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We consider a dual-hop, decode-and-forward network, where the relay can operate in full-duplex (FD) or half-duplex (HD) mode (X-duplex relay). We model the residual self-interference as an additive Gaussian noise with variance proportional to the relay transmit power, and we assume a Gaussian input distribution at the source. Unlike previous work, we assume that the source is only aware of the transmit power distribution adopted by the relay, but not of the symbols that the relay is currently transmitting. This assumption better reflects the practical situation, where the relay node forwards data traffic but modifies physical-layer or link-layer control information. We then identify the optimal power allocation strategy at the source and relay, which in some cases coincides with the HD transmission mode. We prove that such strategy implies either FD transmissions over an entire time frame or FD/HD transmissions over a variable fraction of the frame. We determine the optimal transmit power level at the source and relay for each frame, or fraction thereof. We compare the performance of our scheme against reference FD and HD techniques, which assume that the source is aware of the symbols instantaneously transmitted by the relay, and show that our solution closely approaches such strategies. [ABSTRACT FROM AUTHOR]

This paper presents the first systematic investigation of the potential performance gains for crowd work systems, deriving from available information at the requester about individual worker reputation. In particular, we first formalize the optimal task assignment problem when workers’ reputation estimates are available, as the maximization of a monotone (submodular) function subject to Matroid constraints. Then, being the optimal problem NP-hard, we propose a simple but efficient greedy heuristic task allocation algorithm. We also propose a simple “maximum a-posteriori” decision rule and a decision algorithm based on message passing. Finally, we test and compare different solutions, showing that system performance can greatly benefit from information about workers’ reputation. Our main findings are that: i) even largely inaccurate estimates of workers’ reputation can be effectively exploited in the task assignment to greatly improve system performance; ii) the performance of the maximum a-posteriori decision rule quickly degrades as worker reputation estimates become inaccurate; iii) when workers’ reputation estimates are significantly inaccurate, the best performance can be obtained by combining our proposed task assignment algorithm with the message-passing decision algorithm. [ABSTRACT FROM PUBLISHER]

We analyze the capacity scaling laws of clustered ad hoc networks comprising significant inhomogeneities in the node spatial distribution over the area. In particular, we consider the class of networks in which nodes are distributed according to a doubly stochastic shot-noise Cox process, which allows to model a wide variety of inhomogeneous topologies. For this class of networks, we derive information theoretic upper-bounds to the capacity, identifying six operational regions. We also provide constructive lower bounds by devising, for each region, an optimal communication strategy to achieve the maximum network throughput. The performance of our communication schemes match, in terms of scaling exponent, the theoretical upper-bounds. [ABSTRACT FROM AUTHOR]

Environmental monitoring is often performed through wireless sensor networks, by randomly deploying sensor nodes over the geographical region of interest. Sensors sample a physical phenomenon (the so-called field) and send their measurements to a sink, which is in charge of reconstructing the field from such irregular samples. In this work, we focus on scenarios of practical interest where the sensor deployment is unfeasible in certain areas of the geographical region (e.g., due to terrain asperities), and the delivery of sensor measurements to the sink may fail (e.g., due to fading or to transmission collisions among sensors simultaneously accessing the wireless medium). Under these conditions, we carry out an asymptotic analysis and evaluate the quality of the estimation of a field defined over a d-dimensional domain (d\geq 1) when the sink uses linear filtering as a reconstruction technique. Specifically, given the matrix \bf V representing the sampling system, we let the size of \bf V go to infinity and its aspect ratio have a finite limit bounded away from zero. Then, we provide both the moments and density of the limiting spectral distribution of \bf VV^\ssr H, in terms of those obtained when the samples collected by the sink correspond to locations that are uniformly distributed over the geographical area. By using such asymptotic results, we approximate the mean square error on the estimated field through the \eta-transform of \bf VV^\ssr H, and we derive the sensor network performance under the conditions described above. [ABSTRACT FROM PUBLISHER]

