The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware–software heterogeneity, and the integration of intelligent, data-driven components. Ensuring dependability in such systems requires a holistic approach that spans multiple abstraction layers and encompasses both design- and run-time assurance. Traditional methods for reliability, safety, and security management often fall short in addressing the dynamic and uncertain behaviors introduced by Artificial Intelligence (AI) and Machine Learning (ML) components, especially under stringent real-time, power, and safety constraints. While AI and ML offer powerful predictive, adaptive, and self-optimizing capabilities that can enhance system dependability, their inherent non-determinism, data-dependence, and lack of formal guarantees introduce new challenges for verification, validation, and certification. This paper explores emerging methodologies, architectures, and frameworks for designing dependable autonomous and embedded systems in the era of AI. It highlight advances in reliability modeling, secure system design, and certification approaches that account for imperfect, learning-enabled components, aiming to bridge the gap between AI innovation and certifiable system-level dependability.

This paper studies the physical layer performance of a lean carrier with reduced reference symbols and reduced control channel overhead as a possible candidate for a new 5G air interface. Specifically, we will show that, with minor modifications and optimizations, competitive link level performance can be achieved even in extreme use case scenarios using synchronization and channel estimation algorithms already employed in LTE-A. Further, we propose a set of enhancements to the broadcast channel and to the common search space configurations to fully dispense with cell specific reference symbols and legacy control channels.

The uncoded performance of an Alamouti space-frequency block code operating in a frequency-selective channel is studied in the presence of channel estimation errors. The Alamouti Maximum Likelihood (ML) symbol detector with linear combining is considered at the receiver. Imperfect channel estimates are provided by a realistic Wiener interpolator. The impact of channel estimation errors and correlation mismatch on the uncoded performance of the system is evaluated as a function of key system parameters, such as the anticipated power delay profile at the channel estimator, the actual, i.e. true, power delay profile, the pilot spacing and the Wiener filter length. The role of partial knowledge of the channel statistics is investigated as well.

Due to their extremely large transmission bandwidth, ultrawideband (UWB) communications systems have the potential for significant multipath capture. However, such capture can be dependent on the accuracy of channel estimation, which is the problem considered herein. Strategies that exploit properties of the UWB channel can offer performance improvement over schemes which are less parametric. To this end, recent UWB propagation studies and associated channel modelling suggest that clustering occurs in both space and time for indoor wireless office/laboratory environments. Motivated by this study, a two-stage channel estimation scheme is proposed. First, coarse channel estimation is conducted which estimates the location and dispersion of a cluster around this location. Then, channel estimation efforts are localized around the nominal location to reduce the dimensionality of the estimation of the parameters associated with the different multipath components. For cluster estimation, methods based on maximum-likelihood and correlation matrix fitting are considered. Different strategies are presented for multipath estimation, based on the expectation maximization algorithm and correlator output maximization. The bit error rate of a Rake type receiver is simulated with the estimated channel parameters for a multipath scenario based on clusters. Simulation results indicate that the clustered approach offers solid performance gains over conventional methods

The multipath capture of ultrawideband (UWB) communications systems can be dependent on the accuracy of channel estimation. Furthermore, inefficient modeling of the channel often leads to over-parametrization and increased channel estimation error. Relying on a channel model based on clusters, this letter proposes a maximum likelihood estimation strategy which exploits the properties of the UWB channel and offers performance improvement of about 2 dB over less parametric schemes. The robustness of the proposed algorithm in the presence of pulse distortion is investigated and the corresponding BER degradation is observed to be small even when experimental data are employed.

Algorithms for the estimation of a channel whose impulse response is characterized by a large number of zero tap coefficients are developed and compared. Estimation is conducted in a two-stage fashion where an estimate of the non-zero taps is followed by channel estimation. Tap detection is transformed into an equivalent on-off keying detection problem. Several tap detection algorithms are investigated which tradeoff between complexity and performance. The proposed methods are compared to an unstructured least squares channel estimate as well as a structured approach based on matching pursuit. Three schemes in particular are developed: a sphere decoder based scheme, a Viterbi algorithm based method and a simpler iterative approach. The latter offers a better tradeoff between estimation accuracy and computational cost. A joint estimation and zero tap detection scheme is also considered. All solutions exhibit a significant gain in terms of mean-squared error and bit error rate over conventional schemes which do not exploit the sparse nature of the channel, as well as the matching pursuit approach which does endeavor to exploit the sparsity

Synchronization is one of the most critical issues in ultra-wideband communications due to the short duration of the pulses. In this work, a semi-blind synchronization scheme based on maximum-likelihood techniques to recover both symbol and frame timing is developed. The proposed algorithm performs joint timing and channel estimation and is thus robust against moderate timing errors. The probability of acquisition is computed based on correlated Gaussian random variables and analytical results are shown to be accurate for moderate to high SNR values relative to simulated performance. The results reveal that the proposed algorithm achieves a significant performance gain in terms of mean-squared error and bit-error-rate in comparison to proposed frame rate (FR) based algorithms. The impact of a low resolution analog-to-digital converter is shown to be marginal

