Javier Perez-Ramirez

Optimal 3-D Landmark Placement for Vehicle Localization Using Heterogeneous Sensors

Optimal placement of sensors or landmarks for the localization of an autonomous guided vehicle (AGV) based on range measurements is considered. The optimization relies on the Fisher information matrix (FIM). A closed-form expression of the FIM determinant is obtained for 2-D and 3-D spaces, considering heterogeneous sensors and distance-dependent ranging errors. Analytical bounds on the FIM determinant are derived, and several optimal landmark placement expressions for specific scenarios using two groups of landmarks are given. A minimax formulation for the optimal landmark placement is proposed and iteratively solved using exponential smoothing. There are several key features integrated into the proposed approach. These include 1) averaging of the cost function over elementary regions of the AGV search space to include the effect of the whole search space, 2) using a projected gradient search to stay within the boundaries of the landmark search space, and 3) searching on a convex space for placing the landmarks. Convergence issues of the proposed algorithm are discussed. Numerical results demonstrate that the proposed optimal landmark placement enables accurate AGV localization over significantly large volume or area of the search space compared with the case when landmarks are randomly placed.

Hybrid Optical/RF Channel Performance Analysis for Turbo Codes

Turbo coded data transmission over a hybrid channel, consisting of parallel free space optical (FSO) and radio frequency (RF) links, is considered, and analytical bit error performance results are derived. The FSO link is modeled using the gamma-gamma distribution function, and both random and block fading channels are used. Random and specific codeword bit selections for transmission through the RF link are considered. Conditions to guarantee bit error rate (BER) performance improvement in hybrid channels over FSO only links are derived. In the case of block fading channels, the hybrid channel using turbo codes is found to provide several dBs of gain in the signal-to-noise ratio (SNR) over an optical only link. A technique to jointly optimize puncturing and RF bit selection patterns for the hybrid channel is also presented. Results demonstrate significant BER performance improvement obtained from the proposed joint optimization approach.

A Single-Input Multiple-Output Optical System for Mobile Communication: Modeling and Validation

A single-input multiple-output optical communication system based on an LED transmitter and a receiving pixel grid of a camera is considered. The LED image received at a reference distance is modeled using a Gaussian mixture and the pixel values at any other desired distance are estimated using the reference image. Both optimal and suboptimal pixel combining techniques are analyzed. The experimental validation includes placement of the camera on a motorized translation stage to analyze the effects of random locations of the LED image on the pixel grid. Results show excellent agreement between proposed model and the experiment. When random image locations over the pixel grid due to mobility are considered, a receiver that uses only the best pixel is found to lose more than 50% of the received power over a maximal ratio combiner at a distance of 2 m.

Design and Analysis of Bit Selections in HARQ Algorithm for Hybrid FSO/RF Channels

A novel type-II hybrid automatic repeat request (HARQ) algorithm over hybrid channels, consisting of parallel free space optical (FSO) and radio frequency (RF) links, is presented. The algorithm uses different jointly optimized puncturing and RF bit selection patterns for different retransmissions. Analytical bit error rate and throughput performance expressions for the algorithm in case of both time invariant and random fading channels for recursive systematic, non-recursive non-systematic convolutional codes and turbo codes are given. Numerical results show a gain of several dBs of the proposed algorithm when compared to HARQ that uses random bit selection for transmission through the RF channel. The performance of the algorithm for different FSO and RF link conditions is demonstrated.

Experimental multiuser mobile optical communication using compressive sensing

This paper presents a multiuser mobile optical wireless communication system that uses a single digital camera to receive signals transmitted by multiple users using light-emitting diode (LED) arrays. The key idea is to sample only the engaged camera pixels affected by the signals from the users. Toward this aim, image frames received during an acquisition phase are used to estimate the signal support of the users in the image plane using the orthogonal matching pursuit (OMP) algorithm in a compressed sensing framework. The detected signal support is then clustered and tracked using Kalman Filters. Both numerical methods and hardware experiments are used to validate the algorithms. The proposed system is found to provide excellent performance even for users with weak transmitted signals.

A Joint Positioning and Communication Paradigm Using Relay Nodes as Anchors

Dual-role nodes that can work both as relays and also as anchors for joint communication and source localization are proposed. Selection and power allocation of a few dual-role nodes in the presence of many nodes in the network are considered. A novel approach is proposed that relies on maximizing the signal-to-noise ratio (SNR) at the destination node under a source localization constraint. Bounds on the number of nodes needed to achieve a certain localization performance, a concave bound on SNR at the destination node and a practical algorithm to select the dual-role nodes are presented. To estimate the source location using non- line-of-sight range measurements, a new algorithm using semi- definite programing with relaxation followed by majorization- minimization is presented. The results demonstrate excellent promise for obtaining joint improved bit error rate and mean- squared error localization performance by selecting nodes based on combined SNR and localization constraint.

Compressive Parameter Estimation for Correlated Frames in MIMO Visible Light Communications

Estimation of the image location of a mobile LED array transmitter on the camera sensor plane of a digital camera is considered. A Bayesian framework is used to design an initial large measurement matrix over multiple image frames to exploit inter-frame temporal correlations. This large matrix is then factorized into two component matrices; one is used as the front-end measurement matrix with the potential for hardware implementation while the other is designed for software implementation. The factorization can be performed offline through fixed point iterations. The proposed measurement matrix design directly exploits possible transmitter mobility through a parametric framework. The findings are validated through analysis, computer simulation and hardware experiments. Sub-pixel localization accuracy with significant compression is achieved, and the proposed compressive parameter estimation outperforms results obtained using a Gaussian measurement matrix.

Anchor-cum-Relay Nodes for Localizing a Mobile Source and Relaying Source Signals

The problem of selecting anchor-cum-relay (ACR) nodes for the dual purpose of tracking a mobile source as well as serving as relays for the source signal is considered. The proposed approach uses particle filters (PFs) with node selection based on the received signal-to-noise ratio (SNR) along with a localization constraint derived through the Fisher information matrix (FIM). The detail steps of implementation are given. A posterior Cramer-Rao lower bound approach is also explored to exploit information from previous node selections. Numerical results demonstrate that the proposed FIM-SNR approach achieves more than 16 dB in average source localization mean-squared error (MSE) over nearest node (NN) selection, while performing very close to FIM-based optimal localization. At the same time, the proposed FIM-SNR provides a received SNR nearly identical to NN selection but outperforming FIM-based selections SNR by more than 5.5 dB.

Optimized laser beam parameters for communications in space environments in the presence of pointing errors

We investigate the behavior of spatially partially coherent beams (PCBs) in the presence of pointing errors in the space communication environment. Closed form expressions for the optimal coherence length for minimizing outage probability and maximizing average signal-to-noise ratio (SNR) are derived. In the case of outage probablity, we observe that the optimal coherence parameter does not depend on the pointing error statistics. For average SNR results, PCBs can improve performance when large fixed beam offsets are present. We also provide BER performance analysis results for a convolutionally coded system and demonstrate significant performance improvement using PCBs with optimized parameters.