We study the performance of systems for signal parameters estimation, which are based on the linear minimum mean square error (LMMSE) filtering. Such an estimation technique is widely used in practical scenarios, specifically wireless sensor networks and MIMO communications. We model the estimation system through sums and products of random matrices, involving a d-fold Vandermonde matrix (d\geq 1) with entries uniformly distributed on the complex unit circle. Then, we derive the mean square error (MSE) of the estimated signal by resorting to asymptotic analysis and by applying the \eta-transform operator. We describe how our results can be exploited for the study of practical systems, and we show the agreement existing between the asymptotic results derived through our analysis and the simulation results obtained for small values of d. [ABSTRACT FROM AUTHOR]

We study a class of random matrices that appear in several communication and signal processing applications, and whose asymptotic eigenvalue distribution is closely related to the reconstruction error of an irregularly sampled bandlimited signal. We focus on the case where the random variables characterizing these matrices are (i-dimensional vectors, independent, and quasi-equally spaced, i.e., they have an arbitrary distribution and their averages are vertices of a d-dimensional grid. Although a closed form expression of the eigenvalue distribution is still unknown, under these conditions we are able i) to derive the distribution moments as the matrix size grows to infinity, while its aspect ratio is kept constant, and ii) to show that the eigenvalue distribution tends to the Marčenko-Pastur law as d → ∞. These results can find application in several fields, as an example we show how they can be used for the estimation of the mean square error provided by linear reconstruction techniques. [ABSTRACT FROM AUTHOR]

One of the most significant types of error in digital signal processing (DSP) systems working with wideband signals is the error introduced by the analog-to-digital (AD) and digital-to-analog (DA) converters. This paper presents an accurate and simple method to evaluate the performance of AD/DA converters affected by clock jitter, which is based on the analysis of the mean square error (MSE) between the reconstructed signal and the original one. Using an approximation of the linear minimum MSE (LMMSE) filter as reconstruction technique, we derive analytic expressions of the MSE. In particular, through asymptotic analysis, we are able to simply evaluate the performance of digital signal reconstruction as a function of the clock jitter, number of quantization bits, signal bandwidth and sampling rate. [ABSTRACT FROM AUTHOR]

We focus on a multidimensional field with uncorrelated spectrum and study the quality of the reconstructed signal when the field samples are irregularly spaced and affected by independent and identically distributed noise. More specifically, we apply linear reconstruction techniques and take the mean-square error (MSE) of the field estimate as a metric to evaluate the signal reconstruction quality. We find that the MSE analysis could be carried out by using the closed-form expression of the eigenvalue distribution of the matrix representing the sampling system. Unfortunately, such distribution is still unknown. Thus, we first derive a closed-form expression of the distribution moments, and we find that the eigenvalue distribution tends to the Mar~enko-Pastur distribution as the field dimension goes to infinity. Finally, by using our approach, we derive a tight approximation to the MSE of the reconstructed field. [ABSTRACT FROM AUTHOR]

We consider a wireless sensor network, sampling a bandlimited field, described by a limited number of harmonics. Sensor nodes are irregularly deployed over the area of interest or subject to random displacement; in addition sensors measurements are affected by noise. Our goal is to obtain a high quality reconstruction of the field, with the mean square error (MSE) of the estimate as performance metric. In particular, we analytically derive the performance of several reconstruction/estimation techniques based on linear filtering. For each technique, we obtain the MSE, as well as its asymptotic expression in the case where the number of field-harmonics and the number of sensors grow to infinity, while their ratio is kept constant. Through numerical simulations, we show the validity of the asymptotic analysis, even for a small number of sensors. We provide some novel guidelines for the design of sensor networks when many parameters, such as field bandwidth, number of sensors, reconstruction quality, and sensor displacement characteristics, to be traded off. [ABSTRACT FROM AUTHOR]

