Objective: Medication reconciliation (MedRec) can improve patient safety by resolving medication discrepancies. Because information technology (IT) and patient engagement are promising approaches to optimizing MedRec, the SEAMPAT project aims to develop a MedRec IT platform based on two applications: the "patient app" and the "MedRec app." This study evaluates three dimensions of the usability (efficiency, satisfaction, and effectiveness) and usefulness of the patient app. Methods: We performed a four-month user-centered observational study. Quantitative and qualitative data were collected. Participants completed the system usability scale (SUS) questionnaire and a second questionnaire on usefulness. Effectiveness was assessed by measuring the completeness of the medication list generated by the patient application and its correctness (ie medication discrepancies between the patient list and the best possible medication history). Qualitative data were collected from semi-structured interviews, observations and comments, and questions raised by patients. Results: Forty-two patients completed the study. Sixty-nine percent of patients considered the patient app to be acceptable (SUS Score ≥ 70) and usefulness was high. The medication list was complete for a quarter of the patients (7/28) and there was a discrepancy for 21.7% of medications (21/97). The qualitative data enabled the identification of several barriers (related to functional and non-functional aspects) to the optimization of usability and usefulness. Conclusions: Our findings highlight the importance and value of user-centered usability testing of a patient application implemented in "real-world" conditions. To achieve adoption and sustained use by patients, the app should meet patients' needs while also efficiently improving the quality of MedRec.

To enable frequency domain equalization of continuous phase modulations (CPM), a block construction that ensures cyclicity over each block without disrupting the phase continuity between them was proposed in . We formalize and prove the constraints that should be respected to enable the application of this technique to any CPM scheme.

The large bandwidth available at 60 GHz together with the resulting wavelength of only 5 mm allow the design of multi-Gbps wireless devices equipped with large arrays of tiny antennas. This enables wireless communication of large contents multimedia such as high-definition video. However, due to the high cost and power consumption of analog frond-end (AFE) chains at 60 GHz, it is practically infeasible to allocate a dedicated AFE to each antenna. Thus, it is highly desirable to design low complexity multi-antenna architectures in which an analog linear transformation (ALT) is carried out in order to reduce the required number of AFE chains for digital spatial processing, while minimizing the capacity loss. In this paper, we propose a non-iterative algorithm for joint transmit/receive (TX/RX) ALT. The proposed algorithm is designed with the aim of maximizing the capacity of the resulting reduced dimension MIMO system, assuming a frequency selective propagation channel.

This paper presents a novel fair scheme for resource sharing between nodes in OFDMA mesh networks. The problem is to maximize the overall system rate, under each user's maximal power and minimum rate constraints. To solve the underlying problem, we propose an approach that combines the merits of the well known Lagrange dual framework and the Lambert-W function. By using the Lambert-W function, resource allocation can not only be expressed in closed form but it can also quickly be determined without resorting to complex algorithms since a number of popular mathematical softwares, including Matlab, contain the Lambert-W function as an optimization component. Simulation results are provided to compare the performance of the proposed scheme with other allocation schemes.

We address the problem of co-channel interference (CCI) in wireless mesh networks (WMNs). In such networks, multiple nodes communicate concurrently using the same time/frequency resources. This is recognized as the interference channel (IFC) because the CCI is a major impairment in such a scenario. To mitigate the CCI, non-cooperative beamforming techniques can be employed. Non-cooperative beamformers are simpler to implement than their cooperative counter-parts because they require neither synchronization nor the sharing of information data between the transmit nodes. In this paper, we then propose a non-cooperative beamforming scheme to improve the performance of WMNs with frequency-selective channels. We present an iterative algorithm that maximizes the signal-to-interference-and-noise ratio criterion over all subcarriers of the orthogonal frequency division multiplexing system. The performance of this algorithm is evaluated through simulations.

To enable frequency domain equalization (FDE) for continuous phase modulation (CPM), both cyclicity of individual symbol blocks and phase continuity between different blocks have to be guaranteed. In this letter, we present new block constructions that use a subblock of data-dependent symbols, called intrafix, to satisfy both constraints for different CPM-FDE systems: using either a cyclic prefix or a training sequence (TS), both for precoded and nonprecoded CPM. The known symbols of a TS can be used to improve synchronization and channel estimation. Precoding can be applied to a certain class of CPM schemes to halve the bit error rate.

