Sergio Barbarossa

Parameter estimation of spread spectrum frequency-hopping signals using time-frequency distributions

In this paper we propose a method for estimating the parameters of frequency-hopping (FH) signals embedded in noise. The method is based on two main steps: (i) representation of the signal in the time-frequency domain; (ii) integration in the time-frequency domain along paths expressed in a parametric form depending on the parametric law characterizing the signal instantaneous frequency. The method does not make any assumption about the alphabet of hopping frequencies, the duration of each hop, or the synchronization. The performance of the method is given in terms of estimation variances.

Decoding and equalization of unknown multipath channels based on block precoding and transmit-antenna diversity

Transmit-antenna diversity has been exploited previously to develop high-performance space-time coders and simple maximum-likelihood decoders for transmissions over known flat fading channels. Based on blocking and multiple transmit-antennas, this paper derives novel precoders and decoders that eliminate intersymbol interference and achieve transmit diversity gain in the unknown multipath channels. When unknown, channel status information is acquired blindly based on a deterministic variant of the constant-modulus algorithm. The system performance is evaluated both analytically and with simulations.

Blind equalization using cost function matched to the signal constellation

The constant modulus algorithm (CMA) has been proved to be very effective when used to equalize non-minimum-phase channels blindly. However, the CMA suffers from a residual intersymbol interference (ISI) and slow convergence when applied to high order non-constant modulus (e.g. QAM) constellations and the equalizer is an FIR filter. We propose a method that is able to provide a lower ISI and a faster convergence rate than the CMA, based on cost functions specifically matched to the signal constellation. It is different from other CMA methods, where the matching between a certain number of cumulants between the equalizer output and the signal constellation is the driving criterion, the cost function used in this paper tries to force the equalizer output to belong to the signal constellation. The superiority of the proposed approach with respect to conventional approaches is verified by simulation.

Non-data-aided frequency-offset and channel estimation in OFDM: and related block transmissions

The many advantages responsible for the widespread application of OFDM are primarily limited by its sensitivity to carrier frequency-offsets. Most of the literature dealing with this problem focuses on data-aided frequency-offset estimation only. In this contribution, several non-data-aided frequency-offset and channel estimation schemes are developed for OFDM transmissions over frequency-selective channels. Timing offset is also accounted for because it is incorporated as a pure delay in the unknown channel. The resulting blind estimation methods include subspace based deterministic or statistical algorithms. Simulations illustrate the performance tradeoffs of these schemes.

Mutually orthogonal transceivers for blind uplink CDMA irrespective of multipath channel nulls

Suppression of multiuser interference (MUI) and mitigation of multipath effects constitute major challenges in the design of third-generation wireless mobile systems. Most wideband and multicarrier uplink CDMA schemes suppress MUI statistically in the presence of unknown multipath. For fading resistance, they all rely on transmit- or receive-diversity and multichannel equalization based on bandwidth-consuming training or blind techniques. Either way, they impose restrictive and difficult to check conditions on the FIR channel nulls. Relying on symbol blocking, we design a mutually-orthogonal usercode-receiver (AMOUR) system for quasi-synchronous blind CDMA that eliminates MUI deterministically and mitigates fading irrespective of the unknown multipath and the adopted signal constellation. Analytic evaluation and preliminary simulations reveal the generality, flexibility, and superior performance of AMOUR over competing alternatives.

Optimal adaptive precoding for frequency-selective Nagakami-m fading channels

DMT transmissions with optimal power and bit loading are suitable for wired-line applications but have high complexity when it comes to wireless time-varying environments. Adaptive modulation on the other hand, assumes that training sequences are available to provide an accurate estimate of the channel parameters, while the channel statistics allow one to evaluate the average performance. Random channel modeling is a powerful tool for assessing wireless systems performance, but can be also be instrumental in optimizing the modulation. We develop optimal loading strategies for frequency selective fading, assuming OFDM modulation and by modeling the channel impulse response as an FIR filter whose taps are Nagakami-m correlated fading processes. The design minimizes the BER for a given average transmit power. Channel statistics need to be updated at a very slow rate when compared to the exact channel status information (CSI), which reduces complexity of our adaptive OFDM scheme compared to a standard DMT approach. This also alleviates the need of training and allows us to incorporate partial channel knowledge in the design. Interestingly, our derivations identify the optimal solution for the limiting case where the channel transfer function is exactly known at both transmitter and receiver.

Adaptive detection of polynomial-phase signals embedded in noise using high-order ambiguity functions

The parameter estimation of polynomial-phase signals (PPS) has been extensively studied in the literature in view of possible important applications in remote sensing as well as in telecommunications. However, the detection of PPS has not received similar attention. We propose and analyze an adaptive method for the detection of PPS embedded in white Gaussian noise based on the use of the so called product high order ambiguity function.

Robust OFDM transmissions over frequency-selective channels with multiplicative time-selective effects

OFDM systems enable simple and effective schemes to mitigate frequency-selective fading channels. However, they are extremely sensitive to multiplicative fluctuations induced by time-varying multipath delays, carrier offsets and oscillators phase noise. Although the duration of OFDM symbols is chosen smaller than the channel coherence time to avoid, or reduce, channel time variations, this choice limits system efficiency. In this paper, we propose a generalized OFDM scheme capable of estimating and then compensating channel frequency selectivity and multiplicative noise effects using a deterministic method that exploits the redundancy added to the transmitted sequence in the form of pilot tones and null guard intervals in the frequency domain. The proposed method applies to channels modeled as the cascade of dispersive filters whose output is corrupted by both additive and multiplicative noise.

Optimal power loading for OFDM transmissions over underspread Rayleigh time-varying channels

OFDM renders multipath channels with finite memory equivalent to parallel flat fading subchannels, over which equalization amounts to simple phase compensation. If the channel status information is known at the transmitter side, optimal power loading across subchannels is possible. Users mobility, time and carrier asynchronism introduce variations in the equivalent channel impulse response setting the channel coherence time as a boundary for the OFDM symbol duration. Optimal design should incorporate such variations, possibly avoiding the overhead of frequent training. Most adaptive modulation schemes assume knowledge of the channel response and flat fading. Modeling the channel taps as correlated Gaussian random processes, we develop the optimal power/bit loading strategies for frequency selective fading, based on the knowledge of the channel past estimates and correlation. In practice the channel sample correlation are obtained as a by-product of channel estimation which, however, does not need to be performed on a block by block basis.

Polynomial minimum shift keying modulation: simplified decoding of CPM signals

In this work we introduce the so called polynomial minimum shift keying (PMSK) modulation as a particular case of continuous phase modulations (CPM), the standard used in GSM or DECT systems. The demodulation is based on the high order ambiguity function and leads to simple implementations essentially based on FFT. The most important feature of the demodulation process of PMSK signals is Doppler tolerance and the capability, under some bandwidth constraints, for blind equalization for transmissions over multipath fading channels. The price paid is essentially in terms of oversampling and increased modulation indices to obtain satisfactory performance.