arXiv subjects

Paolo Baracca

Publications and source records attributed to Paolo Baracca.

At least 19 recordsLinked to original sources

arXiv2025

Flexible and High-Performance Radio Access Networks for upcoming Sixth-Generation (6G) Systems

The collaborative research project 6G-ANNA develops concepts for the 6G radio access network (RAN) architecture and technology components. Previous RAN generations have become inherently more complex and reach their limits in handling foreseen future traffic demands with their diverse characteristics in an efficient manner, e.g., for the use-case of mobile eXtended Reality (XR) on a massive scale. One main objective of 6G is to regain both operational and energy efficiency, i.e., by simplification and automation. To achieve this, in this paper a flexible 6G RAN functional architecture and protocol stack as well as implementation and deployment options are described. We outline how performance is optimized by distributed Multiple Input Multiple Output (MIMO) and distributed Carrier Aggregation (CA), and furthermore, how adaptiveness and scalability is enabled by Cloud RAN and service orchestration. Finally, the proposed zero-trust framework mitigates security risks in the described 6G RAN architecture.

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arXiv2025

CQI-Based Interference Prediction for Link Adaptation in Industrial Sub-networks

We propose a novel interference prediction scheme to improve link adaptation (LA) in densely deployed industrial sub-networks (SNs) with high-reliability and low-latency communication (HRLLC) requirements. The proposed method aims to improve the LA framework by predicting and leveraging the heavy-tailed interference probability density function (pdf). Interference is modeled as a latent vector of available channel quality indicator (CQI), using a vector discrete-time state-space model (vDSSM) at the SN controller, where the CQI is subjected to compression, quantization, and delay-induced errors. To robustly estimate interference power values under these impairments, we employ a low-complexity, outlier-robust, sparse Student-t process regression (SPTPR) method. This is integrated into a modified unscented Kalman filter, which recursively refines predicted interference using CQI, enabling accurate estimation and compensating protocol feedback delays, crucial for accurate LA. Numerical results show that the proposed method achieves over 10x lower complexity compared to a similar non-parametric baseline. It also maintains a BLER below the 90th percentile target of 1e-6 while delivering performance comparable to a state-of-the-art supervised technique using only CQI reports.

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arXiv2024

Dynamic Interference Prediction for In-X 6G Sub-networks

The sixth generation (6G) industrial Sub-networks (SNs) face several challenges in meeting extreme latency and reliability requirements in the order of 0.1-1 ms and 99.999 -to-99.99999 percentile, respectively. Interference management (IM) plays an integral role in addressing these requirements, especially in ultra-dense SN environments with rapidly varying interference induced by channel characteristics, mobility, and resource limitations. In general, IM can be achieved using resource allocation and \textit{accurate} Link adaptation (LA). In this work, we focus on the latter, where we first model interference at SN devices using the spatially consistent 3GPP channel model. Following this, we present a discrete-time dynamic state space model (DSSM) at a SN access point (AP), where interference power values (IPVs) are modeled as latent variables incorporating underlying modeling errors as well as transmission/protocol delays. Necessary approximations are then presented to simplify the DSSM and to efficiently employ the extended Kalman filter (EKF) for interference prediction. Unlike baseline methods, our proposed approach predicts IPVs solely based on the channel quality indicator (CQI) reports available at the SN AP at every transmission time interval (TTI). Numerical results demonstrate that our proposed approach clearly outperforms the conventional baseline. Furthermore, we also show that despite predicting with limited information, our proposed approach consistently achieves a comparable performance w.r.t the off-the-shelf supervised learning based baseline.

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arXiv2024

ConPA: A Contention-free Mechanism with Power Adaptation for Beyond Listen-Before-Talk

In view of the need to find novel means to utilize the unlicensed spectrum to meet the rising latency and reliability requirements of new applications, we propose a novel mechanism that allows devices to transmit anytime that a packet has to be delivered. The proposed mechanism, Contention-free with Power Adaptation (ConPA), aims to bypass the contention periods of current Listen-Before-Talk (LBT) approaches, which are the main source of unreliability in unlicensed technologies like Wi-Fi. To assess the feasibility of ConPA, we provide an analytical method based on Markov chains, which allows deriving relevant performance metrics, including throughput, airtime, and quality of transmissions. Using such a model, we study the performance of ConPA in various scenarios, and compare it to baseline channel access approaches like the Distributed Coordination Function (DCF) and the IEEE 802.11ax Overlapping Basic Service Set (OBSS) Packet Detect (PD)-based Spatial Reuse (SR). Our results prove the effectiveness of ConPA in reusing the space to offer substantial throughput gains with respect to the baselines (up to 76% improvement).

