Orthogonal Multiple Access with Correlated Sources: Feasible Region and Pragmatic Schemes

In this paper, we consider orthogonal multiple access coding schemes, where correlated sources are encoded in a distributed fashion and transmitted, through additive white Gaussian noise (AWGN) channels, to an access point (AP). At the AP, component decoders, associated with the source encoders, iteratively exchange soft information by taking into account the source correlation. The first goal of this paper is to investigate the ultimate achievable performance limits in terms of a multi-dimensional feasible region in the space of channel parameters, deriving insights on the impact of the number of sources. The second goal is the design of pragmatic schemes, where the sources use "off-the-shelf" channel codes. In order to analyze the performance of given coding schemes, we propose an extrinsic information transfer (EXIT)-based approach, which allows to determine the corresponding multi-dimensional feasible regions. On the basis of the proposed analytical framework, the performance of pragmatic coded schemes, based on serially concatenated convolutional codes (SCCCs), is discussed

Impacts of organizational arrangements on conservation agriculture: insights from interpretive structural modeling in Iran

Conservation agriculture (CA) has been promoted worldwide as an approach to sustainable resource management and better productivity. Promotion and adoption of CA in Iran have been receiving increased attention from the national government over recent years. Therefore, to speed up development of CA as a basis for sustainable development, drivers that influence the development of CA need to be identified and modeled. The main aim of this study is to present a comprehensive model for CA development in Iran by identifying the institutional drivers that influence its promotion and determining the relationship between drivers. At first, the drivers identified from the literature and interviews with experts, and the relationships among the drivers were explored and clarified using Interpretative Structural Modeling (ISM). A cross-impact matrix multiplication was applied to classification (MICMAC) analysis, which was then used to categorize the drivers in four sub-groups. The results showed that creating a suitable organizational structure is a very significant driving factor for CA development in Iran. Strong driving power and weak dependence associated with this factor should be treated as a critical driver. If CA shall expand more rapidly in future, then Iran’s government should invest in an appropriate organizational structure for it

Nonlinear channels: predistortion or enhanced detection?

Using a union bound on the error probability of optimal receivers for nonlinear channels, this work points out important factors affecting the error performance in the simple case of M-ary pulse amplitude modulation (M-PAM) with no intersymbol interference and unlimited transmission bandwidth. The performance is compared to that obtainable when the nonlinear device is perfectly linearized under a peak power constraint. Considered nonlinearities include third-order polynomials and soft-limiters. Simulation results are in good agreement with the derived theoretical bounds. The analysis suggests that margins for improved performance exist, with respect to the performance obtainable by perfect linearization, when the cardinality of the signal set is not large (e.g., 4- or 8-PAM) and the nonlinearity is not severely saturated

Optimal sequence detection based on oversampling for bandlimited nonlinear channels

Based on a polynomial representation of a memoryless bandpass nonlinearity, a new realization of an optimal receiver is proposed to perform maximum likelihood detection of data sequences transmitted over nonlinear, possibly time-dispersive, channels. The receiver employs oversampling of the observed signal to compute proper branch metrics for a Viterbi processor. Error performance is compared to that of an optimal receiver for the linear channel obtained by ideal analog predistortion of the nonlinear device under a peak-power constraint. In the presence of nonlinear distortion, a significant improvement in the symbol error rate is shown to be achievable by optimal detection with respect to ideal predistortion. The numerical results are based on both analytic and simulation methods