Physical-layer authentication (PLA) mechanisms exploit signals exchanged at the physical layer of communication systems to confirm the sender of a received message. In this paper, we propose a novel challenge-response PLA (CR-PLA) mechanism for a cellular system that leverages the reconfigurability property of a reconfigurable intelligent surface (RIS) (under the control of the verifier) in an authentication mechanism. In CR-PLA, the verifier base station (BS) sets a random RIS configuration, which remains secret to the intruder, and then checks that the resulting estimated channel is modified correspondingly. In fact, for a message sent by an attacker in a different location than the legitimate user equipment (UE), the BS will estimate a different channel and the message will be rejected as fake. Such a solution reduces the communication and computational overhead with respect to higher-layer cryptographic authentication. We derive the maximum a-posteriori attack when the attacker observes a correlated channel and the reconfigurable intelligent surface (RIS) has many elements, and the attacker transmits to Bob either directly or through the RIS. Using a generalized likelihood ratio test to test the authenticity at the base station (BS), we derive approximate expressions of the false alarm and misdetection probabilities when both the BS and the UE have a single antenna each, while the RIS has a large number of elements. We also evaluate the trade-off between security and communication performance, since choosing a random RIS configuration reduces the data rate. Moreover, we investigate the impact of various parameters (e.g., the RIS randomness, the number of RIS elements, and the operating signal-to-noise ratio) on security and communication performance.

We consider uplink multiuser multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication. The transmit (Tx) side of the envisaged system consists of several single-antenna users or/and several multiple-antenna users. At the receive side, a multiple-antenna access point employs compressive sensing techniques to estimate the channel impulse response from the preamble portion of the observed packets. The traditional approach is that of orthogonal pilot allocation: during a short training period, each OFDM subcarrier is assigned exclusively to a single Tx antenna. In this case, the channel state information can conveniently be acquired on a per Tx antenna basis. To the best of our knowledge, all related research imposes that all Tx antennas are allocated the same amount of pilots (which must then be tailored for the most extreme channel conditions). However, in the considered system, Tx antennas may experience totally different channel conditions. Under these circumstances, the use of a fixed number of pilots per Tx antenna results in a lot of unnecessary overhead. To tackle this problem, our work addresses the design of efficient algorithms for adaptive orthogonal pilot allocation. The following design principles are applied: orthogonal pilot allocation, constant-modulus modulation, minimum measurement matrix mutual coherence optimization, and the condition that the number of pilot subcarriers allocated to each Tx antenna is adjusted to the channel conditions experienced by that Tx antenna. The paper tackles the problem of determining the optimal number of pilot subcarriers as well as the optimal positions of the pilots. To facilitate adaptive operation, we propose a reduced-complexity method to determine the optimal pilot positions. The performance of our algorithms is demonstrated by means of computer simulations, using both theoretical channel models and results from our own channel measurement campaign.

A novel coding strategy is proposed for a broadcast setting with two transmitter (TX) antennas and two single-antenna receivers (RX). The strategy consists of using space-time block coding to send a common message (to be decoded by both RXs) across the two TX antennas, while each TX antenna also sends a private message to one of the RXs. The relative weight of the private and common messages from each TX antenna is tuned to maximize the instantaneous achievable sum-rate of the channel. Closed-form expressions for the optimal weight factors are derived. In terms of the generalized degrees of freedom (GDoF) metric, the new scheme is able to achieve the sum-GDoF with finite precision channel state information at the transmitter (CSIT) of the two user broadcast channel. Moreover, as opposed to the existing rate-splitting schemes, the proposed scheme yields instantaneous achievable rates that are independent of the channel phases. This property is instrumental for link adaptation when only magnitude CSIT is available. Our numerical results indeed demonstrate the superiority of the scheme for the 2-user setting in case of magnitude CSIT. Extension to a more general K-user scenario is briefly discussed.

In ultra wideband (UWB) orthogonal frequency-division multiplexing (OFDM) systems, compressive sensing (CS) is often employed to produce a pilot-assisted estimate of the sparse channel. The corresponding estimation performance depends to a large extent on the considered pilot allocation (PA) method, i.e., the way to select which OFDM subcarriers are best used to transmit the pilot symbols. The development of good practical PA methods has recently received a lot of attention in the scientific literature. The main challenge is to provide an attractive trade-off between the complexity of the PA method and the achieved channel estimation performance (and by extension the achieved bit error rate). In this paper, we propose a novel PA method based on simulated annealing (SA). Simulations are conducted to confirm the validity of our approach. Compared to the state-of-the-art method, the proposed PA method is shown to achieve better performance with a lower complexity.