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arXiv2023

Distributed MIMO for 6G sub-Networks in the Unlicensed Spectrum

In this paper, we consider the sixth generation (6G) sub-networks, where hyper reliable low latency communications (HRLLC) requirements are expected to be met. We focus on a scenario where multiple sub-networks are active in the service area and assess the feasibility of using the 6 GHz unlicensed spectrum to operate such deployment, evaluating the impact of listen before talk (LBT). Then, we explore the benefits of using distributed multiple input multiple output (MIMO), where the available antennas in every sub-network are distributed over a number of access points (APs). Specifically, we compare different configurations of distributed MIMO with respect to centralized MIMO, where a single AP with all antennas is located at the center of every sub-network.

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arXiv2022

Jamming Resilient Indoor Factory Deployments: Design and Performance Evaluation

In the framework of 5G-and-beyond Industry 4.0, jamming attacks for denial of service are a rising threat which can severely compromise the system performance. Therefore, in this paper we deal with the problem of jamming detection and mitigation in indoor factory deployments. We design two jamming detectors based on pseudo-random blanking of subcarriers with orthogonal frequency division multiplexing and consider jamming mitigation with frequency hopping and random scheduling of the user equipments. We then evaluate the performance of the system in terms of achievable BLER with ultra-reliable low-latency communications traffic and jamming missed detection probability. Simulations are performed considering a 3rd Generation Partnership Project spatial channel model for the factory floor with a jammer stationed outside the plant trying to disrupt the communication inside the factory. Numerical results show that jamming resiliency increases when using a distributed access point deployment and exploiting channel correlation among antennas for jamming detection, while frequency hopping is helpful in jamming mitigation only for strict BLER requirements.

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arXiv2021

Jamming Detection With Subcarrier Blanking for 5G and Beyond in Industry 4.0 Scenarios

Security attacks at the physical layer, in the form of radio jamming for denial of service, are an increasing threat in the Industry 4.0 scenarios. In this paper, we consider the problem of jamming detection in 5G-and-beyond communication systems and propose a defense mechanism based on pseudo-random blanking of subcarriers with orthogonal frequency division multiplexing (OFDM). We then design a detector by applying the generalized likelihood ratio test (GLRT) on those subcarriers. We finally evaluate the performance of the proposed technique against a smart jammer, which is pursuing one of the following objectives: maximize stealthiness, minimize spectral efficiency (SE) with mobile broadband (MBB) type of traffic, and maximize block error rate (BLER) with ultra-reliable low-latency communications (URLLC). Numerical results show that a smart jammer a) needs to compromise between missed detection (MD) probability and SE reduction with MBB and b) can achieve low detectability and high system performance degradation with URLLC only if it has sufficiently high power.

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arXiv2021

Interference Prediction for Low-Complexity Link Adaptation in Beyond 5G Ultra-Reliable Low-Latency Communications

Traditional link adaptation (LA) schemes in cellular network must be revised for networks beyond the fifth generation (b5G), to guarantee the strict latency and reliability requirements advocated by ultra reliable low latency communications (URLLC). In particular, a poor error rate prediction potentially increases retransmissions, which in turn increase latency and reduce reliability. In this paper, we present an interference prediction method to enhance LA for URLLC. To develop our prediction method, we propose a kernel based probability density estimation algorithm, and provide an in depth analysis of its statistical performance. We also provide a low complxity version, suitable for practical scenarios. The proposed scheme is compared with state-of-the-art LA solutions over fully compliant 3rd generation partnership project (3GPP) calibrated channels, showing the validity of our proposal.

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arXiv2020

Interference Distribution Prediction for Link Adaptation in Ultra-Reliable Low-Latency Communications

The strict latency and reliability requirements of ultra-reliable low-latency communications (URLLC) use cases are among the main drivers in fifth generation (5G) network design. Link adaptation (LA) is considered to be one of the bottlenecks to realize URLLC. In this paper, we focus on predicting the signal to interference plus noise ratio at the user to enhance the LA. Motivated by the fact that most of the URLLC use cases with most extreme latency and reliability requirements are characterized by semi-deterministic traffic, we propose to exploit the time correlation of the interference to compute useful statistics needed to predict the interference power in the next transmission. This prediction is exploited in the LA context to maximize the spectral efficiency while guaranteeing reliability at an arbitrary level. Numerical results are compared with state of the art interference prediction techniques for LA. We show that exploiting time correlation of the interference is an important enabler of URLLC.

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arXiv2019

5G Massive MIMO Architectures: Self-Backhauled Small Cells versus Direct Access

In this paper, we focus on one of the key technologies for the fifth-generation wireless communication networks, massive multiple-input-multiple-output (mMIMO), by investigating two of its most relevant architectures: 1) to provide in-band backhaul for the ultra-dense network (UDN) of self-backhauled small cells (SCs), and 2) to provide direct access (DA) to user equipments (UEs). Through comprehensive 3GPP-based system-level simulations and analytical formulations, we show the end-to-end UE rates achievable with these two architectures. Differently from the existing works, we provide results for two strategies of self-backhauled SC deployments, namely random and ad-hoc, where in the latter SCs are purposely positioned close to UEs to achieve line-of-sight (LoS) access links. We also evaluate the optimal backhaul and access time resource partition due to the in-band self-backhauling (s-BH) operations. Our results show that the ad-hoc deployment of self-backhauled SCs closer to the UEs with optimal resource partition and with directive antenna patterns, provides rate improvements for cell-edge UEs that amount to 30% and tenfold gain, as compared to mMIMO DA architecture with pilot reuse 3 and reuse 1, respectively. On the other hand, mMIMO s-BH underperforms mMIMO DA above the median value of the UE rates when the effect of pilot contamination is less severe, and the LoS probability of the DA links improves.

