Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a “store-carry and forward” fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this article, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancelation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts—required to implement the proposed detection strategy—are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.

In multiple antenna systems employing time-division duplexing, spatial precoder design at the base station (BS) leverages channel state information acquired through uplink pilot transmission, under the assumption of channel reciprocity. Malicious eavesdroppers can start pilot spoofing attacks to alter such design, in order to improve their eavesdropping performance in downlink. The aim of this paper is to study the effects of pilot spoofing attacks on uplink channel estimation, by assuming that the BS knows the angle of arrivals (AoAs) of the legitimate channels. Specifically, after assessing the performance of the simple least squares estimator (LSE), we consider more sophisticated estimators, such as the maximum likelihood estimator (MLE) and different versions of the minimum mean square error estimator (MMSEE), involving different degrees of a priori information about the pilot spoofing attacks. Theoretical analysis and numerical simulations are used to compare the performance of such estimators. In particular, we analytically demonstrate that the spoofing effects in the high signal-to-noise ratio regime can be completely suppressed, under certain conditions involving the AoAs of the legitimate and spoofing channels. Moreover, we show that even an imperfect knowledge of the AoAs and of the average transmission power of the spoofing signals allows the MLE and MMSEE to achieve significant performance gains over the LSE.

Ambient backscatter (AmBC) communications cap-italize on ambient radio-frequency (RF) signals to enable communications among ultra-low-power devices, thus representing a promising cost-effective solution for wireless sensor networks in the Internet of Things. In this paper, we study the scenario where single-antenna AmBC sensors are employed to perform decision fusion over multiple-access fading channels. Specifically, AmBC sensors detect the presence/absence of a phenomenon of interest and transmit their decisions to a multiple-antenna fusion center reader (FCR), by reflecting part of an incident RF ambient signal. In this scenario, we derive fusion rules at the FCR by considering both the cases of instantaneous and statistical channel state information, as well as their corresponding low-complexity alternatives. Numerical simulation results are provided to compare the proposed fusion rules and highlight the relevant trends.

This letter deals with second-order statistics (SOS) of continuous-phase modulated (CPM) signals. To overcome some mathematical inconsistencies emerging from the idealized assumption that the CPM signal evolves from t = -∞, we consider a one-sided model for the signal, which starts from t = 0, noting also that such a model emerges naturally when building practical SOS estimators. On the basis of such a model, we first evaluate the SOS of the pseudosymbols, which arise when expressing a CPM signal in terms of its Laurent representation, as well as closed-form expressions of the cyclic autocorrelation and conjugate correlation functions of one-sided CPM signals.

Ambient backscatter is an intriguing wireless communication paradigm that allows small devices to compute and communicate by using only the power they harvest from far-field radio-frequency (RF) signals in the air. Ambient backscattering devices reflect RF signals emitted by existing or legacy communications systems, such as digital TV broadcasting, cellular, or Wi-Fi ones, which are designed for transporting information and are not intended for RF energy transfer. This paper deals with mathematical modeling and performance analysis of wireless broadband networks operating over fading channels with ambient backscatter devices. After introducing a detailed signal model of the relevant communication links, we study the influence of physical parameters on the capacity of both legacy and backscatter channels, by considering different receiver architectures. We analytically show that, under reasonable operative conditions, a legacy system-employing an orthogonal frequency-division multiplexing (OFDM) modulation scheme-can turn the RF interference arising from the backscatter process into a form of multipath diversity that can be exploited to increase its performance. Moreover, our analysis proves that a backscatter system-transmitting one symbol per OFDM symbol of the legacy system-can achieve satisfactory data rates over relatively short distances, especially when the intended recipient of the backscatter signal is co-located with the legacy transmitter, i.e., they are on the same device.

In this paper, we consider a broadband cognitive radio network, where the primary and secondary systems employ a multicarrier modulation scheme. The proposed spectrum-sharing scheme is based on additive superposition coding: specifically, the secondary transmitter acts as an amplify-and-forward relay, forwarding a linearly weighted combination of the received multicarrier primary signal and its own block of multiple symbols. Such a superposition is performed by the secondary transmitter on the fly, in a single multicarrier symbol of the primary system. Moreover, the proposed scheme does not require cooperation between the primary and secondary systems. An information-theoretic performance analysis of the proposed scheme is developed, whose findings are corroborated by means of numerical Monte Carlo simulations.

