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In this work, we consider a backscatter communication system wherein multiple asynchronous sources (tags) exploit the reverberation generated by a nearby radar transmitter as an ambient carrier to deliver a message to a common destination (reader) through a number of available subchannels. We propose a new encoding strategy wherein each tag transmits both pilot and data symbols on each subchannel and repeats some of the data symbols on multiple subchannels. We then exploit this signal structure to derive two semi-blind iterative algorithms for joint estimation of the data symbols and the subchannel responses that are also able to handle some missing measurements. The proposed encoding/decoding strategies are scalable with the number of tags and their payload and can achieve different tradeoffs in terms of transmission and error rates. Some numerical examples are provided to illustrate the merits of the proposed solutions.

Reconfigurable Intelligent Surface (RIS) brings a transformative potential to radar systems by providing a new dimension to control electromagnetic waves. This paper focuses on enhancing target detectability through the design and analysis of RIS-aided radar. A comprehensive signal model is established, recognizing both Line of Sight (LoS) and Non-Line of Sight (N-LoS) returns, factoring in RIS location and range gate shifts. This modeling enables an examination of the RIS-dependent effect of enlarged clutter region, underscoring the essential need for precise RIS phase optimization. A joint design problem encompassing transmit waveform, receive filter, and RIS phase is then formulated with the aim to optimize Signal-to-Interference-plus-Noise-Ratio (SINR), complying with practical waveform constraints and discrete RIS phase alphabet. For this nonconvex problem, an iterative algorithm is developed to monotonically enhance SINR, ensuring convergence by alternately updating the radar waveform and RIS phases. Through the majorization-minimization framework, radar waveform updates are achieved using the feasible point pursuit technique, while a quasi-closed form solution is employed for the RIS phases. Simulation results demonstrate the efficacy of the proposed design, revealing the crucial role of RIS in the system.

Colocated multiple-input multiple-output (MIMO) technology has been widely used in automotive radars as it provides accurate angular estimation of the objects with a relatively small number of transmitting and receiving antennas. Since the Direction Of Departure (DOD) and the Direction Of Arrival (DOA) of line-of-sight targets coincide, MIMO signal processing allows for the formation of a larger virtual array for angle finding. However, multiple paths impinging the receiver is a major limiting factor, in that radar signals may bounce off obstacles, creating echoes for which the DOD does not equal the DOA. Thus, in complex scenarios with multiple scatterers, the direct paths of the intended targets may be corrupted by indirect paths from other objects, which leads to inaccurate angle estimation or ghost targets. In this paper, we focus on detecting the presence of ghosts due to multipath by regarding it as the problem of deciding between a composite hypothesis, ${\cal H}_{0}$ say, that the observations only contain an unknown number of direct paths sharing the same (unknown) DOD's and DOA's, and a composite alternative, ${\cal H}_{1}$ say, that the observations also contain an unknown number of indirect paths, for which DOD's and DOA's do not coincide. We exploit the Generalized Likelihood Ratio Test (GLRT) philosophy to determine the detector structure, offering closed-form expressions for theoretical detection performance, and a convex waveform optimization approach to improve detection performance. In practical scenarios, the unknown parameters of GLRT philosophy are replaced by carefully designed estimators. The angles of both the active direct paths and of the multi-paths are indeed estimated through a sparsity-enforced Compressed Sensing (CS) approach with Levenberg-Marquardt (LM) optimization to estimate the angular parameters in the continuous domain. Simulation and experimental results are finally offered in order to validate the proposed solution.

In this work, we exploit the radar clutter (i.e., the ensemble of echoes generated by the terrain and/or the surrounding objects in response to the signal emitted by a radar transmitter) as a carrier signal to enable an ambient backscatter communication from a source (tag) to a destination (reader). The proposed idea relies on the fact that, since the radar excitation is periodic, the radar clutter is itself periodic over time scales shorter than the coherence time of the environment. Upon deriving a convenient signal model, we propose two encoding/decoding schemes that do not require any coordination with the radar transmitter or knowledge of the radar waveform. Different tradeoffs in terms of transmission rate and error probability can be obtained upon changing the control signal driving the tag switch or the adopted encoding rule; also, multiple tags can be accommodated with either a sourced or an unsourced multiple access strategy. Some illustrative examples are provided.

Spectrum sensing for cognitive-radio applications may use a matched-filter detector (in the presence of full knowledge of the signal that may be transmitted by the primary user) or an energy detector (when that knowledge is missing). An intermediate situation occurs when the primary signal is imperfectly known, in which case we advocate the use of a linear-quadratic detector. We show how this detector can be designed by maximizing its deflection, and, using moment-bound theory, we examine its robustness to the variations of the actual probability distribution of the inaccurately known primary signal.