We consider a multiuser multiple-input multiple-output (MIMO) communication system using code-division multiple access (CDMA) and multiuser detection to discriminate the different users. Our focus is on the CDMA uplink of a frequency-nonselective Rayleigh fading channel. We study two types of receivers: joint receivers, which address simultaneously both spatial and multiple-access interference; and separate receivers, addressing the two types of interference individually. This approach allows assessing the benefits of adding MIMO processing capabilities to existing multiuser single-input single-output systems. For both receiver types, we analyze solutions based on linear (matched filter, decorrelator, minimum mean-square error) and maximum-likelihood receivers. For all the receivers considered, we provide closed-form expressions (as expectations of given functions) of the resulting pairwise error probabilities. Performance results are obtained in terms of frame-error rate versus Eb/No, following two different approaches. An analytic approach using large-system asymptotic methods, whereby the system parameters (number of users and antennas, spreading gain) are assumed to grow to infinity with finite limiting ratios. A computer-simulation approach is used to illustrate the differences between asymptotic and simulation results. [ABSTRACT FROM AUTHOR]

We examine the performance of a reduced-complexity doubly iterative decoder for space-time turbo codes on a quasi- static fading channel. The decoder works by using preliminary soft values of the coded symbols, obtained after a limited number of turbo iterations, to reduce the spatial interference from the received signal. Then, new turbo iterations are performed to improve on the quality of the soft values, and so on. Using a number of approximations, we obtain a receiver interface that achieves a good tradeoff between performance and complexity, and allows the use of turbo space-time codes for a large number of transmit and receive antennas. [ABSTRACT FROM AUTHOR]

We compare suboptimum linear and nonlinear interfaces to be used for decoding space-time codes transmitted over a multiple-antenna Rayleigh fading channel with perfect channelstate information available at the receiver. The codes we consider are obtained by apportioning evenly, among the transmit antennas, the symbols of off-the-shelf convolutional codes. We observe how the introduction of an interleaver can be beneficial here. We introduce a new simple iterative linear interface, based on hard Viterbi decoding and offering a performance considerably improved with respect to noniterative receivers. [ABSTRACT FROM AUTHOR]

We present an information-theoretic analysis of a point-to-point multiple-input multiple-output (MIMO) link affected by Rayleigh fading and multiple scattering, under perfect channel state information at the receiver. Unlike previous work addressing this setting, we investigate the random coding error exponent, its associated cutoff rate and the expurgated error exponent, and derive closed-form expressions for them. Moreover, leveraging the average mutual information expression presented by Akemann et al., we derive another important metric, namely, the sum rate, under linear receive processing and independent stream decoding. In particular, we characterize the performance of the minimum mean squared error receiver in closed form, and that of the zero forcing receiver by resorting to bounding techniques. The bulk of the work relies on results about finite-dimensional random matrix products, a number of which are novel and detailed in the Appendices. The analysis, validated through numerical results, highlights the severe degradation in the performance of linear receivers due to multi-fold scattering. It also unveils the performance trend of multiple scattering MIMO channels as a function of the number of antennas and the number of scattering stages. [ABSTRACT FROM AUTHOR]

The information that can be transmitted through a wireless channel, with multiple-antenna-equipped transmitter and receiver, is crucially influenced by the channel behavior as well as by the structure of the input signal. We characterize in closed form, the probability density function (pdf) of the output of multiple-input and multiple-output block-fading channels, for an arbitrary signal-to-noise ratio value. Our results provide compact expressions for such output statistics, paving the way to a more detailed analytical information-theoretic exploration of communications in presence of block fading. The analysis is carried out assuming two different structures for the input signal: 1) the independent identically distributed (i.i.d.) Gaussian distribution and 2) a product form that has been proved to be optimal for noncoherent communication, i.e., in absence of any channel state information. When the channel is fed by an i.i.d. Gaussian input, we assume the Gramian of the channel matrix to be unitarily invariant and derive the output statistics in both the noise- and interference-limited scenario, considering different fading distributions. When the product-form input is adopted, we provide the expressions of the output pdf as the relationship between the overall number of antennas and fading coherence length varies. We also highlight the relation between our newly derived expressions and the results already available in the literature, and, for some cases, we numerically compute the mutual information based on the proposed expression of the output statistics. [ABSTRACT FROM AUTHOR]

Focuses on a study which considered the initial timing acquisition in discrete-sequence code-division multiple-access and the subsequent effect of multipath fading. Application of maximum-likelihood estimation in constrained maximization problem; Discussion on Doppler spectrum and slow fading channel; Methodology and results.