Channel Estimation for Diffusive MIMO Molecular Communications

In diffusion-based communication, as for molecular systems, the achievable data rate is very low due to the slow nature of diffusion and the existence of severe inter-symbol interference (ISI). Multiple-input multiple-output (MIMO) technique can be used to improve the data rate. Knowledge of channel impulse response (CIR) is essential for equalization and detection in MIMO systems. This paper presents a training-based CIR estimation for diffusive MIMO (D-MIMO) channels. Maximum likelihood and least-squares estimators are derived, and the training sequences are designed to minimize the corresponding Cram\'er-Rao bound. Sub-optimal estimators are compared to Cram\'er-Rao bound to validate their performance.Comment: 5 pages, 5 figures, EuCNC 201

Diffusive MIMO Molecular Communications: Channel Estimation, Equalization and Detection

In diffusion-based communication, as for molecular systems, the achievable data rate is low due to the stochastic nature of diffusion which exhibits a severe inter-symbol-interference (ISI). Multiple-Input Multiple-Output (MIMO) multiplexing improves the data rate at the expense of an inter-link interference (ILI). This paper investigates training-based channel estimation schemes for diffusive MIMO (D-MIMO) systems and corresponding equalization methods. Maximum likelihood and least-squares estimators of mean channel are derived, and the training sequence is designed to minimize the mean square error (MSE). Numerical validations in terms of MSE are compared with Cramer-Rao bound derived herein. Equalization is based on decision feedback equalizer (DFE) structure as this is effective in mitigating diffusive ISI/ILI. Zero-forcing, minimum MSE and least-squares criteria have been paired to DFE, and their performances are evaluated in terms of bit error probability. Since D-MIMO systems are severely affected by the ILI because of short transmitters inter-distance, D-MIMO time interleaving is exploited as countermeasure to mitigate the ILI with remarkable performance improvements. The feasibility of a block-type communication including training and data equalization is explored for D-MIMO, and system-level performances are numerically derived.Comment: Accepted paper at IEEE transaction on Communicatio

A subspace method for channel estimation in soft-iterative receivers

In this paper we propose a new soft method for the estimation of block-fading channels based on multi-block (MB) processing. The MB estimator [1] exploits the invariance of the subspace spanned by the multipath components of the channel and it estimates the channel subspace by sample averaging over a frame of blocks. Here the MB method is extended to incorporate also soft information, which is available in iterative (turbo) equalizers. The mean square error (MSE) of the soft-based estimate is evaluated analytically and validated by simulations. The comparison with the conventional training-based block-by-block estimate shows the benefits of the proposed approach on the turbo equalizer convergence

Hypergraph-Based Analysis of Clustered Cooperative Beamforming with Application to Edge Caching

The evaluation of the performance of clustered cooperative beamforming in cellular networks generally requires the solution of complex non-convex optimization problems. In this letter, a framework based on a hypergraph formalism is proposed that enables the derivation of a performance characterization of clustered cooperative beamforming in terms of per-user degrees of freedom (DoF) via the efficient solution of a coloring problem. An emerging scenario in which clusters of cooperative base stations (BSs) arise is given by cellular networks with edge caching. In fact, clusters of BSs that share the same requested files can jointly beamform the corresponding encoded signals. Based on this observation, the proposed framework is applied to obtain quantitative insights into the optimal use of cache and backhaul resources in cellular systems with edge caching. Numerical examples are provided to illustrate the merits of the proposed framework.Comment: 10 pages, 5 figures, Submitte