In this paper, we assess the information-theoretic performance of a point-to-point link that exploits ambient backscattering to support green Internet-of-Thing (IoT) communications. In this framework, an IoT passive device transmits its information by reusing ambient radio-frequency signals emitted by an existing or legacy multicarrier communication system. After introducing the signal model of the relevant communication links, the information-theoretic capacity of both the legacy and backscatter systems is derived. It is found that, under reasonable operative conditions, the legacy system can turn the RF interference arising from backscattering into a form of multipath diversity, which can be exploited to increase its own performance. Moreover, it is shown that, even when it employs simple single-carrier modulation techniques, the backscatter system attains significant data rates over relatively short distances.

Recently, we proposed a spectrum-sharing paradigm for single-carrier cognitive radio (CR) networks, where a secondary user (SU) is able to maintain or even improve the performance of a primary user (PU) transmission, while also obtaining a low-data rate channel for its own communication. According to such a scheme, a simple multiplication is used to superimpose one SU symbol on a block of multiple PU symbols.The scope of this paper is to extend such a paradigm to a multicarrier CR network, where the PU employs an orthogonal frequency-division multiplexing (OFDM) modulation scheme. To improve its achievable data rate, besides transmitting over the subcarriers unused by the PU, the SU is also allowed to transmit multiple block-precoded symbols in parallel over the OFDM subcarriers used by the primary system. Specifically, the SU convolves its block-precoded symbols with the received PU data in the time-domain, which gives rise to the term convolutive superposition. An information-theoretic analysis of the proposed scheme is developed, which considers different amounts of network state information at the secondary transmitter, as well as different precoding strategies for the SU. Extensive simulations illustrate the merits of our analysis and designs, in comparison with conventional CR schemes, by considering as performance indicators the ergodic capacity of the considered systems.

This paper considers the problem of jointly compensating carrier frequency offsets (CFOs) and in-phase/quadrature-phase (I/Q) imbalance effects in orthogonal frequency-division multiple-access (OFDMA) or single-carrier frequency-division multiple-access (SC-FDMA) systems. Specifically, we propose a widely-linear time-varying minimum mean-output energy compensation scheme, by deriving its data-dependent frequency-shift implementation. The performance of the proposed receiver is assessed by Monte Carlo computer simulations.

In this letter, we consider the problem of equalizing finite-impulse response (FIR) channels in orthogonal frequency-division multiplexing (OFDM) systems, which employ at the receiver a blanking nonlinearity to mitigate impulsive noise (IN). By exploiting the frequency redundancy associated with the presence of OFDM virtual carriers, we design a frequency-domain linear FIR equalizer that compensates for the intercarrier interference (ICI) generated by nonlinear preprocessing. Monte Carlo computer simulations, carried out assuming a Middleton Class A model for the IN, allows one to assess the error probability performance of the proposed equalizer.

In this paper, we propose a cognitive radio scheme that allows a secondary user (SU) to transmit over the same time-frequency slot of a primary user (PU), even when the PU is active. In our scheme, the SU amplifies and forwards the signal of the PU, by using as scaling factor the value of its information symbol to be transmitted towards the secondary receiver. The information-theoretic limits of the proposed protocol are investigated in terms of ergodic channel capacities of both the PU and SU links. It is shown that: 1) under certain operating conditions, the SU can superimpose its information symbols on the PU signal, without violating the cognitive radio principle of protecting the PU transmission; and 2) when the primary link is busy, the SU offers the PU its own transmitting power in exchange for a low-capacity communication channel, which improves the packet delay performance of the SU. In this barter, the tempting incentive for the PU consists of a noticeable improvement of its achievable rate at the price of a slight increase in the computational complexity of the primary receiver.

This paper deals with the synthesis of a new reception scheme for the uplink of a single-carrier interleaved frequency-division multiple-access (SC-IFDMA) wireless network. In such networks, the in-phase/quadrature-phase (I/Q) imbalance, introduced at each user transmitter and at the base station receiver, and the carrier frequency offsets (CFOs) between the transmitters and the receiver are sources of severe performance degradation. The proposed receiver, based on the minimum mean-output energy (MMOE) criterion, jointly mitigates CFO and I/Q imbalance effects by processing the received signal and its complex conjugate version. Monte Carlo computer simulations are carried out to assess the effectiveness of the MMOE solution.

