Conference Paper

Positioning Algorithms for Cellular Networks Using TDOA

Inst. of Commun. & Navigation, German Aerosp. Center, Wessling
DOI: 10.1109/ICASSP.2006.1661018 Conference: Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on, Volume: 4
Source: IEEE Xplore

ABSTRACT In this paper, we investigate the performance of positioning algorithms in wireless cellular networks based on time difference of arrival (TDoA) measurements provided by the base stations. The localization process of the mobile station results in a non-linear least squares estimation problem which cannot be solved analytically. Therefore, we use iterative algorithms to determine an estimate of the mobile station position. The well-known Gauss-Newton method fails to converge for certain geometric constellations, and thus, it is not suitable for a general solution in cellular networks. Another algorithm is the steepest descent method which has a slow convergence in the final iteration steps. Hence, we apply the Levenberg-Marquardt algorithm as a new approach in the cellular network localization framework. We show that this method meets the best trade-off between accuracy and computational complexity

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we address the problem of localizing sensor nodes in a static network, given that the positions of a few of them (denoted as “beacons“) are a priori known. We refer to this problem as “auto-localization.” Three localization techniques are considered: the two-stage maximum-likelihood (TSML) method; the plane intersection (PI) method; and the particle swarm optimization (PSO) algorithm. While the first two techniques come from the communication-theoretic “world,” the last one comes from the soft computing “world.” The performance of the considered localization techniques is investigated, in a comparative way, taking into account (i) the number of beacons and (ii) the distances between beacons and nodes. Since our simulation results show that a PSO-based approach allows obtaining more accurate position estimates, in the second part of the paper we focus on this technique proposing a novel hybrid version of the PSO algorithm with improved performance. In particular, we investigate, for various population sizes, the number of iterations which are needed to achieve a given error tolerance. According to our simulation results, the hybrid PSO algorithm guarantees faster convergence at a reduced computational complexity, making it attractive for dynamic localization. In more general terms, our results show that the application of soft computing techniques to communication-theoretic problems leads to interesting research perspectives.
    Applied Soft Computing 12/2014; 25:426-434. DOI:10.1016/j.asoc.2014.07.025 · 2.68 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a novel maximum likelihood (ML) time difference of arrival (TDoA) estimation algorithm for subsample delays. We introduce a new initial acquisition and cell search algorithm with implicit multiple access interference (MAI) cancelation. A joint carrier frequency offset (CFO) estimation and subsample delay estimation is used to compensate Doppler spreads and oscillator drifts. Analytical derivations show how the CFO influences the TDoA subsample delay estimation and vice versa. Furthermore, we show through numerical simulations that the geographic base station mapping and the used synchronization codes influence the estimation accuracy. Additionally, we introduce a new successive interference cancelation (SIC) to improve the overall accuracy.
    8th Workshop on Positioning, Navigation and Communication 2011 (WPNC'11); 04/2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper gives an introduction to a generic OFDM based testbed for positioning using time difference of arrival (TDoA) measurements. An overview of the transmitter system and receiver system is given. Furthermore an inital access algorithm with interference mitigation for subsample delay estimation is presented and simulation results are shown. The influence of the geographic base station mapping and the used synchronization codes is discussed. First measurement results reveal perliminary figures for the expected performance leading to further algorithm investigations.
    8th International Workshop on Multi-Carrier Systems & Solutions, MC-SS 2011; 01/2011