Non-Coherent Rate-Splitting (NCRS) was recently proposed as a practical multiuser coding and decoding scheme to increase the spectral efficiency of multibeam satellite communication systems. In this paper, we further study the practical realization of NCRS. We propose a modified coding scheme (NCRS*) that is robust to a nonzero time offset among beams. In NCRS*, as opposed to NCRS, the beams send independently channel encoded and modulated waveforms. We assess the performance of NCRS* in terms of the achievable rate region. It is shown that NCRS* performs worse than NCRS, but better than or comparable to other competing schemes, which, as opposed to NCRS*, require flexible bandwidth allocation or perfect synchronization at the transmitter. We also propose a new N-MAP algorithm for the practical implementation of NCRS* receivers. Similar to the existing UMAP algorithm, N-MAP takes into account the modulation used by, and the time offset between, the signals received from the different beams. In most cases, however, N-MAP has a significantly lower complexity than U-MAP.

The identification of maximum tolerable levels for potential mismatches is critical when designing communication systems. In this paper, we derive maximum tolerable levels for time-interleaved analog-to-digital-converter (TI-ADC) gain mismatch in orthogonal frequency-division multiplexing (OFDM) systems. To this end, we first analytically evaluate the bit error rate (BER) for square quadrature amplitude modulated-OFDM systems that are impaired by: 1) the gain mismatch of a TI-ADC and 2) the channel estimation errors (CEEs) of a zero-forcing equalizer. Our analysis includes the cases of a frequency-selective Rayleigh fading channel and a wired channel. Next, built on the obtained BER expressions, a threshold is established on the gain mismatch level, at which an error floor caused by the gain mismatch is below a given BER value at high signal-to-noise ratios in the absence of CEEs. Finally, numerical results further show that if and only if we set the gain mismatch level below 0.25 of this threshold, there is essentially no BER performance degradation compared with the mismatch-free case.

This paper presents an efficient procedure to numerically evaluate the exact bit error rate of a rectangular quadrature amplitude modulated-orthogonal frequency division multiplexing (OFDM) system that is impaired by the gain mismatch of a time-interleaved analog-to-digital converter. As opposed to previous contributions, no approximations are involved in this procedure. The obtained results allow to accurately analyze the effect of this type of mismatch on the performance of practical high-speed OFDM systems. The accuracy and efficiency of the proposed technique are demonstrated by comparing analytical results with brute-force Monte-Carlo simulations.

This paper studies frame synchronization for use with the advanced communication link transmission unit format that was recently proposed for updating the telecommand synchronization and channel coding standard for space applications. With a view to improving the robustness against jamming, future satellite telecommand systems are planning to adopt direct-sequence spread spectrum modulation and advanced channel coding. Compared to the frame synchronization algorithm specified in the current Consultative Committee for Space Data Systems (CCSDS) recommendation, we consider a longer start sequence and relax the condition for declaring synchronization. We investigate the performance of this algorithm in the presence of jamming, and show that the frame synchronizer can be designed such that the overall system's robustness against pulsed jamming is limited by the robustness of the code rather than the synchronizer.

This paper considers the detection of coded phaseshift keying signals subjected to additive white Gaussian noise and oscillator phase noise. We propose a detector that partitions the received frame into smaller blocks and models the unknown phasor variations over each block as a truncated discrete cosine transform (DCT) expansion. Detection and decoding are iteratively performed between a soft-input soft-output (SISO) demodulator, a SISO demapper, and a SISO decoder based on the sum-product algorithm and the factor graph framework, whereas the expectation-maximization algorithm is used in the demodulator for the DCT coefficients estimation. The resulting demodulator is shown to have an excellent performance/complexity tradeoff and to be well-suited for parallel processing on multiple cores.

This paper presents a new iterative multiuser (MU) detection algorithm for asynchronous spectrally-efficient continuous-phase modulation in additive white Gaussian noise. The proposed detector is derived from the sum-product (SP) algorithm and the factor graph (FG) framework, and performs approximate maximum a posteriori bit detection. A convenient FG of the actual MU detection problem is considered, rather than only FGs of the individual single-user detection problems combined with ad-hoc inter-user interference cancellation. A suitable set of SP messages is approximated by a Gaussian distribution; this considerably reduces the computational complexity and memory size requirements as compared to a straightforward application of the SP rules. The resulting algorithm succeeds in achieving a good error performance.

