Recognizing interleaved and concurrent activities using qualitative and quantitative temporal relationships

The majority of approaches to activity recognition in sensor environments are either based on manually constructed rules for recognizing activities or lack the ability to incorporate complex temporal dependencies. Furthermore, in many cases, the rather unrealistic assumption is made that the subject carries out only one activity at a time. In this paper, we describe the use of Markov logic as a declarative framework for recognizing interleaved and concurrent activities incorporating both input from pervasive lightweight sensor technology and common-sense background knowledge. In particular, we assess its ability to learn statistical-temporal models from training data and to combine these models with background knowledge to improve the overall recognition accuracy. We also show the viability and the benefit of exploiting both qualitative and quantitative temporal relationships like the duration of the activities and their temporal order. To this end, we propose two Markov logic formulations for inferring the foreground activity as well as each activities’ start and end times. We evaluate the approach on an established dataset where it outperforms state-of-the-art algorithms for activity recognition.     

Modularity-based decompositions for valued CSP

This paper addresses combinatorial problems that can be expressed as Valued Constraint Satisfaction Problems (VCSPs). In the VCSP framework, the constraints are defined by valuation functions to reflect several constraint violation levels. Despite the NP-hardness of VCSPs, tractable versions can be obtained by forcing the allowable valuation functions to have specific mathematical properties. This is the case of VCSPs with submodular valuation functions only. In this paper, we propose a problem decomposition scheme for binary VCSPs that takes advantage of modular valuation functions even when the studied problem is not limited to these functions. Modular functions are less frequent than submodular ones but, in compensation, they are easier to process. The proposed scheme works within a backtrack-based search and consists in decomposing the original problem into a set of modular, and then tractable, subproblems. Our decomposition scheme is distinguished by the possibility of instantiating variables by assigning to them subsets of values instead of single values.     

Investigation of load modulated inverse Class‐F power amplifier with extended conduction angle

A novel design space of load modulated (LM) inverse Class‐F power amplifiers (PAs) with extended conduction angle is proposed. The effects of the driven level factor β and the biasing operation factor ρ on the third‐harmonic generation are discussed. The harmonic generation mechanism shows that the knee voltage effects are the source of third‐harmonics for LM inverse Class‐F PAs. The definition of the inverse Class‐F mode is consistently valid under the circumstance of load modulation in a limited output power back‐off (OPBO) range. Meanwhile, the conduction angle θ₀ can be extended from π/2 to a limited value (<110°) to keep the standard waveforms of inverse Class‐F mode and maintain high efficiency. After introducing the “continuous concept” and the second harmonic manipulation method, the mathematical design space of inverse Class‐F PAs with extended conduction angle is derived. Calculation shows that the purely conductive load modulation can enable high back‐off efficiency operation for LM inverse Class‐F PAs. As proof of concept, a demonstrator amplifier is fabricated and measured. The experimental results show that the power added efficiency (PAE) with optimum V_ctrl is improved by 5% over an OPBO range of 6 dB compared with the same PA with fixed V_ctrl.     

A compound structure and a single‐step identification procedure for I/Q and DC offset impairments and nonlinear distortion modeling and compensation in wireless transmitters

The nonlinear behavior of power amplifiers (PAs) and the in‐phase/quadrature (I/Q) imbalance in I/Q modulators are considered as the main sources of distortions and impairments in radio frequency transmitters. In this article, a compound structure and a single‐step identification procedure are proposed for the modulator's I/Q imbalance and DC offset and the PAs nonlinearity modeling and compensation of wireless transmitters. In fact, the performance of the digital predistortion technique used for PA linearization is adversely affected by the I/Q modulator's impairments that result mainly from gain/phase imbalance and DC offset. The measurement results reveal the robustness of the proposed model in modeling and linearization of the PA in the presence of I/Q modulator imperfections and show its superiority as compared to the generalized memory polynomial model and the dual‐input polynomial model. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

On the RF/DSP design for efficiency of OFDM transmitters

In this paper, a system-level RF/digital signal processing (DSP) design approach of power-efficient orthogonal frequency-division multiplexing (OFDM) transmitters is proposed. A DSP-based low-IF architecture, which allows a significant enhancement of their power and spectrum efficiencies, is proposed. The cascade of the peak-to-average power ratio (PAPR) reduction technique, predistortion technique, and the in-phase and quadrature modulation led to impressive improvement in the power efficiency and effective linear output power of the OFDM transmitter. Measurement results carried out on an IEEE 802.11a transmitter designed and built for this experiment are presented in terms of error vector magnitude (EVM), adjacent channel leakage ratio, and power efficiency. The power stage of this transmitter uses a heterojunction bipolar InGaP transistor operating in a deeply class AB. The cascade of the PAPR reduction and baseband predistortion processing modules results in the reduction of the power backoff operation point by approximately 10 dB accompanied by a relative increase in the wireless local area network transmitter power efficiency by roughly 400% while meeting the emission mask spectrum and EVM levels demanded by the 802.11a standard.     

