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Stefano Buzzi

Publications and source records attributed to Stefano Buzzi.

At least 73 records · Page 4Linked to original sources

The Ultimate Weapon for Ultra-Broadband 6G: Digital Beamforming and Doubly Massive mmWave MIMO

The use of millimeter waves for wireless communications is one of the main technological innovations of 5G systems with respect to previous generations of cellular systems. Their consideration, however, has been up to now mainly restricted to the case in which analog or, at most, hybrid analog-digital beamforming structures were used, thus posing a limitation on the multiplexing capabilities and peak data rates that could be theoretically achieved at these frequencies. Recent progress in the field of electronics, however, has made the energy consumption of digital beamforming structures at least on par with that of analog beamforming, thus redeeming them from the ghetto they had been placed in over the last year. Digital beamforming, coupled with the use of large antenna arrays at both sides of the communication link, promises thus to be one of the secret weapons of future 6G networks, capable of unleashing unprecedented values of spectral and energy efficiency for ultra-broadband connectivity.

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Scoring the Terabit/s Goal:Broadband Connectivity in 6G

This paper explores the road to vastly improving the broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, with peak data rates up to 1 Tbps. Several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be mainly used for pushing the peak rates of point-to-point links. Finally, at the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latency, higher reliability, and reduced complexity.

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Pilot Assignment in Cell-Free Massive MIMO based on the Hungarian Algorithm

This letter focuses on the problem of pilot assignment in cell-free massive MIMO systems. Exploiting the well-known Hungarian algorithms, two procedures are proposed, one maximizing the system throughput, and the other one maximizing the fairness across users. The algorithms operate based on the knowledge of large-scale fading coefficients as a proxy for the distances between users in the system and take into account both the uplink and downlink performance. Numerical results show that the proposed pilot assignment algorithms are effective and outperform the many competing alternatives available in the literature.

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White Paper on Broadband Connectivity in 6G

This white paper explores the road to implementing broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, from extreme capacity with peak data rates up to 1 Tbps, to raising the typical data rates by orders-of-magnitude, to support broadband connectivity at railway speeds up to 1000 km/h. To achieve these goals, not only the terrestrial networks will be evolved but they will also be integrated with satellite networks, all facilitating autonomous systems and various interconnected structures. We believe that several categories of enablers at the infrastructure, spectrum, and protocol/ algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric and scalable cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be used for pushing the peak rates of point-to-point links. The latter path will lead to THz communications complemented by visible light communications in specific scenarios. At the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latencies, higher reliability, and reduced complexity. Different options will be needed to optimally support different use cases. The resource efficiency can be further improved by using various combinations of full-duplex radios, interference management based on rate-splitting, machine-learning-based optimization, coded caching, and broadcasting.

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Resource Allocation in Wireless Networks Assisted by Reconfigurable Intelligent Surfaces

Reconfigurable Intelligent Surfaces (RISs) are recently attracting a wide interest due to their capability of tuning wireless propagation environments in order to increase the system performance of wireless networks. In this paper, a multiuser single-cell wireless network assisted by a RIS is studied. First of all, for the special case of a single-user system, three possible approaches are shown in order to optimize the Signal-to-Noise Ratio with respect to the beamformer used at the base station and to the RIS phase shifts. Then, for a multiuser system, assuming channel-matched beamforming, the geometric mean of the downlink Signal-to-Interference plus Noise Ratios across users is maximized with respect to the base stations transmit powers and RIS phase shifts configurations. Numerical results show that the proposed procedure are effective and greatly improve the performance of the considered systems.

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Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis

This paper considers the uplink of a massive MIMO communication system using 5G New Radio-compliant multiple access, which is to co-exist with a radar system using the same frequency band. A system model taking into account the reverberation (clutter) produced by the radar system onto the massive MIMO receiver is proposed. In this scenario, several receivers for uplink channel estimation and data detection are proposed, ranging from the simple channel-matched beamformer to the zero-forcing and linear minimum mean square error receivers for clutter disturbance rejection, under the two opposite situations of perfectly known ad completely unknown clutter covariance. A theoretical analysis is also given, deriving a lower bound on the achievable uplink spectral efficiency and the mutual information between the input Gaussian-encoded symbols and the observables available at the communication receiver of the cellular massive MIMO system: regarding the latter, in particular, we show that, in the large antenna number regime, the radar clutter effects at the base station is suppressed and single-user capacity is restored. Numerical results, illustrating the performance of the proposed detection schemes, confirm the findings of the theoretical analysis, and permit quantifying the system robustness to clutter effect for increasing number of antennas at the base station.

