704 research outputs found
Performance analysis and optimization of STAR-RIS-aided cell-free massive MIMO systems relying on imperfect hardware
Full text linkSimultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) systems are investigated under spatially correlated fading channels using realistic imperfect hardware. Specifically, the transceiver distortions, time-varying phase noise, and RIS phase shift errors are considered. Upon considering imperfect hardware and pilot contamination, we derive a linear minimum mean-square error (MMSE) criterion-based cascaded channel estimator. Moreover, a closed-form expression of the downlink ergodic spectral efficiency (SE) is derived based on maximum ratio (MR) based transmit precoding and channel statistics, where both a finite number of access points (APs) and STAR-RIS elements as well as imperfect hardware are considered. Furthermore, by exploiting the ergodic signal-to-interference-plus-noise ratios (SINRs) among user equipment (UE), a max-min fairness problem is formulated for the joint optimization of the passive transmitting and reflecting beamforming (BF) at the STAR-RIS as well as of the power control coefficients. An alternating optimization (AO) algorithm is proposed for solving the resultant problems, where iterative adaptive particle swarm optimization (APSO) and bisection methods are proposed for circumventing the non-convexity of the RIS passive BF and the quasi-concave power control sub-problems, respectively. Our simulation results illustrate that the STAR-RIS-aided CF-mMIMO system attains higher SE than its RIS-aided counterpart. The performance of different hardware parameters is also evaluated. Additionally, it is demonstrated that the SE of the worst UE can be significantly improved by exploiting the proposed AO-based algorithm compared to conventional solutions associated with random passive BF and equal-power scenarios.<br/
Cell-free massive MIMO surveillance of multiple untrusted communication links
No full textA cell-free massive multiple-input multiple-output (CF-mMIMO) system is considered for enhancing the monitoring performance of wireless surveillance, where a large number of distributed multi-antenna aided legitimate monitoring nodes (MNs) proactively monitor multiple distributed untrusted com munication links. We consider two types of MNs whose task is to either observe the untrusted transmitters or jam the untrusted receivers. We first analyze the performance of CF mMIMO surveillance relying on both maximum ratio (MR) and partial zero-forcing (PZF) combining schemes and derive closed form expressions for the monitoring success probability (MSP) of the MNs. We then propose a joint optimization technique that designs the MN mode assignment, power control, and MN weighting coefficient control to enhance the MSP based on the long-term statistical channel state information knowledge. This challenging problem is effectively transformed into tractable forms and efficient algorithms are proposed for solving them. Numerical results show that our proposed CF-mMIMO surveil lance system considerably improves the monitoring performance with respect to a full-duplex co-located massive MIMO proactive monitoring system. More particularly, when the untrusted pairs are distributed over a wide area and use the MR combining, the proposed solution provides nearly a thirty-fold improvement in the minimum MSP over the co-located massive MIMO baseline, and forty-fold improvement, when the PZF combining is employed
Reconfigurable massive MIMO: harnessing the power of the electromagnetic domain for enhanced information transfer
No full textThe capacity of commercial massive multiple-input multiple-output (mMIMO) systems is constrained by the limited array aperture at the base station, and cannot meet the everincreasing traffic demands of wireless networks. Given the array aperture, holographic MIMO with infinitesimal antenna spacing can maximize the capacity, but is physically unrealizable. As a promising alternative, reconfigurable mMIMO is proposed to harness the unexploited power of the electromagnetic (EM) domain for enhanced information transfer. Specifically, the reconfigurable pixel antenna technology provides each antenna with an adjustable EM radiation (EMR) pattern, introducing extra degrees of freedom for information transfer in the EM domain. In this article, we present the concept and benefits of availing the EMR domain for mMIMO transmission. Moreover, we propose a viable architecture for reconfigurable mMIMO systems, and the associated system model and downlink precoding are also discussed. In particular, a three-level precoding scheme is proposed, and simulation results verify its considerable spectral and energy efficiency advantages compared to traditional mMIMO systems. Finally, we further discuss the challenges, insights, and prospects of deploying reconfigurable mMIMO, along with the associated hardware, algorithms, and fundamental theory
