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

WMMSE resource allocation for FD-NOMA

Resource allocation in interference-limited systems is a key enabler for beyond 5G (B5G) technologies, such as multi-carrier full duplex non-orthogonal multiple access (FD-NOMA). In FD-NOMA systems resource allocation is a computation-intensive non-convex problem due to the presence of strong interference and the integrality condition on channel allocation. In this paper, we propose an iterative algorithm based on the combination of channel and power allocations aimed at the minimization of the weighted mean square error, which converges to a feasible allocation of the original problem. Experimental results show that the proposed algorithm has lower complexity than other state-of-the-art solutions for the same problem. Moreover, the presented results assess the validity of our approach showing performance close to the theoretical optimum

Optimum channel allocation in OFDMA multi-cell systems

This paper addresses the problem of allocating users to radio resources (i.e., sub-carriers) in the downlink of an OFDMA cellular system. We consider a classical multi-cellular environment with a realistic interference model and a margin adaptive approach, i.e., we aim at minimizing total transmission power while maintaining a certain given rate for each user. We discuss computational complexity issues of the resulting model and present a heuristic approach that finds optima under suitable conditions, or "reasonably good" solutions in the general case. Computational experiences show that, in a comparison with a commercial state-of-the-art optimization solver, our algorithm is quite effective in terms of both infeasibilities and transmitted powers and extremely efficient in terms of CPU times. © 2009 Springer Berlin Heidelberg

Spatial multiplexing in near field MIMO channels with reconfigurable intelligent surfaces

We consider a multiple-input multiple-output (MIMO) channel in the presence of a reconfigurable intelligent surface (RIS). Specifically, our focus is on analysing the spatial multiplexing gains in line-of-sight and low-scattering MIMO channels in the near field. We prove that the channel capacity is achieved by diagonalising the end-to-end transmitter-RIS-receiver channel, and applying the water-filling power allocation to the ordered product of the singular values of the transmitter-RIS and RIS-receiver channels. The obtained capacity-achieving solution requires an RIS with a non-diagonal matrix of reflection coefficients. Under the assumption of nearly-passive RIS, that is, no power amplification is needed at the RIS, the water-filling power allocation is necessary only at the transmitter. We refer to this design of RIS as a linear, nearly-passive, reconfigurable electromagnetic object (EMO). In addition, we introduce a closed-form and low-complexity design for RIS, whose matrix of reflection coefficients is diagonal with unit-modulus entries. The reflection coefficients are given by the product of two focusing functions: one steering the RIS-aided signal towards the mid-point of the MIMO transmitter and one steering the RIS-aided signal towards the mid-point of the MIMO receiver. We prove that this solution is exact in line-of-sight channels under the paraxial setup. With the aid of extensive numerical simulations in line-of-sight (free-space) channels, we show that the proposed approach offers performance (rate and degrees of freedom) close to that obtained by numerically solving non-convex optimization problems at a high computational complexity. Also, we show that it provides performance close to that achieved by the EMO (non-diagonal RIS) in most of the considered case studies

On Safety Enhancement in IIoT Scenarios through Heterogeneous Localization Techniques

In the field of the Industrial Internet of Things (IIoT), strictly related to Industry 4.0, one of the main aspects to be carefully considered by the governing board of a manufacturing company is the safety level to be guaranteed to the workers inside production plants. This involves daily human activities, together with production machines to be used during the working hour (and periodically maintained), and mobile industrial vehicles moving around the production plant. To this end, a precise localization of both workers and vehicles is expedient to improve the safety level—avoiding that people move inside forbidden areas or perform dangerous actions—as well as allowing a more accurate control and reporting to national authorities in charge of verifying the compliance to safety regulations (e.g., aggregated data, not shared outside the company, used to fill injuries reports in case of official inspections), in the presence of accidents and anomalous events. In this paper, we present the design of IIoT-related localization mechanisms exploiting heterogeneous communication technologies, in turn analysing how the localization can cope with the adoption of wideband (e.g., Wi-Fi) and narrowband (e.g., Narrowband IoT, NB-IoT) communication protocols and discussing how these communication paradigms may impact existing and modern production plants

Optimal Power Allocation for Full-Duplex Communications Over OFDMA Cellular Networks

We consider the optimal power allocation problem for an OFDMA small-cells network where the BSs operate in full-duplex mode. Although the problem formulation is not convex, we show that, leveraging on the intimate relationship between the minimum mean square error and the interference to noise ratio, it is possible to derive an iterative allocation scheme that provably converges to a local maximum of the sum rate. Moreover, owing to the convexity of the mean square error formulation, the proposed approach copes with unlimited number of interferers, and as such it is amenable for implementation on a generic multicell scenario. Despite we do not explicitly specify any sub-channel assignment constraint, the solution at convergence allows to fulfill the exclusivity assignment constraint in almost all cases, i.e., the constraint that each sub-channel can be assigned to at most two user pairs in the cell. The proposed allocation scheme allows to achieve fast convergence to a solution that approaches the performance of a power allocation scheme that includes an exhaustive search over all possible sub-channel assignments