The problem of blind adaptive multiuser detection in multirateCDMA systems is considered. Indeed, since symboldetection in multirate CDMA systems requires periodicallytime-varying processing of the observables, classical LMS and RLSadaptive algorithms, which assume that the solution to be trackedis time-invariant or slowly time-varying, are not suited for blindadaptive multiuser detection in a multirate system. While a cyclicRLS algorithm has recently appeared in the literature, thispaper focuses on the development of LMS-based cyclic filteringalgorithms. In particular, cyclic versions of the standard LMSalgorithm, of the LMS algorithm with iterate averaging and of theLMS algorithm with adaptive step-size are derived. Interestingly,the last two algorithms are shown to exhibit a convergence speed close to thatof the cyclicRLS procedure, but with an order of magnitude lower computationalcomplexity.An adaptive procedure for the automatic selection ofthe algorithm periodicity is also presented, which is based on aminimum mean-output-energy criterion, and that obviates theneed for knowledge of the transmitted data-rates from theinterfering signals.Moreover, the case of known multipathfading channels is also examined. In particular, it is shown that theproposed cyclic LMS algorithms can be used to achieve RLS-likeperformance also in the presence of multipath distortion.Extensive computer simulation results, along with some analyticalconvergence results, confirmthat the proposed algorithms are effective and achieve very satisfactoryperformance.

In a Dual-Rate DS/CDMA system, a primary, ``high rate'' network coexists witha secondary one with a slower rate. Demultiplexinghigh-rate users typically entails, at the receiverend, a time-varying processing ifVariable Spreading Length (VSL), Variable Chip Rate (VCR), or Variable ChipRate with Frequency Shift (VCRFS) modulation formats are used, and Rake-Typedemodulation schemes if the chip rate exceeds the channel coherence bandwidth.The realization of fully adaptive receivers thus requires the joint estimationof(a) the interference to be suppressed, whether from other users ofthe high-ratenetwork or from the secondary network, and (b) the channel tap weights.The solutionthat we consider here assumes that,for each user, a pilot signal is transmitted alongwith the information-bearing signal, whether in a time-multiplexed orin a parallel-channel format. We consider both the uplink and the downlink channel and, based on a Minimum-Mean-Square-Error(MMSE) optimality criterion, we have come up with a fully adaptive system,capable on the one handof tracking, through a cyclic Recursive-Least-Squares typealgorithm, the periodically time-varying variations of theinterference subspace andon the other of updating the channel tap weights estimates.A thorough performance assessment is presented, and the convergence dynamicsof the system are derived through computer simulations in order to assessthe impact of the prior uncertainty with regard to the other-users signaturesand thechannel tap weights realizations.

In this work the authors introduce and analyze a detection scheme for simultaneous suppression ofmultiaccess and digital narrowband interference (NBI) for an asynchronousDS/CDMA system operatingover a frequency-selective fading channel. The proposed detector may possibly consider a processing interval greater than the bit-interval, andamounts to a RAKE structure, wherein each branch is designed under an MMSE optimization strategy, followedby a propercombining rule. It is shown that narrowband interference rejection entails ingeneral a time-varyingdetection structure. As to the performance assessment, we give closed-form formulas for the systemBit Error Rate (BER),Near-Far Resistance and Signal-to-Interference Ratio (SIR).Numerical results show that the proposed receiver proves effective in suppressing interference, and that itlargely outperforms conventional multiuser detectors which do not account forthe presence of theNBI, at the price of little complexity increase.Finally, we provide a blind adaptive implementation of the proposedreceiver, based on the exponentially weighted Recursive-Least-Squares (RLS)algorithm, andrequiring knowledge of the relevant parameters of the desired user only, andof the NBI signaling time.

Signal and image and detection systems based on nonlinear operations of Fourier-transformed data often exhibit greater selectivity than standard matched-filtering techniques. One such system is the joint transform correlator. We analyze the performance of the nonlinear joint transform correlator in terms of the output signal-to-noise ratio; this signal-to-noise ratio is evaluated in terms of both output contrast (peak-to-noise floor) and output variability (peak-to-peak standard deviation). The main assumption used is that the signal energy is small relative to that of the additive noise; this assumption is defensible in practice owing to the generally small spatial extent of target images relative to scenes. With respect to the first performance measure, this study is an extension of that in an earlier paper [Appl. Opt.34, 5218 (1995)]. The previous analysis was carried out under a restriction that the signal and noise spectra were to be similar (actually multiples of one another). In the current study there is no such constraint, and all analysis of the second measure is new. The analysis is supported by simulation. A benefit of analytical rather than simulational study is that conclusions can be drawn with greater confidence. One of the most interesting of these is that the smooth square-root Fourier plane nonlinearity, more usually known as the k-law processor with k = 0.5, offers extremely robust performance with respect to relative noise bandwidth.

The problem of blind multiuser detection for an asynchronous multicarrier DS-CDMA system employing multiple transmit and receive antennae over a Rayleigh fading channel is considered in this paper. The solutions that we develop require prior knowledge of the spreading code of the user to be decoded only, while no further information either on the user to be decoded or on the other active users is required. Several combining rules for the observables at the output of each receive antenna are proposed and assessed, and the implications of the different options are studied in depth in terms of both detection performance and computational complexity. A closed form expression is also derived for the conditional error probability and a lower bound for the near-far resistance is provided. Results confirm that the proposed blind receivers can cope with both multiple access interference suppression and channel estimation at the price of a limited performance loss as compared to the ideal linear receivers which assume perfect channel state information.