Instituto de Telecomunicações

Publications

Multi-Gigabit/s OFDM real-time based transceiver engine for emerging 5G MIMO systems

Publication . Ribeiro, Carlos; Gomes, Rodolfo; Duarte, Luís; Hammoudeh, Akram; Caldeirinha, Rafael F. S.

This paper presents a highly scalable multi-Gigabit/s Real-Time (RT) Wideband (WB) Orthogonal Frequency Division Multiplexing (OFDM) processing chain for 5G applications. It is aimed to significantly reduce the Hardware (HW) footprint of Multiple Input Multiple Output (MIMO) systems. In this context, implementation complexity results for MIMO configurations of 2 × 2, 4 × 4 and 8 × 8, enabled at sampling rates of 245.76, 122.88, 61.44 and 30.72 MHz, respectively, are compared with the ones from conventional MIMO architectures. For example, for a 8 × 8 MIMO–OFDM configuration implementation, savings of up to 87% are achieved when compared with conventional design methods, in terms of DSP48E1 slices. Moreover, in a Xilinx Virtex 7 XC7VX485T, it is shown that a second processing branch might be implemented, leading to a 5 Gbps (using 1024 Quadrature Amplitude Modulation (QAM)) Single-Input Single-Output (SISO) link or a 16 × 16 MIMO configuration. Finally, in order to validate the proposed architecture, the impact of its inclusion on a complete Field Programmable Gate Array (FPGA) 8 × 8 OFDM system, at LTE's highest sampling rate of 30.72 MHz, is evaluated. Subsequently, it is demonstrated that this does not affect the performance of OFDM, even in the presence of Carrier Frequency Offset (CFO).

2020-02Journal article

Open access

Detection of Mispronunciations and Disfluencies in Children Reading Aloud

Publication . Proença, Jorge; Lopes, Carla; Tjalve, Michael; Stolcke, Andreas; Candeias, Sara; Perdigão, Fernando

To automatically evaluate the performance of children reading aloud or to follow a child’s reading in reading tutor applications, different types of reading disfluencies and mispronunciations must be accounted for. In this work, we aim to detect most of these disfluencies in sentence and pseudoword reading. Detecting incorrectly pronounced words, and quantifying the quality of word pronunciations, is arguably the hardest task. We approach the challenge as a two-step process. First, a segmentation using task-specific lattices is performed, while detecting repetitions and false starts and providing candidate segments for words. Then, candidates are classified as mispronounced or not, using multiple features derived from likelihood ratios based on phone decoding and forced alignment, as well as additional meta-information about the word. Several classifiers were explored (linear fit, neural networks, support vector machines) and trained after a feature selection stage to avoid overfitting. Improved results are obtained using feature combination compared to using only the log likelihood ratio of the reference word (22% versus 27% miss rate at constant 5% false alarm rate).

2017-08-20Conference paper

Open access

Filtering Email Addresses, Credit Card Numbers and Searching for Bitcoin Artifacts with the Autopsy Digital Forensics Software

Publication . Domingues, Patricio; Frade, Miguel; Parreira, João Mota

Email addresses and credit card numbers found on digital forensic images are frequently an important asset in a forensic casework. However, the automatic harvesting of these data often yields many false positives. This paper presents the Forensic Enhanced Analysis (FEA) module for the Autopsy digital forensic software. FEA aims to eliminate false positives of email addresses and credit card numbers harvested by Autopsy, thus reducing the workload of the forensic examiner. FEA also harvests potential Bitcoin public addresses and private keys and validates them by looking into Bitcoin’s blockchain for the transactions linked to public addresses. FEA explores the report functionality of Autopsy and allows exports in CSV, HTML and XLS formats. Experimental results over four digital forensic images show that FEA eliminates as many as of email addresses and of credit card numbers.

2019-04-10Conference paper

Open access

Reference picture selection using checkerboard pattern for resilient video coding

Publication . Carreira, J.; Assunção, P.; Faria, S.; Ekmekcioglu, E.; Kondoz, A.; Lim, H.

The improved compression efficiency achieved by the High Efficiency Video Coding (HEVC) standard has the counter-effect of decreasing error resilience in transmission over error-prone channels. To increase the error resilience of HEVC streams, this paper proposes a checkerboard reference picture selection method in order to reduce the prediction mismatch at the decoder in case of frame losses. The proposed approach not only allows to reduce the error propagation at the decoder, but also enhances the quality of reconstructed frames by selectively constraining the choice of reference pictures used for temporal prediction. The underlying approach is to increase the amount of accurate temporal information at the decoder when transmission errors occur, to improve the video quality by using an efficient combination of diverse motion fields. The proposed method compensates for the small loss of coding efficiency at frame loss rates as low as 3%. For a single frame-loss event the proposed method can achieve up to 2 dB of gain in the affected frames and an average quality gain of 0.84 dB for different error prone conditions.

2015-12Conference paper

Restricted access

Keywords

Telecommunications,Electronics,Signal processing,Instrumentation and measurement, Engineering and technology ,Engineering and technology/Electrical engineering, electronic engineering, information engineering

Funding agency

Fundação para a Ciência e a Tecnologia, I.P.

Funding programme

Financiamento do Plano Estratégico de Unidades de I&D - 2013/2015 - OE

Funding Award Number

UID/EEA/50008/2013