523 research outputs found
Spatially Distributed Molecular Communications: An Asynchronous Stochastic Model
No full textThis letter studies large-scale molecular communication systems by using point processes theory. A swarm of point transmitters randomly placed in a bounded space are considered in conjunction with a single fully absorbing receiver. The transmitters' positions are modeled by a spatial point process, but the global clock assumption, adopted by prior works, is here removed. More precisely, the emission times for each point transmitter are considered as random and are modeled by a non-stationary time-domain point process. We show that, if the intensity function is the same for all time point processes (thus taking the meaning of a distributed input), the average number of received molecules per time unit (receiving rate) can be computed through a convolution: the collective response to a one-molecule emission can be properly interpreted as the impulse response. This models unifies all the widely known transmitter models (exact concentration, Poisson concentration, and timing transmitter), which result as special cases. Analytical expressions for the receiving rate are provided and validated by Monte-Carlo simulations
Partial Equalization for MC–CDMA Systems in Non-Ideally Estimated Correlated Fading
No full textMulticarrier code-division multiple access (MC–CDMA) can support high data rates in next-generation multiuser wireless communication systems. Partial equalization (PE) is a low-complexity technique for combining the signals of subcarriers to improve the achievable performance of MC–CDMA systems in terms of their bit error probability (BEP) and bit error outage (BEO) in comparison with maximal ratio combining, orthogonality restoring combining, and equal-gain combining techniques. We analyze the performance of the multiuser MC–CDMA downlink and derive the optimal PE parameter expression, which minimizes the BEP. Realistic imperfect channel estimation and frequency-domain (FD) block-fading channels are considered. More explicitly, the analytical expression of the optimum PE parameter is derived as a function of the number of subcarriers, number of active users (i.e., the system load), mean signal-to-noise ratio (SNR), and variance of the channel-estimation errors for the aforementioned FD block-fading channel. We show that the choice of the optimal PE technique significantly increases the achievable system load for the given target BEP and BEO
Localization With Joint Diffusion-Based Molecular Communication and Sensing Systems: Fundamental Limits and Tradeoffs
No full textThis paper introduces and examines a novel joint communication and sensing system based on molecular diffusion. Using a configuration of at least four fully absorbing spherical receivers, the proposed system achieves precise 3D-localization of a pointwise transmitter by counting the same molecules emitted for communication purposes. We develop an analytical framework to explore the fundamental limits of communication and localization within this context. Exact closed-form expressions for the bit error probability and the Cramér-Rao bound on localization error are derived, considering both Poisson concentration and timing transmitter models, with and without accounting for molecule degradation. For the first time, theoretical trade-offs between communication and localization performance are established, taking inter-symbol interference and molecule degradation into account. In scenarios without molecule degradation, inter-symbol interference detrimentally affects communication but enhances localization. Conversely, the introduction of degradation improves communication performance but partially compromises localization effectiveness. These trade-offs are navigated by adjusting number of transmitted symbols or degradation rate, respectively. Furthermore, we compare communication and localization ranges, alongside the associated costs measured in terms of average emitted molecules required to meet performance requirements
Ginibre sampling and signal reconstruction
No full textThe spatial distribution of sensing nodes plays a crucial role in signal sampling and reconstruction via wireless sensor networks. Although homogeneous Poisson point process (PPP) model is widely adopted for its analytical tractability, it cannot be considered a proper model for all experiencing nodes. The Ginibre point process (GPP) is a class of determinantal point processes that has been recently proposed for wireless networks with repulsiveness between nodes. A modified GPP can be considered an intermediate class between the PPP (fully random) and the GPP (relatively regular) that can be derived as limiting cases. In this paper we analyze sampling and reconstruction of finite-energy signals in Rd when samples are gathered in space according to a determinantal point process whose second order product density function generalizes to Rd that of a modified GPP in R2. We derive closed form expressions for sampled signal energy spectral density (ESD) and for signal reconstruction mean square error (MSE). Results known in the literature are shown to be sub-cases of the proposed framework. The proposed analysis is also able to answer to the fundamental question: does the higher regularity of GPP also imply an higher signal reconstruction accuracy, according to the intuition? Theoretical results are illustrated through a simple case study
Inhomogeneous Poisson Sampling of Finite-Energy Signals with Uncertainties in Rd