For both outdoor and indoor wireless systems there is an increasing demand of high spectral efficiency at a very low cost and power consumption. In this context, MIMO wireless system adopting spatial multiplexing offer a way of increasing the spectral efficiency of the system. In order to fully exploit this capacity non linear MIMO detectors such as maximum likelihood detectors are required. However, when high order modulation schemes are applied, the complexity of this kind of detector becomes prohibitive for a practical implementation. As a solution to this problem, low complexity maximum likelihood detectors such as sphere detectors are appealing as a low complexity solution for high spectral efficiency transmission. Although sphere decoding provides a lower complexity solution than a classical ML detector, its complexity still remains unpredictable and exponentially dependent on channel propagation conditions. This variability in complexity makes the implementation of sphere decoders not practical. In this paper, a new approach for constraining the ML search space is proposed which provides a predictable upper bound for complexity, hence facilitating its implementation. Moreover, the new approach for computing the constrained search space significantly reduces the complexity of the detection while offering scalability in terms of performance and complexity. Simulation results in a cellular system demonstrate the scalability of our detector and the performance/complexity trade-off that it enables.

Analog beamforming (ABF) with one scalar weight per antenna is an attractive technique for low-cost, low-power 60 GHz multi-antenna wireless communication systems. However, the design of the corresponding joint transmit and receive (Tx/Rx) ABF optimization algorithms is still challenging in the case of multipath channels due to the constraint of having only one scalar weight per antenna. In this paper, we aim at maximizing the average signal to noise ratio (SNR) at the input of the equalizer and analytically derive close-to-optimal Tx/Rx scalar weights. We show that the required channel state information (CSI) for joint Tx/Rx ABF weights computation is the inner product between all Tx/Rx channel impulse response pairs. Taking the channel length into account, a training-based estimation strategy of this CSI is proposed. Simulation results carried out in a typical 60 GHz multipath environment show that the proposed scheme outperforms the existing ABF schemes in term of BER performances.

We present a new scheme for maximizing the signal-to-noise ratio (SNR) in wideband multi-antenna receivers that employ time-interleaved analog-to-digital converters (ADCs). Current wideband receivers interleave a fixed number of slower ADCs into one fast ADC and assign this latter to one antenna according to an antenna selection algorithm. However, this does not always guarantee an optimal trade-off between thermal noise and quantization noise. This results in an overall SNR that is lower than what could be obtained with the same number of ADCs, assigned in a more optimal way. Therefore, we propose to adjust the number of slower ADCs assigned to a certain fast, interleaved ADC dynamically, according to the SNR of every individual antenna. Our proposed algorithm can be implemented at the expense of a very limited hardware complexity increase. The SNR gain of our new scheme can exceed 7 dB, depending on channel conditions and ADC specifications.

In this paper, we develop a new low-complexity linear frequency domain equalization (FDE) approach for continuous phase modulated (CPM) signals. As a CPM signal is highly correlated, calculating a linear minimum mean square error (MMSE) channel equalizer requires the inversion of a nondiagonal matrix, even in the frequency domain. In order to regain the FDE advantage of reduced computational complexity, we show that this matrix can be approximated by a block-diagonal matrix without performance loss. Moreover, our MMSE equalizer can be simplified to a low-complexity zero-forcing equalizer. The proposed techniques can be applied to any CPM scheme. To support this theory we present a new polyphase matrix model, valid for any block-based CPM system. Simulation results in a 60 GHz environment show that our reduced-complexity MMSE equalizer significantly outperforms the state of the art linear MMSE receiver for large modulation indices, while it performs only slightly worse for small ones.

One of the techniques for spectrum sensing is the energy detection of signals from primary transmitters. However, when detecting in a certain frequency band, this technique suffers from the random fading introduced by the channel. This problem can be alleviated by the use of multiple antennas introducing spatial diversity. The performance of the energy detector with multiple antennas has already been analytically analyzed for flat fading channels. In this paper, we propose analytical expressions for the performance of multi-antenna energy detector with multi-paths fading channels. These expressions will enable to compare for different channel power profiles the gains brought by the two sources of diversity: spatial (or antenna) diversity and multi-path diversity. This analytical performance is compared to simulations to show the validity of the used approximations.