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Transmit Power Allocation for Joint Communication and Sensing through Massive MIMO Arrays

The paper considers a scenario where a base station (BS), equipped with a large-scale antenna array, execute, using the same frequency range, both communication with mobile users and radar surveillance of the surrounding environment, relying on the ability of the massive MIMO array to synthesize multiple narrow beams. Based on an OFDM signaling format for both communication and surveillance tasks, a lower bound to the system achievable downlink rate is provided, along with a GLRT detection rule that does not require any knowledge about the target parameters. Then, a power allocation strategy is proposed, aimed at maximizing the fairness across the mobile users, while guaranteeing a minimum signal to interference ratio threshold value for the radar system. Numerical results show that the system performs effectively, and that the power control procedure helps in improving the system fairness.

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Analysis of UAV Communications in Cell-Free Massive MIMO systems

We study support for unmanned aerial vehicle (UAV) communications through a cell-free massive MIMO architecture, wherein a large number of access points (APs) is deployed in place of large co-located massive MIMO arrays. We consider also a variation of the pure cell-free architecture by applying a user-centric association approach, where each user is served only from a subset of APs in the network. Under the general assumption that the propagation channel between the mobile stations, either UAVs or ground users (GUEs), and the APs follows a Ricean distribution, we derive closed-form spectral efficiency lower bounds for uplink and downlink with linear minimum mean square error channel estimation. We consider several power allocation and user scheduling strategies for such a system, and, among these, also minimum-rate maximizing power allocation strategies to improve the system fairness. Our numerical results reveal that cell-free massive MIMO architecture and its low-complexity user-centric alternative may provide better performance than a traditional multi-cell massive MIMO network deployment.

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Using Massive MIMO Arrays for Joint Communication and Sensing

One of the trends that is gaining more and more importance in the field of beyond-5G and 6G wireless communication systems is the investigation on systems that jointly perform communication and sensing of the environment. This paper proposes to use a base station (BS), that we call \textit{radar-BS}, equipped with a large-scale antenna array to execute, using the same frequency range, communication with mobile users and sensing/surveillance of the surrounding environment through radar scanning. The massive antenna array can indeed both operate as a MIMO radar with co-located antennas -- transmitting radar signals pointing at positive elevation angles -- and perform signal-space beamforming to communicate with users mainly based on the ground. Our results show that using a massive MIMO radar-BS the communication and the radar system can coexist with little mutual interference.

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Uplink power control in cell-free massive MIMO via deep learning

This paper focuses on the use of a deep learning approach to perform sum-rate-max and max-min power allocation in the uplink of a cell-free massive MIMO network. In particular, we train a deep neural network in order to learn the mapping between a set of input data and the optimal solution of the power allocation strategy. Numerical results show that the presence of the pilot contamination in the cell-free massive MIMO system does not significantly affect the learning capabilities of the neural network, that gives near-optimal performance. Conversely, with the introduction of the shadowing effect in the system the performance obtained with the deep learning approach gets significantly degraded with respect to the optimal one.

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Enabling Ultra Reliable Wireless Communications for Factory Automation with Distributed MIMO

Factory automation is one of the most challenging use cases for 5G-and-beyond mobile networks due to strict latency, availability and reliability constraints. In this work, an indoor factory scenario is considered, and distributed multiple-input multiple-output (MIMO) schemes are investigated in order to enable reliable communication to the actuators (ACs) active in the factory. Different levels of coordination among the access points serving the ACs and several beamforming schemes are considered and analyzed. To enforce system reliability, a max-min power allocation (MPA) algorithm is proposed, aimed at improving the signal to interference plus noise ratio (SINR) of the ACs with the worst channel conditions. Extensive system simulations are performed in a realistic scenario, which includes a new path-loss model based on recent measurements in factory scenarios, and, also, the presence of non-Gaussian impulsive noise. Numerical results show that distributed MIMO schemes with zero-forcing (ZF) beamforming and MPA have the potential of providing SINR gains in the order of tens of dB with respect to a centralized MIMO deployment, as well as that the impulsive noise can strongly degrade the system performance and thus requires specific detection and mitigation techniques.

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Subspace Tracking and Least Squares Approaches to Channel Estimation in Millimeter Wave Multiuser MIMO

The problem of MIMO channel estimation at millimeter wave frequencies, both in a single-user and in a multi-user setting, is tackled in this paper. Using a subspace approach, we develop a protocol enabling the estimation of the right (resp. left) singular vectors at the transmitter (resp. receiver) side; then, we adapt the projection approximation subspace tracking with deflation and the orthogonal Oja algorithms to our framework and obtain two channel estimation algorithms. We also present an alternative algorithm based on the least squares approach. The hybrid analog/digital nature of the beamformer is also explicitly taken into account at the algorithm design stage. In order to limit the system complexity, a fixed analog beamformer is used at both sides of the communication links. The obtained numerical results, showing the accuracy in the estimation of the channel matrix dominant singular vectors, the system achievable spectral efficiency, and the system bit-error-rate, prove that the proposed algorithms are effective, and that they compare favorably, in terms of the performance-complexity trade-off, with respect to several competing alternatives.