RIS-assisted cell-free massive MIMO relying on reflection pattern modulation
No full textWe propose reflection pattern modulation-aided reconfigurable intelligent surface (RPM-RIS)-assisted cell-free massive multiple-input-multiple-output (CF-mMIMO) schemes for green uplink transmission. In our RPM-RIS-assisted CF-mMIMO system, extra information is conveyed by the indices of the active RIS blocks, exploiting the joint benefits of both RIS-assisted CF-mMIMO transmission and RPM. Since only part of the RIS blocks are active, our proposed architecture strikes a flexible energy vs. spectral efficiency (SE) trade-off. We commence with introducing the system model by considering spatially correlated channels. Moreover, we conceive a channel estimation scheme subject to the linear minimum mean-square error (MMSE) constraint, yielding sufficient information for the subsequent signal processing steps. Then, upon exploiting a so-called large-scale fading decoding (LSFD) scheme, the uplink signal-to-interference-and-noise ratio (SINR) is derived based on the RIS ON/OFF statistics, where both maximum ratio (MR) and local minimum mean-square error (L-MMSE) combiners are considered. By invoking the MR combiner, the closed-form expression of the uplink SE is formulated based only on the channel statistics. Furthermore, we derive the total energy efficiency (EE) of our proposed RPM-RIS-assisted CF-mMIMO system. Additionally, we propose a chaotic sequence-based adaptive particle swarm optimization (CSA-PSO) algorithm to maximize the total EE by designing the RIS phase shifts. Specifically, the initial particle diversity is promoted by invoking chaotic sequences, and an adaptive time-varying inertia weight is developed to improve its particle search performance. Furthermore, the particle mutation and reset steps are appropriately selected to enable the algorithm to escape from local optima. Finally, our simulation results demonstrate that the proposed RPM-RIS-assisted CF-mMIMO architecture strikes an attractive SE vs. EE trade-off, while the CSA-PSO algorithm is capable of attaining a significant EE performance gain compared to conventional solutions
Prefazione [a: Michail Kuzmin, Le stagioni dell'amore, Bari, Stilo, 2020, 172 pp.]
No full text"Kuranty ljubvi" (Le stagioni dell'amore) è un piccolo, ma poeticamente significativo, contributo alla produzione letteraria del Simbolismo russo nel segno della sintesi delle arti. Michail Kuzmin, uno dei più importanti scrittori di quell'epoca, è l'autore del ciclo poetico-musicale e delle partiture."Kuranty ljubvi" (The seasons of love) is a small but poetically significant contribution to the literary production of Russian Symbolism in the context of the synthesis of the arts. Michail Kuzmin, one of the most important writers of that era, is the author of the poetic-musical cycle and of the scores
Dei delitti e delle pene nella traduzione di Michail M. Scerbatov
Full text linkAfter more than two centuries, this work presents the Russian version of “Dei delitti e delle pene” by Cesare Beccaria, translated by Prince Michail M. Šcerbatov. The edition, conducted on the autographed manuscript, is presented with the original Italian text. In the introductory study, the author traces the fundamental stages of the diffusion of Beccaria’s work in Russia, focusing in particular on the figure of Michail M. Isaev, scholar and translator of the masterpiece by Beccaria, who was the first to re-propose the modern organisation of the “Fifth” edition. The author gives an account of the version proposed by Šcerbatov, investigating its textual genesis and evaluating some aspects of the language used by the translator - first of all the lexicon used for the rendering of philosophical-political and legal terms
Characterisation and Modelling of Indoor and Short-Range MIMO Communications
Full text linkOver the last decade, we have witnessed the rapid evolution of Multiple-Input Multiple-Output
(MIMO) systems which promise to break the frontiers of conventional architectures and deliver
high throughput by employing more than one element at the transmitter (Tx) and receiver (Rx)
in order to exploit the spatial domain. This is achieved by transmitting simultaneous data
streams from different elements which impinge on the Rx with ideally unique spatial signatures
as a result of the propagation paths’ interactions with the surrounding environment. This thesis
is oriented to the statistical characterisation and modelling of MIMO systems and particularly
of indoor and short-range channels which lend themselves a plethora of modern applications,
such as wireless local networks (WLANs), peer-to-peer and vehicular communications.