Continuous phase modulations (CPM) have a perfectly constant envelope and are inherently robust against analog front-end nonidealities. Therefore, they have recently been proposed for several modern wireless standards. In this paper, we further develop an existing high-performance frequency domain equalization approach for CPM signals. First, we introduce a polyphase matrix model, valid for any block-based CPM system, which has clear advantages compared to existing models. Second, the model is used to reduce the complexity of the existing minimum mean square error channel equalizer. The proposed technique can be applied to any CPM scheme. Simulation results in a 60 GHz environment confirm that it does not cause any noticeable performance degradation.

In this paper, we present an analytical analysis to predict the power spectral density (PSD) at the output of a nonlinear power amplifier (PA). We focus on offset quadrature phase shift keying (OQPSK) waveform band-limited by a square root raised cosine (SRRC) filter. This is one of the waveforms used in wideband code division multiple access (W-CDMA) wireless standard. We show that the PA output PSD obtained by our analytical analysis matches well the simulated PSD. Furthermore, we compare the PA output PSD of QPSK and OQPSK waveforms as a function of the SRRC filter roll-off. We conclude that for small roll-off, both QPSK and OQPSK experience almost the same level of spectral re-growth. As the roll-off increases, OQPSK becomes less sensitive to PA nonlinearity relative to QPSK.

We show how to apply Frequency Domain Equalization (FDE) to precoded Continuous Phase Modulation (CPM) systems. It is well known that differential precoding can be applied to the specific, popular class of CPM schemes with modulation index h = 1/2Q, where Q is any integer. This precoding halves the bit error rate (BER) compared to nonprecoded CPM without any overhead or complexity increase. We apply FDE to a block-based precoded CPM system. Therefore, we show that in addition to a cyclic prefix, two subblocks of data-dependent symbols have to be inserted in each block to cope with the memory in the CPM signal and to enable correct decoding by the receiver. We explain how to calculate these subblocks. Simulation results in a 60 GHz environment confirm that the BER is halved by precoding, and that this precoding is compatible with FDE using our new technique.

We present a new symbol block construction which yields a cyclic continuous phase modulated (CPM) signal to enable frequency domain equalization. It is known that in addition to a cyclic prefix, a subblock of data-dependent symbols has to be inserted in each block to cope with the memory in the CPM signal. We propose a new subblock, called intrafix, valid for any CPM scheme. Our intrafix is shorter than what is currently known in the literature, reducing the overhead. Moreover, it can be calculated on a per-block basis, without knowledge of previous blocks. We also prove that there are constraints on the length of both the intrafix and the total block by studying the influence of the modulation index. Simulation results in a 60 GHz environment show that our new block construction satisfies all requirements.

This paper proposes iterative estimators of quasi static frequency selective channels. Their properties (in terms of expectation and mean-squared estimation error) as well as complexity are discussed. Their average performance is also analytically approached. For the sake of low complexity, the derived estimators are either linear or affine in the vector of observations at the channel output. Such estimators are referred to as iterative because they use soft information on data symbols fed back by the soft-in/soft-out (SISO) channel decoder of a turbo equalizer. Because involved in this iterative process, they perform better at low signal-to-noise ratios (SNRs) than standard (i.e. non iterative) channel estimators using the same number of pilot symbols. Conversely, iterative estimators require a smaller number of pilot symbols to achieve the same performance as standard estimators.

A new approach for frequency-domain equalization of continuous phase modulated (CPM) signals is presented. In contrast with state-of-the-art receivers, we separate channel equalization on the one hand and CPM demodulation on the other. This separation enables us to calculate independently of the CPM scheme a new low-complexity zero-forcing channel equalizer. We also present a new high-performance minimum mean square error (MMSE) channel equalizer for any CPM scheme and a method to lower its complexity for a popular class of CPM schemes. Simulations show that our new MMSE equalizer significantly outperforms state-of-the-art linear receivers in a 60 GHz multipath environment.