In this paper, we propose an opportunistic amplify-and-forward relaying scheme for a cognitive radio network, which is aimed at allowing a secondary user (SU) to transmit over the same time-frequency slot of a primary user (PU). In our scheme, the SU amplifies and transmits the PU signal it receives, by using as relaying gain the information symbols that the SU wishes to transmit towards its own secondary receiver. The information theoretic limits of the proposed protocol are investigated by showing that, in some operative conditions of practical interest, the SU can embed its information symbols in the PU signal, without violating the cognitive radio principle of protecting the PU transmission and, at the same time, by attaining low transmission rates.

This paper proposes a blind channel shortening algorithm for uplink reception of a single-carrier interleaved frequency-division multiple-access (SC-IFDMA) system, affected by timing offsets (TOs) and carrier frequency offsets (CFOs), and transmitting over a highly dispersive channel. When the cyclic prefix (CP) cannot completely compensate for channel dispersion and TOs, a convenient strategy is to shorten the channel by timedomain equalization (TEQ) in order to ease signal reception. The proposed receiver exhibits a three-stage structure: the first stage performs blind channel shortening without requiring a priori knowledge of the channels or preliminary compensation of the CFOs; the second stage performs multiuser CFO compensation; finally, to alleviate noise amplification effects possibly arising from CFO compensation, the third stage implements blind peruser signal-to-noise ratio (SNR) maximization. The performance of the proposed method are assessed and compared with those of existing algorithms by Monte Carlo computer simulations.

This paper proposes a blind channel shortening algorithm for uplink reception of a single-carrier interleaved frequency-division multiple-access (SC-IFDMA) system transmitting over a highly-dispersive channel, which is affected by both timing offsets (TOs) and frequency offsets (CFOs). When the length of the cyclic prefix (CP) is insufficient to compensate for channel dispersion and TOs, a common strategy is to shorten the channel by means of time-domain equalization, in order to restore CP properties and ease signal reception. The proposed receiver exhibits a three-stage structure: the first stage performs blind shortening of all the user channel impulse responses (CIRs), by adopting the minimum mean-output energy criterion, without requiring neither a priori knowledge of the CIRs to be shortened, nor preliminary compensation of the CFOs; the second stage performs joint compensation of the CFOs; finally, to alleviate noise amplification effects, possibly arising from CFO compensation, the third stage implements per-user signal-to-noise ratio (SNR) maximization, without requiring knowledge of the shortened CIRs. A theoretical analysis is carried out to assess the effectiveness of the proposed shortening algorithm in the high-SNR regime; moreover, the performances of the overall receiver are validated and compared with those of existing methods by extensive Monte Carlo computer simulations.

This paper deals with multiple-input multiple-output (MIMO) broadband wireless communication systems, employing orthogonal frequency-division multiplexing (OFDM) with cyclic prefix (CP) in combination with space-time-frequency block coding (STFBC). In order to exploit the benefits of OFDM and STFBC in highly frequency-selective channels, without incurring in a significant increase of receiver complexity, a channel shortening prefilter is inserted at the receiver, aimed at reducing the length of the MIMO channel impulse response before CP removal. Two MIMO channel shorteners are proposed, both relying on linearly-constrained minimization of the mean-output-energy of the signal at the output of the channel shortener, where the linear constraints are optimally chosen so as to maximize the signal-to-noise ratio either at the output of the channel shortener or at the input of the STFBC maximum-likelihood decoder. Unlike other solutions proposed in the literature, these shortening designs are blind ones, i.e., a priori knowledge of the MIMO channel impulse response to be shortened is not required, and can be carried out in closed-form, i.e., iterative computation of the prefilter weights is not necessary. Numerical simulations show that, without a substantial increase in computational complexity, receivers equipped with the proposed blind channel shorteners pay only a negligible performance penalty with respect to non-blind channel shorteners, while being significantly more robust to finite sample-size effects.

