C. Vilella

Partially clipping (PC) method for the peak-to-average power ratio (PAPR) reduction in OFDM

OFDM (orthogonal frequency division multiplexing) has emerged as one of the best modulations for broadband mobile communications. Despite its robustness against multipath interference, the drawback of peak-to-average power ratio (PAPR) has to be overcome. PAPR increases the A/D and D/A complexity and reduces the high power amplifier efficiency as well as battery life. A new technique for reducing the PAPR of OFDM modulation is presented. This method does not spread the OFDM signal bandwidth, it scarcely increases the computational complexity and no additional information has to be known by the receiver.

Hierarchical CRF with product label spaces for parts-based models

Non-rigid object detection is a challenging open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, human-computer interaction or image auto-annotation. Most successful approaches to non-rigid object detection make use of part-based models. In particular, Conditional Random Fields (CRF) have been successfully embedded into a discriminative parts-based model framework due to its effectiveness for learning and inference (usually based on a tree structure). However, CRF-based approaches do not incorporate global constraints and only model pairwise interactions. This is especially important when modeling object classes that may have complex parts interactions (e.g. facial features or body articulations), because neglecting them yields an oversimplified model with suboptimal performance. To overcome this limitation, this paper proposes a novel hierarchical CRF (HCRF). The main contribution is to build a hierarchy of part combinations by extending the label set to a hierarchy of product label spaces. In order to keep the inference computation tractable, we propose an effective method to reduce the new label set. We test our method on two applications: facial feature detection on the Multi-PIE database and human pose estimation on the Buffy dataset.

Remote sensing and skywave digital communication from antarctica.

This paper presents an overview of the research activities undertaken by La Salle and the Ebro Observatory in the field of remote sensing. On 2003 we started a research project with two main objectives: implement a long-haul oblique ionospheric sounder and transmit the data from remote sensors located at the Spanish Antarctic station Juan Carlos I to Spain. The paper focuses on a study of feasibility of two possible physical layer candidates for the skywave link between both points. A DS-SS based solution and an OFDM based solution are considered to achieve a reliable low-power low-rate communication system between Antarctica and Spain.

Low Rate High Frequency Data Transmission from Very Remote Sensors

This chapter deals with the difficulties of transmitting data gathered from sensors placed in very remote areas where energy supplies are scarce. The data link is established by means of the ionosphere, a layer of the upper atmosphere that is ionized by solar radiation. Communications through the ionosphere have persisted, although the use of artificial repeaters, such as satellites, has provided more reliable communication. In spite of being random, noisy and susceptible to interference, ionospheric transmission still has favorable characteristics (e.g. low cost equipment, worldwide coverage, invulnerability, etc.) that appeal to current communications engineering.