This paper addresses soft estimation of time-varying frequency selective channels using Kalman smoothing. The proposed estimator uses soft extrinsic information provided by a channel decoder. It is intended to improve the performance of an already existing Kalman filtering-based estimator by exploiting all - rather than part of - the data at the receiver disposal. It is the linear estimator exhibiting for the case of interest the minimum mean-squared estimation error. Its complexity is shown to be quite low. An approximated analytical calculation of the mean- squared estimation error (MSEE), both for Kalman filtering and Kalman smoothing, is also proposed. Simulation results illustrate the performance gain of smoothing over filtering and validate our calculation of the MSEE.

This paper deals with iterative maximum-likelihood synchronization of a scalar parameter. An efficient implementation of the Newton-Raphson (NR) maximum-search method is proposed. Considering the latter implementation, the NR approach is shown to be an attractive alternative to synchronization methods based on the expectation-maximization (EM) algorithm. Simulation results for the case of phase-offset synchronization show that NR method usually increases the speed of convergence of the synchronization algorithm

This paper analytically calculates the expectation and the variance of a soft-information-based best linear unbiased estimator of amplitude and carrier phase offset. Long data frames are considered. The calculation includes the impact on the performance of the presence of training symbols as well as non-Gaussianity of the log-likelihood ratios (LLRs) fed to the estimator input. It is also analyzed how the properties of the estimator are affected when the ratio between the mean and variance of the LLRs is not equal to 1/2

This paper addresses the issue of code-aided hypothesis testing in communication systems, i.e., the estimation of discrete-valued nuisance parameters. A hypothesis testing procedure optimal in the sense of the minimization of the frame-error rate (FER) is derived. Its complexity is shown to be comparable to other recently-proposed code-aided hypothesis procedures. Moreover, when a conditional maximum a posteriori decision rule is used to make the decisions about the transmitted sequence, it is shown that the proposed hypothesis testing procedure combined with sequence detection reduces, in a good approximation, to a joint maximum-likelihood problem. Finally, as an illustrative example, we show the case of phase ambiguity resolution for a convolutionally-coded transmission.

This paper proposes a semi-analytical method for predicting the performance degradation of a turbo-equalization scheme due to signal-to-noise ratio (SNR) estimation errors. In other words, sensitivity of turbo-equalization to an imperfect knowledge of the SNR (or, equivalently, channel noise variance) is analyzed. The considered turbo-equalizer uses the Wang and Poor's soft-in/soft-out (SISO) Minimum Mean Square Error (MMSE) / Interference Cancellation (IC) equalizer and a SISO convolutional decoder. The proposed method is applied to BPSK data modulation and single-user context but may be extended to the multi-user case. This paper shows that the equalizer behavior may be very reliably predicted totally by calculations (no simulations are needed) in the presence of imperfectly known SNR at the receiver. As far as the prediction of the decoder behavior is concerned, it requires simulations for only one independent input parameter. Long frames and perfect channel knowledge at the receiver are assumed in the paper.

This paper proposes a simple and time non-consuming method to predict, at any iteration, the performance of a turbo equalization scheme using a soft-in/soft-out (SISO) minimum mean square error (MMSE)/interference cancellation (IC) equalizer and a SISO decoder. Gaussianity of the extrinsic log-likelihood ratios (LLRs) output by the equalizer as well as the decoder is assumed. This paper shows that the equalizer behavior may then be very reliably predicted only by calculations (no simulations are needed) whereas that of the decoder requires simulations for only one independent input parameter. Comparison between the proposed prediction method and plain simulations of the overall turbo equalization scheme shows that our method accurately determines the system performance at any iteration.

The current paper addresses the issue of estimating the user propagation delays, received carrier phase offsets and received amplitudes in an asynchronous DS-CDMA environment with frequency non-selective propagation channels. The proposed synchronizer is based on the expectation-maximization (EM) algorithm and takes benefit from the soft information delivered by the receiver which is of the turbo type. The performance of the proposed synchronizer is illustrated by simulation results. In particular, the mean and the mean squared error of the estimator, as well as the bit error rate reached by the synchronized system, are reported.

The paper addresses the issue of estimating the sampling instant in turbo receivers. The proposed synchronizer is based on the expectation-maximization (EM) algorithm and takes benefit from the soft information delivered by the turbo system. Performance of the proposed synchronizer is illustrated by simulation results. In particular, the mean and the variance of the estimator as well as the bit error rate reached by the synchronized system are reported.