The contributions of the thesis are detailed below. Firstly, an indoor channel model is proposed
which decorrelates the full spatial correlation matrix of a 5.2 GHzmeasuredMIMO channel and
thereafter assigns the Nakagami-m distribution on the resulting uncorrelated eigenmodes. The
choice of the flexible Nakagami-m density was found to better fit the measured data compared
to the commonly used Rayleigh and Ricean distributions. In fact, the proposed scheme captures
the spatial variations of the measured channel reasonably well and systematically outperforms
two known analytical models in terms of information theory and link-level performance.
The second contribution introduces an array processing scheme, namely the three-dimensional
(3D) frequency domain Space Alternating Generalised Expectation Maximisation (FD-SAGE)
algorithm for jointly extracting the dominant paths’ parameters. The scheme exhibits a satisfactory
robustness in a synthetic environment even for closely separated sources and is applicable
to any array geometry as long as its manifold is known. The algorithm is further applied to the
same set of raw data so that different global spatial parameters of interest are determined; these
are the multipath clustering, azimuth spreads and inter-dependency of the spatial domains.
The third contribution covers the case of short-range communications which have nowadays
emerged as a hot topic in the area of wireless networks. The main focus is on dual-branch
MIMO Ricean systems for which a design methodology to achieve maximum capacities in the
presence of Line-of-Sight (LoS) components is proposed. Moreover, a statistical eigenanalysis
of these configurations is performed and novel closed-formulae for the marginal eigenvalue
and condition number statistics are derived. These formulae are further used to develop an
adaptive detector (AD) whose aim is to reduce the feasibility cost and complexity of Maximum
Likelihood (ML)-based MIMO receivers.
Finally, a tractable novel upper bound on the ergodic capacity of the above mentioned MIMO
systems is presented which relies on a fundamental power constraint. The bound is sufficiently
tight and applicable for arbitrary rank of the mean channel matrix, Signal-to-Noise ratio (SNR)
and takes the effects of spatial correlation at both ends into account. More importantly, it
includes previously reported capacity bounds as special cases
I/Q imbalance in two-way AF relaying
No full textWe analyze the performance of dual-hop two-way amplify-and-forward relaying in the presence of in-phase and quadrature-phase imbalance (IQI) at the relay node. In particular, two power allocation schemes, namely, fixed power allocation and instantaneous power allocation, are proposed to improve the system reliability and robustness against IQI under a total transmit power constraint. For each proposed scheme, the outage probability is investigated over independent, non-identically distributed Nakagami- m fading channels, and exact closed-form expressions and bounds are derived. Our theoretical analysis indicates that, without IQI compensation, IQI can create fundamental performance limits on two-way relaying. However, these limits can be avoided by performing IQI compensation at source nodes. Compared with the equal power allocation scheme, our numerical results show that the two proposed power allocation schemes can significantly improve the outage performance, thus reducing the IQI effects, particularly when the total power budget is large
Low-SNR analysis of MIMO Weibull fading channels
No full textThe capacity performance of multiple-input multiple-output (MIMO) systems in Weibull fading channels has not been properly addressed in the literature. In this paper, we consider three MIMO architectures, namely spatial-multiplexing (SM) MIMO systems with optimal and minimum mean square error (MMSE) receivers as well as orthogonal space-time block-codes (OSTBC) MIMO systems, that operate over Weibull fading channels. Since the capacity analysis at arbitrary Signal-to-Noise ratios (SNRs) is intractable, we focus on the low-SNR regime which is characterized by the minimum energy per information bit to reliably convey any positive rate and the wideband slope. For these two metrics, new closed-form expressions are derived which enable us to perform a detailed comparative study of the considered configurations and assess MIMO capacity in Weibull fading channels
Bayesian approach to channel estimation for AF MIMO relaying systems
No full textIn this paper, we investigate the problem of channel estimation in amplify-and-forward multiple-input multiple-output relaying systems operating over random wireless channels. Using the Bayesian framework, novel linear minimum mean square error and expectation-maximization based maximum a posteriori channel estimation algorithms are developed, that provide the destination with full knowledge of all channel parameters involved in the transmission. Moreover, new, explicit expressions for the Bayesian Cramer-Rao bound are deduced for predicting and evaluating the channel estimation accuracy. Our simulation results demo nstrate that the incorporation of prior knowledge into the channel estimation algorithm offers significantly improved performance, especially in the low signal-to-noise ratio regime
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