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Energy-Efficient Power Control in Cell-Free and User-Centric Massive MIMO at Millimeter Wave

In a cell-free massive MIMO architecture a very large number of distributed access points simultaneously and jointly serves a much smaller number of mobile stations; a variant of the cell-free technique is the user-centric approach, wherein each access point just serves a reduced set of mobile stations. This paper introduces and analyzes the cell-free and user-centric architectures at millimeter wave frequencies, considering a training-based channel estimation phase, and the downlink and uplink data transmission phases. First of all, a multiuser clustered millimeter wave channel model is introduced in order to account for the correlation among the channels of nearby users; second, an uplink multiuser channel estimation scheme is described along with low-complexity hybrid analog/digital beamforming architectures. Third, the non-convex problem of power allocation for downlink global energy efficiency maximization is addressed. Interestingly, in the proposed schemes no channel estimation is needed at the mobile stations, and the beamforming schemes used at the mobile stations are channel-independent and have a very simple structure. Numerical results show the benefits granted by the power control procedure, that the considered architectures are effective, and permit assessing the loss incurred by the use of the hybrid beamformers and by the channel estimation errors.

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Cell-free Massive MIMO for UAV Communications

We study support for unmanned aerial vehicle (UAV) communications through a cell-free massive MIMO architecture. Under the general assumption that the propagation channel between the mobile stations, either UAVs or ground users, and the access points follows a Ricean distribution, we derive closed form spectral efficiency lower bounds for uplink and downlink with linear minimum mean square error (LMMSE) channel estimation. We also propose power allocation and user scheduling strategies for such a system. Our numerical results reveal that a cell-free massive MIMO architecture may provide better performance than a traditional multicell massive MIMO network deployment.

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MIMO-UFMC Transceiver Schemes for Millimeter Wave Wireless Communications

The UFMC modulation is among the most considered solutions for the realization of beyond-OFDM air interfaces for future wireless networks. This paper focuses on the design and analysis of an UFMC transceiver equipped with multiple antennas and operating at millimeter wave carrier frequencies. The paper provides the full mathematical model of a MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission, and for the case of multiple-packet continuous transmission. In the latter situation, the paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, the several considered detection structures and transmission schemes are compared in terms of bit-error-rate, root-mean-square-error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear MMSE data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10 - 13 $\%$. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance.

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Massive MIMO in Sub-6 GHz and mmWave: Physical, Practical, and Use-Case Differences

The use of base stations (BSs) and access points (APs) with a large number of antennas, called Massive MIMO (multiple-input multiple-output), is a key technology for increasing the capacity of 5G networks and beyond. While originally conceived for conventional sub-6GHz frequencies, Massive MIMO (mMIMO) is ideal also for frequency bands in the range 30-300 GHz, known as millimeter wave (mmWave). Despite conceptual similarities, the way in which mMIMO can be exploited in these bands is radically different, due to their specific propagation behaviors and hardware characteristics. This paper reviews these differences and their implications, while dispelling common misunderstandings. Building on this foundation, we suggest appropriate signal processing schemes and use cases to efficiently exploit mMIMO in both frequency bands.

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Co-existence Between a Radar System and a Massive MIMO Wireless Cellular System

In this paper we consider the uplink of a massive MIMO communication system using 5G New Radio-compliant multiple access, which is to co-exist with a radar system using the same frequency band. We propose a system model taking into account the reverberation (clutter) produced by the radar system at the massive MIMO receiver. Then, we propose several linear receivers for uplink data-detection, ranging by the simple channel-matched beamformer to the zero-forcing and linear minimum mean square error receivers for clutter disturbance rejection. Our results show that the clutter may have a strong effect on the performance of the cellular communication system, but the use of large-scale antenna arrays at the base station is key to provide increased robustness against it, at least as far as data-detection is concerned.

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Energy-Efficient Downlink Power Control in mmWave Cell-Free and User-Centric Massive MIMO

This paper considers cell-free and user-centric approaches for coverage improvement in wireless cellular systems operating at millimeter wave frequencies, and proposes downlink power control algorithms aimed at maximizing the global energy efficiency. To tackle the non-convexity of the problems, an interaction between sequential and alternating optimization is considered. The use of hybrid analog/digital beamformers is also taken into account. The numerical results show the benefits obtained from the power control algorithm, as well as that the user-centric approach generally outperforms the cell-free one.

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