Ordered Tomlinson-Harashima Precoding in G.fast Downstream

G.fast is an upcoming next generation DSL standard envisioned to use bandwidth up to 212 MHz. Far-end crosstalk (FEXT) at these frequencies greatly overcomes direct links. Its cancellation based on non-linear Tomlinson-Harashima Precoding (THP) proved to show significant advantage over standard linear precoding. This paper proposes a novel THP structure in which ordering of successive interference pre-cancellation can be optimized for downstream with non-cooperating receivers. The optimized scheme is compared to existing THP structure denoted as equal-rate THP which is widely adopted in wireless downlink. Structure and performance of both methods differ significantly favoring the proposed scheme. The ordering that maximizes the minimum rate (max-min fairness) for each tone of the discrete multi-tone modulation is the familiar V-BLAST ordering. However, V-BLAST does not lead to the global maximum when applied independently on each tone. The proposed novel Dynamic Ordering (DO) strategy takes into account asymmetric channel statistics to yield the highest minimum aggregated rate.Comment: 7 pages, 11 figures, Accepted at the 2015 IEEE Globecom 2015, Selected Areas in Communications: Access Networks and Systems, 6-10 December, 201

On the Transport Capability of LAN Cables in All-Analog MIMO-RoC Fronthaul

Centralized Radio Access Network (C-RAN) architecture is the only viable solution to handle the complex interference scenario generated by massive antennas and small cells deployment as required by next generation (5G) mobile networks. In conventional C-RAN, the fronthaul links used to exchange the signal between Base Band Units (BBUs) and Remote Antenna Units (RAUs) are based on digital baseband (BB) signals over optical fibers due to the huge bandwidth required. In this paper we evaluate the transport capability of copper-based all-analog fronthaul architecture called Radio over Copper (RoC) that leverages on the pre-existing LAN cables that are already deployed in buildings and enterprises. In particular, the main contribution of the paper is to evaluate the number of independent BB signals for multiple antennas system that can be transported over multi-pair Cat-5/6/7 cables under a predefined fronthauling transparency condition in terms of maximum BB signal degradation. The MIMO-RoC proves to be a complementary solution to optical fiber for the last 200m toward the RAUs, mostly to reuse the existing LAN cables and to power-supply the RAUs over the same cable

Wireless Communications with Space-Time Modulated Metasurfaces

Space-time modulated metasurfaces (STMMs) are a newly investigated technology for next 6G generation wireless communication networks. An STMM augments the spatial phase function with a time-varying one across the elements, allowing for the conveyance of information that possibly modulates the impinging signal. Hence, STMM represents an evolution of reconfigurable intelligent surfaces (RIS), which only design the spatial phase pattern. STMMs convey signals without a relevant increase in the energy budget, which is convenient for applications where energy is a strong constraint. This paper proposes a mathematical model for STMM-based wireless communication, that creates the basics for two potential STMM architectures. One has excellent design flexibility, whereas the other is more cost-effective. The model describes STMM's distinguishing features, such as space-time coupling, and their impact on system performance. The proposed STMM model addresses the design criteria of a full-duplex system architecture, in which the temporal signal originating at the STMM generates a modulation overlapped with the incident one. The presented numerical results demonstrate the efficacy of the proposed model and its potential to revolutionize wireless communication

Wireless Sensor Network Modeling and Deployment Challenges in Oil and Gas Refinery Plants

Wireless sensor networks for critical industrial applications are becoming a remarkable technological paradigm. Large-scale adoption of the wireless connectivity in the field of industrial monitoring and process control is mandatorily paired with the development of tools for the prediction of the wireless link quality to mimic network planning procedures similar to conventional wired systems. In industrial sites, the radio signals are prone to blockage due to dense metallic structures. The layout of scattering objects from the existing infrastructure influences the received signal strength observed over the link and thus the quality of service (QoS). This paper surveys the most promising wireless technologies for industrial monitoring and control and proposes a novel channel model specifically tailored to predict the quality of the radio signals in environments affected by highly dense metallic building blockage. The propagation model is based on the diffraction theory, and it makes use of the 3D model of the plant to classify the links based on the number and density of the obstructions surrounding each individual radio device. Accurate link classification opens the way to the optimization of the network deployment to guarantee full end-to-end connectivity with minimal on-site redesign. The link-quality prediction method based on the classification of propagation conditions is validated by experimental measurements in two oil refinery sites using industry standard ISA SP100.11a compliant devices operating at 2.4 GHz