The presence of a frequency offset (FO) and phase noise can cause severe performance degradation in digital communication systems. This work combines a simple FO estimation technique with a low-complexity phase noise estimation method, inspired by the space-alternating generalized expectation-maximization algorithm. Using a truncated discrete-cosine transform (DCT) expansion, the phase noise estimate is derived from the estimated DCT coefficients of the phase. A number of implementations of the proposed algorithm are discussed. Numerical results indicate that when estimating the FO from pilot symbols only, comparable performance can be reached as the computationally more complex case where the FO is updated iteratively, with small convergence time. The phase noise estimation step is well capable of compensating for the residual FO. For the considered scenario, performing FO compensation before iterative phase noise estimation yields a bit-error rate performance degradation close to the case where the FO is known.

The introduction of turbo and low-density parity-check (LDPC) codes with iterative decoding that almost attain Shannon capacity challenges the synchronization subsystems of a data modem. Fast and accurate signal synchronization has to be performed at a much lower value of signal-to-noise ratio (SNR) than in previous less efficiently coded systems. The solution to this issue is developing specific synchronization techniques that take advantage of the presence of the channel code and of the iterative nature of decoding: the so-calledturbo-synchronizationalgorithms. The aim of this paper within this special issue devoted to the turbo principle is twofold: on the one hand, it shows how the many turbo-synchronization algorithms that have already appeared in the literature can be cast into a simple and rigorous theoretical framework. On the other hand, it shows the application of such techniques in a few simple cases, and evaluates improvement that can be obtained from them, especially in the low-SNR regime.

This paper investigates the effectiveness of a (non-)code-aided ML-based FB phase synchronizer at the low operating signal-to-noise ratio of capacity-approaching codes. We show that the performance of the code-aided synchronizer is very close to that of a data-aided synchronizer that knows all data symbols in advance. This illustrates the optimality of the code-aided synchronizer. For the non-code-aided and the data-aided synchronizer, the linearized mean square phase error (MSPE) is evaluated analytically in the case of a first order loop. We demonstrate that, the MSPE of the non-code-aided synchronizer equals that of the data-aided synchronizer when the carrier phase is essentially constant and the loop filter gain is the same for both synchronizers, but that the non-code-aided synchronizer (as compared to the data-aided synchronizer) yields a larger MSPE due to phase fluctuations. This proves that code-aided FB phase estimation outperforms non-code-aided FB phase estimation when that the phase to be estimated is time-varying.

In this paper, based on a sequential Monte Carlo method, a computationally efficient algorithm is presented for blind data detection in the presence of residual phase noise generated at the output the phase tracking loop employed in a digital receiver. The basic idea is to treat the transmitted symbols as "missing data" and draw samples sequentially of them based on the observed signal samples up to time t. This way, the Bayesian estimates of the phase noise and the incoming data are obtained through these samples, sequentially drawn, together with their importance weights. The proposed receiver structure is seen to be ideally suited for high-speed parallel implementation using VLSI technology.

This contribution considers the joint estimation of the carrier phase and the frequency offset from a noisy linearly modulated burst signal containing random data symbols (DS) as well as known pilot symbols (PS). The corresponding Cramer-Rao lower bound (CRB) is derived. This bound indicates that it is potentially more accurate to estimate carrier phase and frequency from such a 'hybrid' burst than from a burst without PS or from the limited number of PS only. The new bound is then compared with the performance of new and existing carrier synchronizers. We present the iterative Soft-Decision-Directed estimator with combined Data-Aided/Nondata-Aided initialization, which performs closely to the CRB, and provides a large improvement over the classical Nondata-Aided estimator at low and moderate Signal-to-Noise Ratio.