Cooperative network solution and implementation for emergency applications with enhanced position estimation capability

This paper proposes a cooperative network topology for emergency applications which comprises of incident scene networks (ISN) and external area networks. Both base stations and rescuers in ISN are modeled as nodes with the capabilities of software defined radio and signal processing. A worldwide interoperability for microwave access-based emergency protocol is proposed with which rescuers can estimate their geo-locations via time difference of arrival based on more than four known base stations coordinates. A comparative study of state-of-the-art position estimation methods have been carried out for the proposed cooperative network topology to select the most robust method. Hardware results for the most robust position estimation method without/with multipath mitigation have been implemented and presented to estimate the location of the rescuer.     

Systematic and Adaptive Characterization Approach for Behavior Modeling and Correction of Dynamic Nonlinear Transmitters

This paper proposes a comprehensive and systematic characterization methodology that is suitable for the forward and reverse behavior modeling of wireless transmitters (Txs) driven by wideband-modulated signals. This characterization approach can be implemented in adaptive radio systems since it does not require particular signal or training sequences. The importance of the nature of the driving signal and its average power on the behavior of radio-frequency Txs are experimentally investigated. Critical issues related to the proposed characterization approach are analytically studied. This includes a new delay-estimation method that achieves good accuracy with low computational complexity. In addition, the receiver linear calibration and its noise budget are investigated. To demonstrate the accuracy and robustness of the proposed method, a full characterization (including the memoryless nonlinearity and the memory effects) of a 100-W Tx driven by a multicarrier wideband code-division multiple-access signal is carried out, and its forward and reverse models are identified. Cascading the identified reverse model derived using the proposed methodology and the Tx prototype leads to excellent compensation of the static nonlinearities and the memory effects exhibited by the latter. Critical issues in implementing this approach are also discussed.     

Efficiency Enhancement of Sigma–Delta Modulator Based Transmitters Using Multi-Level Quantizers

This paper is concerned with the performance of first- and second- order sigma–delta modulator (ΣΔM) based transmitters with an Orthogonal Frequency Division Modulation (OFDM) signal and Code Division Multiplexing Access (CDMA) signal. In particular, the WorldWide Interoperability for Microwave Access (WiMAX) and Interim Standard 95 (IS-95) down link signals have been used for this study as test signals. The simulation and experimental results showed that the performances of the ΣΔM for both signals are improved by increasing the number of quantization levels and the order of the ΣΔM circuit. A ΣΔ modulator based transmitter using a switching mode power amplifier was developed and built for validation purposes. It is found that the increase of the quantization level of the ΣΔ modulator from 2 to 5 leads to a substantial improvement in the measured power efficiency of the transmitter from 5% to 42%. This improvement in efficiency is in good agreement with simulated and measured results obtained using simulink and FPGA board respectively.     

Estimation of crossover DPD using orthogonal polynomials in fixed point arithmetic

This paper deals with the fixed point implementation of crossover digital predistortion (DPD). The implementation of digital predistortion linearization technique on DSPs poses major challenges, regarding cost, power consumption, speed, precision and volume. Depending on resource availability and design restrictions, fixed-point DSPs may be considered as a suitable solution. Least squares estimation of crossover DPD for multiple-input, multiple-output (MIMO) applications using conventional polynomial models face numerical instability for fixed-point processing. Orthogonal polynomials on the other hand are robust to matrix inversion. Fixed point matrix inversion was implemented using LU decomposition and triangular matrix inversion. This paper examines crossover DPD design for MIMO applications, while using fixed-point arithmetic. It also compares the linearization of 2 × 2 MIMO transmitters in the presence of radio frequency crosstalk using both orthogonal and memory polynomial models. The performance of the two crossover DPDs has been evaluated using a 3GPP standard: orthogonal crossover DPD decreased the measured adjacent channel power ratio of the signal from −42 dBc to −52 dBc.     

Wireless Communications Transmitter Performance Enhancement Using Advanced Signal Processing Algorithms Running in a Hybrid DSP/FPGA Platform

This paper deals with digital base band signal processing algorithms, which are seen as enabling technologies for software-enabled radios, that are intended for the correction of the analog front end. In particular, this paper focuses on the design, optimization and testability of predistortion functions suitable for the linearization of narrowband and wideband transmitters developed with a hybrid DSP/FPGA platform. To select the best algorithm for the identification of the predistortion function, singular value decomposition, recursive least squares (RLS), and QR-RLS algorithms are implemented on the same digital signal processor; and, the computation complexity, time, accuracy and the required resources are studied. The hardware implementation of the predistortion function is then carefully performed, in order to meet the real time execution requirements.