energy from primary transmitters' (PTs) RF signals and transmit only when outside PT guard zones. Using a stochastic-geometry model with independent Poisson point processes, it derives closed-form expressions for maximum spatial throughput under outage constraints, showing that secondary throughput decreases linearly with PT density and optimal ST density is inversely proportional to ST transmission probability.

ABSTRACT

Wireless networks can be self-sustaining by harvesting energy from radio-frequency (RF) signals. Building on classic cognitive radio networks, we propose a novel method for network coexisting where mobiles from a secondary network, called secondary transmitters (STs), either harvest energy from transmissions by nearby transmitters from a primary network, called primary transmitters (PTs), or transmit information if PTs are sufficiently far away; STs store harvested energy in rechargeable batteries with finite capacity and use all available energy for subsequent transmission when batteries are fully charged. In this model, each PT is centered at a guard zone and a harvesting zone that are disks with given radiuses; a ST harvests energy if it lies in some harvesting zone, transmits fixed-power signals if it is outside all guard zones or else idles. Based on this model, the spatial throughput of the secondary network is maximized using a stochastic-geometry model where PTs and STs are modeled as independent homogeneous Poisson point processes (HPPPs), under the outage constraints for coexisting networks and obtained in a simple closed-form. It is observed from the result that the maximum secondary throughput decreases linearly with the growing PT density, and the optimal ST density is inversely proportional to the derived transmission probability for STs.

Motivation & Objective

• To enable self-sustaining secondary networks by harvesting RF energy from primary transmissions.
• To model coexistence between primary and secondary networks using spatial stochastic processes.
• To maximize the spatial throughput of the secondary network under outage constraints for both networks.
• To derive closed-form expressions for optimal transmission power and node density in the secondary network.
• To analyze the trade-off between secondary network performance and primary network protection via guard zones.

Proposed method

• Model PTs and STs as independent homogeneous Poisson point processes (HPPPs) in a 2D plane.
• Define guard zones (radius $ r_g $) around each PT to protect primary transmissions and harvesting zones (radius $ r_h $) for energy collection.
• Use Markov-chain theory to derive the transmission probability $ p_t $ of STs based on their spatial distribution relative to PTs.
• Apply Poisson approximation to model the spatial distribution of active STs and compute secondary network throughput.
• Formulate outage constraints for both primary and secondary networks using signal-to-interference-plus-noise ratio (SINR) thresholds.
• Optimize secondary transmission power $ P_s $ and ST density $ λ_s $ to maximize spatial throughput under energy harvesting and interference constraints.

Experimental results

Research questions

• RQ1 How does the spatial distribution of PTs and STs affect the achievable throughput of a secondary network powered by RF energy harvesting?
• RQ2 What is the optimal balance between ST density and transmission power to maximize secondary network throughput under primary network outage constraints?
• RQ3 How does increasing PT density impact the maximum achievable secondary network throughput?
• RQ4 Under what conditions does the secondary network throughput become limited by primary network protection rather than energy availability?
• RQ5 What is the analytical relationship between the optimal ST density and the transmission probability of STs?

Key findings

• The maximum secondary spatial throughput $ \mathcal{C}_s^* $ decreases linearly with increasing PT density $ \lambda_p $, indicating a direct trade-off between primary network density and secondary performance.
• The optimal ST density $ \lambda_s^* $ is inversely proportional to the secondary transmission probability $ p_t $, implying that higher ST activity requires lower ST density to maintain system stability.
• When harvesting efficiency $ \eta $ and $ r_h^{-\alpha} $ are sufficiently large, the optimal $ \lambda_s^* $ is determined by the intersection of constraints from primary and secondary outage probabilities.
• If $ \eta r_h^{-\alpha} < \frac{\theta_s}{\theta_p} \left( \frac{\mu_s}{\mu_p} \right)^{-\alpha/2} $, the secondary outage constraint is the bottleneck, and $ \lambda_s^* $ is limited by secondary network requirements.
• Numerical results confirm that the analytical approximations for outage probability closely match simulation results, validating the model's accuracy under realistic parameters.
• As $ \lambda_p \to 0 $, $ \mathcal{C}_s^* $ approaches its theoretical maximum, but $ \lambda_s^* \to \infty $, indicating that sparse PT deployment requires impractically dense ST deployment to achieve peak throughput.