Performance of Linear Field Reconstruction Techniques with Noise and Uncertain Sensor Locations

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 motion; 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 field number of 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, sensor motion characteristics, and noise level of the measures, have to be traded off

Upper Bounds to the Performance of Cooperative Traffic Relaying in Wireless Linear Networks

Wireless networks with linear topology, where nodes generate their own traffic and relay other nodes' traffic, have attracted increasing attention. Indeed, they well represent sensor networks monitoring paths or streets, as well as multihop networks for videosurveillance of roads or vehicular traffic. We study the performance limits of such network systems when (i) the nodes' transmissions can reach receivers farther than one-hop distance from the sender, (ii) the transmitters cooperate in the data delivery, and (iii) interference due to concurrent transmissions is taken into account. By adopting an information-theoretic approach, we derive analytical bounds to the achievable data rate in both the cases where the nodes have full-duplex and half-duplex radios. The expressions we provide are mathematically tractable and allow the analysis of multihop networks with a large number of nodes. Our analysis highlights that increasing the number of coop- erating transmitters beyond two leads to a very limited gain in the achievable data rate. Also, for half-duplex radios, it indicates the existence of dominant network states, which have a major influence on the bound. It follows that efficient, yet simple, communication strategies can be designed by considering at most two cooperating transmitters and by letting half-duplex nodes operate according to the aforementioned dominant state

Towards D2D-Enhanced Heterogeneous Networks

In this paper, we examine upcoming 5G networks where the support of device-to-device (D2D) communication is expected to be a key asset for operators and users alike. Firstly, we argue the need to functionally integrate D2D and infrastructure-to-device (I2D) modes. Next, we address practical issues such as integrated resource scheduling of D2D communication within heterogeneous networks, proposing an extension of the proportional fairness algorithm, which we call multi-modal proportional fairness (MMPF). We evaluate the impact of D2D in a two-tier scenario combining macro- and micro- coverage, finding that, although I2D retains a clear edge for general-purpose downloading, D2D is an appealing solution for localized transfers as well as for viral content

Optimal Content Downloading in Vehicular Networks

We consider a system where users aboard communication-enabled vehicles are interested in downloading different contents from Internet-based servers. This scenario captures many of the infotainment services that vehicular communication is envisioned to enable, including news reporting, navigation maps and software updating, or multimedia file downloading. In this paper, we outline the performance limits of such a vehicular content downloading system by modelling the downloading process as an optimization problem, and maximizing the overall system throughput. Our approach allows us to investigate the impact of different factors, such as the roadside infrastructure deployment, the vehicle-to-vehicle relaying, and the penetration rate of the communication technology, even in presence of large instances of the problem. Results highlight the existence of two operational regimes at different penetration rates and the importance of an efficient, yet 2-hop constrained, vehicle-to-vehicle relaying

Performance of mMIMO FD Relay Networks with Limited Relay State Knowledge

Massive MIMO (mMIMO) is a key technology for improving propagation conditions and extending geographical coverage of wireless communications. We here address a mMIMO full-duplex relay network for machine-type-communications where channel state information availability at the transmitter is impractical. In this scenario, we argue that high end-to-end data rates can be achieved even if no precoding is performed at the transmitting nodes. We first formulate an optimization problem aiming at maximizing the achievable rate, considering the source transmit power to depend on the transmit power distribution at the relay node. We then solve this problem by letting the number of antennas grow large, and derive closed-form expressions for the transmit power at the source and relay, as well as for the system data rate. Our results, show that the rate obtained when no precoding is implemented at the relay, or at any of the transmitters, closely matches that of SVD precoding under the optimum receiver, and still achieves very high values in the case of the ZF and the MMSE receiver

Persistent Localized Broadcasting in VANETs

We present a communication protocol, called LINGER, for persistent dissemination of delay-tolerant information to vehicular users, within a geographical area of interest. The goal of LINGER is to dispatch and confine information in localized areas of a mobile network with minimal protocol overhead and without requiring knowledge of the vehicles' routes or destinations. LINGER does not require roadside infrastructure support: it selects mobile nodes in a distributed, cooperative way and lets them act as "information bearers", providing uninterrupted information availability within a desired region. We analyze the performance of our dissemination mechanism through extensive simulations, in complex vehicular scenarios with realistic node mobility. The results demonstrate that LINGER represents a viable, appealing alternative to infrastructure-based solutions, as it can successfully drive the information toward a region of interest from a far away source and keep it local with negligible overhead. We show the effectiveness of such an approach in the support of localized broadcasting, in terms of both percentage of informed vehicles and information delivery delay, and we compare its performance to that of a dedicated, state-of-the-art protoco

A Holistic View of ITS-Enhanced Charging Markets

We consider a network of electric vehicles (EVs) and its components: vehicles, charging stations, and coalitions of stations. For such a setting, we propose a model in which individual stations, coalitions of stations, and vehicles interact in a market revolving around the energy for battery recharge. We start by separately studying 1) how autonomously operated charging stations form coalitions; 2) the price policy enacted by such coalitions; and 3) how vehicles select the charging station to use, working toward a time/price tradeoff. Our main goal is to investigate how equilibrium in such a market can be reached. We also address the issue of computational complexity, showing that, through our model, equilibria can be found in polynomial time. We evaluate our model in a realistic scenario, focusing on its ability to capture the advantages of the availability of an intelligent transportation system supporting the EV drivers. The model also mimics the anticompetitive behavior that charging stations are likely to follow, and it highlights the effect of possible countermeasures to such a behavior