In this paper, the problem of synthesizing a blind channel shortening algorithm for orthogonal frequency-division multiplexing (OFDM) systems is addressed. In particular, a commonly adopted assumption in the channel shortening framework is discussed, showing that, when it is violated, the data statistics usually needed for the synthesis of the shortening algorithms turn out to be periodically time varying (PTV) rather than time-invariant. Elaborating on this point, and considering in particular the recently proposed minimum-mean output-energy (MMOE) blind channel shortening algorithm, it is shown how its synthesis must be modified in order to account for the PTV nature of the data statistics. Numerical results assessing the performance of the proposed blind PTV-MMOE channel shortening algorithm are reported.

The problem of channel shortening equalization (CSE) for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is addressed. Relying on constrained minimization of the mean-output-energy (MOE) at the CSE output, we propose a blind channel shortening technique, which does not require a priori knowledge or estimation of the MIMO channel impulse responses to be shortened. Numerical results showing the attainable performance gain of the proposed method are reported.

Constrained optimization techniques, based on the maximum signal-to-noise-plus-interference (SINR) criterion,, are considered for joint equalization and narrowband interference (NBI) suppression in orthogonal frequency-division multiplexing (OFDM) systems. Specifically, we show that a recently proposed linear receiver (D. Darsena et al., 2005), which mitigates, in the minimum mean-output-energy sense, the NBI contribution at the receiver output, can be regarded as the solution of a constrained maximum-SINR optimization criterion and, moreover, admits an interesting three-stage decomposition. This decomposition improves the receiver robustness against errors in the estimated statistics of the received data and, most important, allows one to greatly simplify the channel estimation problem. Computer simulations are earned out to illustrate the performance improvements achievable by adopting the constrained maximum-SINR equalizer, in comparison with its unconstrained counterpart

We consider in this letter the problem of perfectly equalizing finite-impulse response (FIR) channels in digital communication systems employing nonredundant precoding at the transmitter. In this case, as it is well known, there is no linear FIR zero-forcing (ZF) block equalizer that is capable of perfectly recovering information symbols in the absence of noise. We show that, when the symbol constellation is improper, it is possible to design widely linear FIR-ZF block equalizers that, unlike their linear counterparts, process both the received signal and its complex-conjugate version. In addition, we propose a simple procedure to synthesize universal modulation-induced cyclostationary (MIC) precoders that assures perfect symbol recovery, regardless of the channel-zero locations.

The paper deals with the problem of blind mitigation of intersymbol interference (ISI) as well as multiple-access interference (MAI) in asynchronous high data-rate direct-sequence code-division multiple-access systems. A blind adaptive multiuser receiver based on the constant-modulus algorithm (CMA) is proposed, which demodulates each desired user by exploiting only the knowledge of its spreading code, without requiring estimation of the users's channels and timings. In order to overcome the CMA interference capture problem, which arises in a multiuser scenario, a two-stage adaptive receiver is adopted: In the first stage, partial MAI and ISI suppression is blindly achieved by exploiting the desired user signature structure properties; in the second stage, the residual MAI and the ISI are removed by using the CMA, and the information symbols of the desired user are reliably recovered. Theoretical analysis and simulation results show that the first stage is an effective blind adaptive strategy which allows the CMA detector in the second stage to lock on the desired-user symbol, at a particular delay. The proposed blind receiver achieves a significant performance gain in comparison with existing blind methods.

We address the problem of synthesizing blind channel identification and equalization methods for digital communications systems, aimed at counteracting the presence of cochannel or adjacent-channel interference. Owing to the presence of the interfering signal, the minimum mean-square error equalizer turns out to be linear periodically time-varying, which is implemented by resorting to its Fourier series representation. Moreover, by exploiting the cyclic conjugate second-order statistics of the channel output, we propose a new weighted subspace-based channel identification method, which is asymptotically immune to the presence of high-level interference. Computer simulation results confirm the effectiveness of the proposed identification/equalization technique.

