Resource Allocatoion Optimization In Wireless Wideband Localization Networks

With the rapid development of wireless communication technology, reliable and accurate position estimation of “agent” nodes is essential for many wireless applications. In range-based localization techniques, the system accuracy, energy efficiency and network lifetime are affected by network topology, measuring environment and measuring method, and transmit power and signal bandwidth. In this paper, we take wideband positioning technology as the background, and resource allocation in wireless localization network as our main research topic. We can get the guidance for resource allocation optimization in wireless wideband localization networks by building the joint power and bandwidth allocation(JPBA) model. Through our analysis, the JPBA model is non-convex problems that cannot be solved directly, so we present an approximate method by optimization theory. The JPBA optimization model above is established on the real agents’ position which cannot be obtained directly in practical localization networks, and there must have localization variance between the measurements and real agents’ position. The JPBA based on the measurement results may have some uncontrollable factors. In this paper, we formulate a simple and robust JPBA model. It is possible to avoid uncontrolled resource allocation problem caused by the agent nodes’ inaccurate positions. The main work is listed below,First, this paper based on the theory of wireless wideband localization networks and signal propagation model is established on the TOA estimation as the background. We formulate the joint power and bandwidth allocation(JPBA) model in wireless wideband localization networks based on the square position error bound(SPEB), such as localization accuracy maximization model and the power consumption minimization model. We give a simple approximate method to solve the JPBA model based on the geometry programming theory.Second, As the lack of priori knowledge, uncertainty of the parameters of localization networks’ channel and the measurement errors in localization networks. The position of the agents through preliminary measurement we get there must exist in uncertainties between the real agents’ position. The optimal JPBA model described above is established based on the real position of the agent nodes do not have the robust property and will cause some uncontrollable consequences. Hence, we present the robust JPBA model when the agents’ position in uncertainties based on the far-field constraints. It will provide the robust resource allocation scheme when the uncertainty exists.Third, a lots of numerical formulation experiments are performed in our paper. From our numerical results, we found that the JPBA method performs much better than uniform allocation and pure power allocation on positioning and the efficiency of resource use of power. We also found that the optimal JPBA method will lost its positioning ability as the increase of uncertainty of the agents’ position, but the robust JPBA can avoid a dramatically decrease in positioning performance caused by the measurement error. The resource allocation model can provide guidance for practical positioning system designing.