14 research outputs found
Robust Power Allocation for Energy-Efficient Location-Aware Networks
In wireless location-aware networks, mobile nodes (agents) typically obtain their positions using the range measurements to the nodes with known positions. Transmit power allocation not only affects network lifetime and throughput, but also determines localization accuracy. In this paper, we present an optimization framework for robust power allocation in network localization with imperfect knowledge of network parameters. In particular, we formulate power allocation problems to minimize localization errors for a given power budget and show that such formulations can be solved via conic programming. Moreover, we design a distributed power allocation algorithm that allows parallel computation among agents. The simulation results show that the proposed schemes significantly outperform uniform power allocation, and the robust schemes outperform their non-robust counterparts when the network parameters are subject to uncertainty.National Natural Science Foundation (China) (Project 61201261)National Basic Research Program of China (973 Program) (61101131)University Grants Committee (Hong Kong, China) (GRF Grant Project 419509)National Science Foundation (U.S.) (Grant ECCS-0901034)United States. Office of Naval Research (Grant N00014-11-1-0397)Massachusetts Institute of Technology. Institute for Soldier Nanotechnologie
5G Downlink Multi-Beam Signal Design for LOS Positioning
In this work, we study optimal transmit strategies for minimizing the
positioning error bound in a line-of-sight scenario, under different levels of
prior knowledge of the channel parameters. For the case of perfect prior
knowledge, we prove that two beams are optimal, and determine their beam
directions and optimal power allocation. For the imperfect prior knowledge
case, we compute the optimal power allocation among the beams of a codebook for
two different robustness-related objectives, namely average or maximum squared
position error bound minimization. Our numerical results show that our
low-complexity approach can outperform existing methods that entail higher
signaling and computational overhead.Comment: accepted for publication at IEEE GLOBECOM 201
A Review on suboptimal power allocation schemes for WSN localization
This paper considers a review of two proposed power allocation algorithms for increasing accuracy in localization scenarios, a deeper theoretical analysis and a detailed performance comparison. Appropriate power allocation (PA) among beacons is an effective tool to implement localization with improved precision. At first, a brief review on existing optimal PA strategies is presented. Subsequently, the first PA algorithm is discussed: a function called uncertainty area is defined according to the interaction of beacons in a pair-wise selection procedure.
A general selection strategy among allocated transmission powers for each beacon completes the algorithm structure. In the literature, on one hand the commonly made assumption about ranging measures is that their ideal values are equal to their corresponding Cramer-Rao bounds but, on the other hand, at high signal-to-noise ratios, real ranging estimators are characterized by different lower limits on their performance, mainly as a result of maximum sampling rates and computational load available in the sensors. The second PA algorithm develops a type of adaptive PA (APA) directly based on measured SNRs and, consequently, much simpler than other techniques
Power Optimization for Network Localization
Reliable and accurate localization of mobile objects is essential for many
applications in wireless networks. In range-based localization, the position of
the object can be inferred using the distance measurements from wireless
signals exchanged with active objects or reflected by passive ones. Power
allocation for ranging signals is important since it affects not only network
lifetime and throughput but also localization accuracy. In this paper, we
establish a unifying optimization framework for power allocation in both active
and passive localization networks. In particular, we first determine the
functional properties of the localization accuracy metric, which enable us to
transform the power allocation problems into second-order cone programs
(SOCPs). We then propose the robust counterparts of the problems in the
presence of parameter uncertainty and develop asymptotically optimal and
efficient near-optimal SOCP-based algorithms. Our simulation results validate
the efficiency and robustness of the proposed algorithms.Comment: 15 pages, 7 figure
Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition
This paper studies joint beamforming and power control in a coordinated
multicell downlink system that serves multiple users per cell to maximize the
minimum weighted signal-to-interference-plus-noise ratio. The optimal solution
and distributed algorithm with geometrically fast convergence rate are derived
by employing the nonlinear Perron-Frobenius theory and the multicell network
duality. The iterative algorithm, though operating in a distributed manner,
still requires instantaneous power update within the coordinated cluster
through the backhaul. The backhaul information exchange and message passing may
become prohibitive with increasing number of transmit antennas and increasing
number of users. In order to derive asymptotically optimal solution, random
matrix theory is leveraged to design a distributed algorithm that only requires
statistical information. The advantage of our approach is that there is no
instantaneous power update through backhaul. Moreover, by using nonlinear
Perron-Frobenius theory and random matrix theory, an effective primal network
and an effective dual network are proposed to characterize and interpret the
asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on
Wireless Communications are correcte
Beamforming Design for Joint Localization and Data Transmission in Distributed Antenna System
A distributed antenna system is studied whose goal is to provide data
communication and positioning functionalities to Mobile Stations (MSs). Each MS
receives data from a number of Base Stations (BSs), and uses the received
signal not only to extract the information but also to determine its location.
This is done based on Time of Arrival (TOA) or Time Difference of Arrival
(TDOA) measurements, depending on the assumed synchronization conditions. The
problem of minimizing the overall power expenditure of the BSs under data
throughput and localization accuracy requirements is formulated with respect to
the beamforming vectors used at the BSs. The analysis covers both
frequency-flat and frequency-selective channels, and accounts also for
robustness constraints in the presence of parameter uncertainty. The proposed
algorithmic solutions are based on rank-relaxation and Difference-of-Convex
(DC) programming.Comment: 15 pages, 9 figures, and 1 table, accepted in IEEE Transactions on
Vehicular Technolog