In this paper, a new method for blind spatial signal filtering is proposed. It utilizes the selectivity property of the higher-order cyclostationary statistics exhibited by the signal of interest to accurately estimate its unknown steering vector, also in the presence of strong frequency-overlapped interfering signals, which would render the standard stationarity-based techniques ineffective. The method is useful when the desired signal cannot be accurately extracted by exploiting its second-order cyclostationarity properties, as proposed in Schell and Gardner (1993). A performance analysis, carried out by computer simulations in the case of QAM-modulated signals with partially overlapping bands, substantiates the effectiveness of the proposed method.

The problem of jointly equalizing a digital communication signal distorted by a linear time-invariant channel and rejecting co-channel or adjacent-channel digital interference is tackled. Owing to the presence of the interfering signal, the proposed optimum linear MMSE equalizer turns out to be periodically time-varying (LPTV). Moreover, new simple and effective blind channel identification procedures are presented, which can be applied as long as the desired and interfering signal exhibit different circularity and/or cyclo-stationarity properties. Simulation results confirm the effectiveness of the proposed techniques.

This paper presents a new technique for the compression of multispectral images, which relies on the segmentation of the image into regions of approximately homogeneous land cover. The rationale behind this approach is that, within regions of the same land cover, the pixels have stationary statistics and are characterized by mostly linear dependency, contrary to what usually happens for unsegmented images. Therefore, by applying conventional transform coding techniques to homogeneous groups of pixels, the proposed algorithm is able to effectively exploit the statistical redundancy of the image, thereby improving the rate distortion performance. The proposed coding strategy consists of three main steps. First, each pixel is classified by vector quantizing its spectral response vector, so that both a reliable classification and a minimum distortion encoding of each vector are obtained. Then, the classification map is entropy encoded and sent as side information, Finally, the residual vectors are grouped according to their classes and undergo Karhunen-Loeve transforming in the spectral domain and discrete cosine transforming in the spatial domain. Numerical experiments on a six-band thematic mapper image show that the proposed technique outperforms the conventional transform coding technique by 1 to 2 dB at all rates of interest.

This paper addresses the problem of narrowband interference suppression in direct-sequence spread-spectrum (DS/SS) techniques, which have been adopted to implement code division multiple access (CDMA) systems for wireless mobile communications. The theory of cyclic Wiener filtering, based on the cyclostationarity assumption for the signals involved in the reception problem, is applied to design single-channel adaptive frequency-shift filters which exploit both temporal and spectral correlation properties, i.e., the correlation between time- and frequency-shifted versions of the received signal. The numerical results show that receiving structures based on the proposed cyclostationarity-based interference suppression schemes largely outperform receivers that utilize conventional linear time-invariant suppressors, when they operate in highly contaminated interference environments.

The paper deals with signal extraction performed by processing data received by an array of sensors. The proposed method is blind, i.e., it does not require any a priori knowledge of directional information associated with the signals of interest (SOI's). Such information is obtained directly from the received data by exploiting the higher-order cyclostationarity (HOCS) properties exhibited by most communication signals. The proposed method is inherently tolerant to both possibly non-stationary Gaussian disturbances as well as non-Gaussian interferences not exhibiting the same HOCS properties presented by the SOI's. Simulation results confirm the effectiveness of the method when it operates in severely degraded disturbance environments.

This paper addresses the problem of multispectral-image compression and proposes a new encoding scheme, based on the classification of the multispectral image into regions of homogeneous land cover. Separate regions resulting from classification are efficiently encoded by means of conventional transform coding techniques, whereas the classification information is compacted resorting to spatial prediction and Ziv-Lempel coding. Simulation results show that the proposed algorithm assures both a high compression ratio and a good reproduction quality, with a reasonable computational complexity.

The paper deals with two-sensor interception of cyclostationary signals in the presence of additive non-Gaussian noise. The locally optimum approach is considered as a starting point to derive cyclostationarity-exploiting receiver structures for detecting a weak signal and locating its emission source through time-difference-of-arrival (TDOA) measurements. To obtain analytical information about the detection performance of the proposed receivers, the deflection in both constant and variable noise-level environments is evaluated. Monte Carlo simulations, aimed at evaluating the detection performance in terms of detection probability and false-alarm probability, and the TDOA estimation accuracy, have been carried out. The results show that the cyclostationarity-exploiting receivers can significantly outperform the radiometric receivers in both signal detection and source location, when the noise level is unknown or variable and/or strong interfering signals are present.