Nonconvex

传感器网络中基于到达时间差有效的凸松弛方法的稳健定位

We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this Nonconvex optimization problem.We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.

标签： 传感器网络

上传时间： 2016-11-27

上传用户：xxmluo
Utility Maximization in Nonconvex Wireless Systems

Once upon a time, cellular wireless networks provided two basic services: voice telephony and low-rate text messaging. Users in the network were separated by orthogonal multiple access schemes, and cells by generous frequency reuse patterns [1]. Since then, the proliferation of wireless services, fierce competition, andthe emergenceof new service classes such as wireless data and multimediahave resulted in an ever increasing pressure on network operators to use resources in a moreefficient manner.In the contextof wireless networks,two of the most common resources are power and spectrum—and, due to regulations, these resources are typically scarce. Hence, in contrast to wired networks, overprovisioning is not feasible in wireless networks.

标签： Maximization Nonconvex Wireless Utility Systems in

上传时间： 2020-06-01

上传用户：shancjb