No full textSpatiotemporal signal reconstruction from samples randomly gathered in a multidimensional space with uncertainty is a crucial problem for a variety of applications. Such a problem generalizes the reconstruction of a deterministic signal and that of a stationary random process in one dimension, which was first addressed by Whittaker, Kotelnikov, and Shannon. In this work we analyze multidimensional random sampling with uncertainties jointly accounting for signal properties (signal spectrum and spatial correlation) and for sampling properties (inhomogeneous sample spatial distribution, sample availability, and non-ideal knowledge of sample positions). The reconstructed signal spectrum and the signal reconstruction accuracy are derived as a function of signal and sampling properties. It is shown that some of these properties expand the signal spectrum while others modify the spectrum without expansion. The signal reconstruction accuracy is first determined in a general case and then specialized for cases of practical interests. The optimal interpolator function is derived and asymptotic results are obtained to show the impact of sampling non-idealities. The analysis is corroborated by verifying that previously known results can be obtained as special cases of the general one and by means of a case study accounting for various settings of signal and sample properties
Throughput versus fairness tradeoff analysis
No full textOptimal resource allocation is an outstanding issue in wireless communication systems. In this work we focus on the ever challenging optimization of the tradeoff between throughput and fairness. Specifically, we propose a novel framework to analytically derive the maximum average throughput versus fairness under the assumptions that the throughput of each user i) increases if more resources are allocated to him and ii) depends on how many resources and not which resources are allocated. We achieve a general formulation of the tradeoff optimization problem and we also derive and validate a closed form solution in those scenarios where throughput linearly depends on resources, which cover several realistic cases. Besides these valuable results, the framework also lays solid basis toward a more general solution
On the Effect of Combined Equalization for MC-CDMA Systems in Correlated Fading Channels
No full textEqualization techniques are considered in multi carrier-code division multiple access (MC-CDMA) systems to efficiently combine subcarriers contribution and improve the performance. In this paper we analytically investigate a combined equalization technique which consists in performing both pre- equalization at the transmitter and post-equalization at the receiver, by exploiting channel knowledge at both sides. To keep the framework as much general as possible, a parametric partial combining (PC) technique is considered. The analytical framework proposed allows the derivation of the bit error probability in correlated block fading channels and its dependence on the number of subcarriers, the number of active users, the mean signal-to-noise ratio (SNR) averaged over small-scale fading and, above all, the PC parameters, thus allowing the derivation of optimal equalization technique depending on fading levels
On the exploitation of OFDMA properties for an efficient alert message flooding in VANETs
No full textVehicular ad hoc networks (VANETs) drive new challenging research issues at different layers of the protocol pillar, from physical to application. Focusing on the medium access layer, one of the most promising and not yet fully explored option is the adoption of orthogonal frequency division multiple access (OFDMA). Besides guaranteeing high spectral efficiency and effective resource allocation, it relies at the physical layer on orthogonal frequency division multiplexing, which allows repetitions of the same signals to be opportunistically combined at the receiver even if they are not perfectly synchronized. Exploiting this property, here we suggest and discuss the use of OFDMA for alert message flooding in VANETs to increase reliability and resource usage efficiency. The achievable benefit and the potential drawback (in terms of high delivery delay) are here assessed through a simple yet realistic model that allows to compare, in highway scenarios, OFDMA with carrier sensing multiple access/collision avoidance, currently adopted by IEEE 802.11p for distributed communications in high mobility scenarios
Analysis of Inhomogeneous Random Sampling
No full textProcess estimation from randomly deployed samples in a multidimensional space with sample position
errors is essential for various applications. This analyzes random sampling in R^d jointly accounting for
finite-energy process properties (process spectrum and spatial correlation) and for sampling properties
(inhomogeneous sample spatial distribution, sample availability, and non-ideal knowledge of sample
positions). Based on process and sampling properties, the estimated process spectrum and the estimation
accuracy are derived. Some properties expand the process spectrum while others modify the process
without expansion. The process estimation accuracy is determined in a general case. The analysis is
corroborated by verifying that previously known results can be obtained as special cases of the general
one and by means of a case study accounting for various process and sample properties
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