This paper considers the Cramer-Rao bound (CRB) related to estimating the carrier frequency of a noisy phase-shift keying signal. The following scenarios are discussed: 1) carrier frequency estimation irrespective of the carrier phase, based on either known or random data and 2) joint carrier phase and frequency estimation, based on either known or random data. Ideal symbol timing is assumed. We compare the results obtained from a (commonly used) simplified observation model against those resulting from the correct model. Because of the presence of nuisance parameters (random data and/or random carrier phase), the analytical computation of the corresponding CRBs is often not feasible. Here we present results that are based upon a combined analytical/numerical approach. Our results show that the choice of the observation model has essentially no effect on the CRBs at moderate and high signal-to-noise ratios. We also show that of the two scenarios considered, joint frequency and phase estimation yields the smaller CRB; the penalty resulting from frequency estimation, irrespective of the carrier phase, decreases with increasing observation interval.

This paper derives the Cramer-Rao bound (CRB) related to the estimation of the time delay of a linearly modulated bandpass signal with unknown carrier phase and frequency. We consider the following two scenarios: joint estimation of the time delay, the carrier phase, and the carrier frequency; and joint estimation of the time delay and the carrier frequency irrespective of the carrier phase. The transmit pulse is a bandlimited square-root Nyquist pulse. For each scenario, the transmitted symbols constitute either an a priori known training sequence or an unknown random data sequence. In spite of the presence of random data symbols and/or a random carrier phase, we obtain a relatively simple expression of the CRB, from which the effect of the constellation and the transmit pulse are easily derived. We show that the penalty resulting from estimating the time delay irrespective of the carrier phase decreases with increasing observation interval. However, the penalty, caused by not knowing the data symbols a priori, cannot be reduced by increasing the observation interval. Comparison of the true CRB to existing symbol synchronizer performance reveals that decision-directed timing recovery is close to optimum for moderate-to-large signal-to-noise ratios.

This paper is devoted to turbo synchronization, that is to say the use of soft information to estimate parameters like carrier phase, frequency offset or timing within a turbo receiver. It is shown how maximum-likelihood estimation of those synchronization parameters can be implemented by means of the iterative expectation-maximization (EM) algorithm [A.P. Dempster, et al., 1977]. Then we show that the EM algorithm iterations can be combined with those of a turbo receiver. This leads to a general theoretical framework for turbo synchronization. The soft decision-directed ad-hoc algorithm proposed in V. Lottici and M. Luise, [2002] for carrier phase recovery turns out to be a particular instance of this implementation. The proposed mathematical framework is illustrated by simulations reported for the particular case of carrier phase estimation combined with iterative demodulation and decoding [S. ten Brink, et al., 1998].

This contribution considers the Cramer-Rao bound (CRB) related to the joint estimation of the carrier phase and frequency of a noisy linearly modulated signal with random data symbols, using the correct continuous-time model of the received signal. We compare our results with the existing results obtained from a (common used) simplified discrete-time model of the matched filter output samples, that ignores useful signal reduction and ISI caused by nonzero frequency offset. We show that both models yield the same CRB for phase estimation. As far as frequency estimation is concerned, we point out that: (i) the correct observation models yield the smaller CRB, and (ii) the difference between the CRBs resulting from the two models is apparent only at very small SNR. This indicates that at practical SNR values, the frequency offset affects the likelihood function mainly through the signal rotation (rather than signal magnitude) at the matched filter output.

In this paper, we consider the effect of a carrier phase offset on the performance of a low-density parity-check (LDPC) coded QAM modulated system. We investigate an ML-based carrier phase synchronization algorithm that makes use of the posterior probabilities of the data symbols, provided by the iterative decoder. The resulting carrier phase synchronizer is an extension, to LDPC coded systems, of the iterative phase estimator for turbo coded systems, presented in V.Lottici and M.Louse [2002], and has negligible BER performance degradation as compared to the ideally synchronized system.

This contribution considers the Cramer-Rao bound (CRB) related to phase-independent carrier frequency estimation from a noisy PSK signal. Instead of estimating the frequency jointly with the carrier phase, we treat the phase as a nuisance parameter. Ideal symbol timing is assumed. Both cases of known data (training sequence) and random data are considered. We show that frequency estimation irrespective of the carrier phase yields a larger CRB than does joint frequency and phase estimation; the penalty resulting from the former strategy vanishes with increasing observation interval.

In this contribution we consider the Cramer-Rao bound (CRB) for the estimation of the time delay of a noisy linearly modulated signal with random data symbols. In spite of the presence of the nuisance parameters (i.e., the random data symbols), we obtain a closed-form expression of this CRB for arbitrary PSK, QAM or PAM constellations and a bandlimited square-root Nyquist transmit pulse.