A Sum-Utility Maximization Approach for Fairness Resource Allocation in Wireless Powered Body Area Networks

Abstract

Wireless body area networks (WBANs) are essential for monitoring physiological signals of the human body, but the lifetime of WBANs is limited by battery longevity and it is not convenient or feasible for replacing the batteries of the sensors. The newly emerged energy-harvesting technology provides the potential to break the battery limitation of WBANs. However, the radio resource of a WBAN should be carefully scheduled for the wireless power transfer links and wireless information transmission links; otherwise, severely unfair resource allocation could be incurred due to the difference of channel qualities of the sensors. In this paper, we propose a marginal utility theoretic method to allocate the radio resource to the on-/in-body sensors in a fair and efficient manner. Especially, we consider that the sensors are wireless powered by multiple pre-installed radio-frequency energy sources. First, the utility function for a sensor node is proposed, which can map the achievable throughput to a satisfaction level of network QoS. Then, the fairness resource allocation among the sensor nodes is modeled as a sum-utility maximization problem. By using the dual decomposition method, the optimal solution to the proposed problem can finally be solved in the closed form. In comparison with the sum-throughput maximization and common-throughput maximization methods, the simulation results show that the proposed sum-utility maximization method can bring a fair throughput allocation for the sensors with different channel conditions, and the performance loss to the sum-throughput maximization method is small, while the sum-throughput maximization method is extremely unfair. INDEX TERMS Wireless body area networks, wireless power transfer, utility theory, convex optimization.

Minimum Length Scheduling for Multi-Cell Full Duplex Wireless Powered Communication Networks

“…To increase the energy harvesting rate of such networks, the usage of multiple energy transmitters is investigated in [ 9 , 10 , 11 ]. Particularly, [ 9 ] studied the time allocation and load balancing for the throughput maximization, [ 10 ] provided the implementation of a test-bed to maximize the amount of harvested energy, and [ 11 ] investigated a wireless body area network with the objective of maximizing the sum throughput.…”

“…To increase the energy harvesting rate of such networks, the usage of multiple energy transmitters is investigated in [ 9 , 10 , 11 ]. Particularly, [ 9 ] studied the time allocation and load balancing for the throughput maximization, [ 10 ] provided the implementation of a test-bed to maximize the amount of harvested energy, and [ 11 ] investigated a wireless body area network with the objective of maximizing the sum throughput. Furthermore, to increase the network coverage, multi-cell WPCN, in which multiple HAPs are used for both energy transmission and information reception, were investigated for minimum throughput maximization [ 12 ] and throughput maximization through beam-forming [ 13 ].…”

Throughput Maximization by Time Switching in Multipoint WBAN With Fairness Consideration

“…Similarly, the novel relay selection protocol and the optimized power splitting on maximum ratio combining (MRC) protocol are proposed to minimum outage and maximize sum-throughput with relay cooperative networks, respectively [18]. In [19], the authors are committed to optimizing the system utility function to improve network quality of service (QoS) and the fairness resource allocation through the theoretical method of marginal utility. Spectrum resources are an important performance indicator of WBANs.…”

Validation of Wired and Wireless Interconnected Body Sensor Networks

“…Power efficiency is the most important factor for WBSN because of the fact that the sensor nodes are not only smaller in size but also have limited battery life [10,11]. Different techniques for reducing the power levels have been discussed in References [12,13,14,15,16,17,18,19,20,21,22,23] for WBSN. The goal is to keep a low radio power level for transmission and reception which is not only safe for human body, efficient for network protocols and also save battery life.…”