This paper is concerned with timing recovery for ultra-wideband communication systems operating in a dense multipath environment. Two timing algorithms are proposed that exploit the samples of the received signal to estimate the start of the individual frames with respect to the receiver's clock (frame timing) and the location of the first frame in each symbol (symbol timing). Channel estimation comes out as a by-product and can be used for coherent matched filter detection. The proposed algorithms require sampling rates on the order of the inverse of the pulse duration. Their performance is assessed by simulating the operation of coherent and differential detectors. Their sensitivity to the sampling rate is discussed, and the effects of the multiple access interference are evaluated.

The paper investigates ultra-wideband receivers for applications in sensor and control networks, M-ary pulse position modulation is considered and the detector operates with no knowledge of the channel response. It is shown that the optimum decision rule consists of comparing the signal energies received in the M possible pulse positions in a symbol interval and deciding for that position corresponding to the maximum energy. Simple synchronization algorithms are proposed and their performance is assessed by simulation over realistic multipath channels. The algorithms are non-data-aided (blind) and have a feedback structure in which the error signal is based on energy measurements from the received waveform. The receiver performance degradations due to timing errors are found to be marginal

This paper deals with channel acquisition and tracking for the uplink of direct-sequence code-division multiple-access systems. The transmission medium is characterized by multipath propagation, and the goal is to estimate the time-varying channel impulse response (CIR) for a new user entering the system. Channel acquisition is pursued through maximum-likelihood techniques. The resulting scheme may be too complex in some applications, as it requires the online inversion of a large matrix. Therefore, we also consider a simpler solution based on the least-squares (LS) criterion. Channel tracking is performed through weighted LS methods. At each signaling interval, the CIR estimate is updated using data decisions and exploiting the inverse of the interference covariance matrix to mitigate the near-far problem. Performance is assessed by simulation in a scenario inspired by the frequency-division duplexing component of the universal mobile telecommunications system. The acquisition/tracking algorithms are found to be resistant to multiuser interference and suitable for transmissions over fast-fading channels.

The paper is concerned with timing recovery for ultra-wideband communications operating in a dense multipath environment. A timing algorithm is proposed that exploits the samples of the received signal to estimate the start of the individual frames with respect to a local reference (frame timing) and the location of the first frame in each symbol (symbol timing). Channel estimation is inherent in the timing algorithm and can be used for coherent matched filter detection.

Channel estimation for ultra-wideband (UWB) signals is considered herein. The UWB propagation study and associated channel modelling of R. J. -M Cramer et al., (May 2002) suggest clustering occurs in both space and time for indoor wireless office/laboratory environments. Motivated by this study, a two-stage channel estimation scheme is proposed. First, coarse channel estimation is conducted to estimate the nominal location and dispersion of a cluster. Then, channel estimation efforts are concentrated around the nominal parameters to reduce the dimensionality of the estimation of the parameters associated with the different multipath components. Different strategies based on maximum-likelihood, least squares and expectation maximization are presented and compared in terms of estimation accuracy and complexity. The bit error rate of a Rake type receiver is simulated with the estimated channel parameters for a clustered multipath scenario.

Algorithms for the estimation of a channel whose impulse response is characterized by a large number of negligible tap coefficients are developed and compared. Exploiting this sparsity, the estimation problem is transformed into an equivalent on-off keying detection problem, whose solution gives an indication on the position of the zero taps. The proposed schemes are compared to the standard least squares estimate via simulations in terms of mean square error and bit error rate. A scheme based on sphere decoding appears to give the best performance while maintaining moderate complexity.

Synchronization and channel acquisition for ultra-wideband signals are investigated. The channel impulse response is estimated via two approaches: a least-squares method which ignores channel structure, and a subspace technique which finds channel sparseness and then exploits this structure for final channel estimation. Symbol and frame synchronization is also accomplished using least squares methods. Performance is investigated through the evaluation of mean-squared channel estimation error and probability of error with a RAKE receiver employing the channel estimates for an indoor wireless channel. It is observed that the subspace method exploiting the clustered property of the channel yields the best performance at the expense of complexity.

This paper investigates channel acquisition and tracking for the uplink of a DS-CDMA system. The transmission medium is characterized by multipath propagation and the goal is the estimate the time-varying channel impulse response (CIR) of a new user entering the system. Channel acquisition is pursued through maximum likelihood techniques while channel tracking is performed through weighted least squares methods. At each signaling interval the CIR estimate the inverse of the interference covariance matrix to mitigate the near-far problem. Performance is assessed by simulation in a scenario inspired by the UMTS system.