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arXiv2019

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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arXiv2018

Downlink Performance of Uplink Fractional Power Control in 5G Massive MIMO Systems

Uplink power control is an efficient scheme to mitigate pilot contamination in massive multiple-input multiple-output (MIMO) systems. In this work, we provide a comprehensive study on the effects of fractional power control (FPC) on the downlink performance of the most relevant fifth generation (5G) massive MIMO deployments. Specifically, we perform thorough system simulations based on the most recent three dimensional spatial channel model released by the 3rd Generation Partnership Project to evaluate the impact of different deployment-related parameters such as pilot reuse factor, beamforming criterion, and base station array size. Our results indicate the most suitable tuning of the FPC parameters and show that optimized FPC provides huge gains in the cell border throughput when compared to a baseline scheme with all the users transmitting at maximum power. Moreover, our simulations also demonstrate that the effectiveness of FPC grows in scenarios with severe pilot contamination, confirming that implementing this feature is essential in realistic deployments.

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arXiv2018

Performance of Massive MIMO Self-Backhauling for Ultra-Dense Small Cell Deployments

A key aspect of the fifth-generation wireless communication network will be the integration of different services and technologies to provide seamless connectivity. In this paper, we consider using massive multiple-input multiple-output (mMIMO) to provide backhaul links to a dense deployment of self-backhauling (s-BH) small cells (SCs) that provide cellular access within the same spectrum resources of the backhaul. Through a comprehensive system-level simulation study, we evaluate the interplay between access and backhaul and the resulting end-to-end user rates. Moreover, we analyze the impact of different SCs deployment strategies, while varying the time resource allocation between radio access and backhaul links. We finally compare the above mMIMO-based s-BH approach to a mMIMO direct access (DA) architecture accounting for the effects of pilot reuse schemes, together with their associated overhead and contamination mitigation effects. The results show that dense SCs deployments supported by mMIMO s-BH provide significant rate improvements for cell-edge users (UEs) in ultra-dense deployments with respect to mMIMO DA, while the latter outperforms mMIMO s-BH from the median UEs' standpoint.

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arXiv2018

Quantized Precoding for Multi-Antenna Downlink Channels with MAGIQ

A multi-antenna, greedy, iterative, and quantized (MAGIQ) precoding algorithm is proposed for downlink channels. MAGIQ allows a straightforward integration with orthogonal frequency-division multiplexing (OFDM). MAGIQ is compared to three existing algorithms in terms of information rates and complexity: quantized linear precoding (QLP), SQUID, and an ADMM-based algorithm. The information rate is measured by using a lower bound for finite modulation sets, and the complexity is measured by the number of multiplications and comparisons. MAGIQ and ADMM achieve similar information rates with similar complexity for Rayleigh flat-fading channels and one-bit quantization per real dimension, and they outperform QLP and SQUID for higher order modulation.

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arXiv2018

A Statistical Approach for RF Exposure Compliance Boundary Assessment in Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is a fundamental enabler to provide high data throughput in next generation cellular networks. By equipping the base stations (BSs) with tens or hundreds of antenna elements, narrow and high gain beams can be used to spatially multiplex several user equipment (UE) devices. While increasing the achievable performance, focusing the transmit power into specific UE directions also poses new issues when performing the radio frequency (RF) exposure assessment. In fact, the spatial distribution of the actual BS transmit power strongly depends on the deployment scenario and on the position of the UEs. Traditional methods for assessing the RF exposure compliance boundaries around BS sites are generally based on maximum transmit power and static beams. In massive MIMO systems, these approaches tend to be very conservative, in particular when time averaging is properly considered. In this work, we propose to leverage the three dimensional spatial channel model standardized by the Third Generation Partnership Project in order to assess reasonably foreseeable compliance boundaries of massive MIMO BSs. The analysis is performed by considering BSs fully loaded and different configurations of active UEs per cell. Numerical results show that the statistical approach developed in this paper allows reducing to nearly half the compliance distance when compared to the traditional method.

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arXiv2017

Uplink Sounding Reference Signal Coordination to Combat Pilot Contamination in 5G Massive MIMO

To guarantee the success of massive multiple-input multiple-output (MIMO), one of the main challenges to solve is the efficient management of pilot contamination. Allocation of fully orthogonal pilot sequences across the network would provide a solution to the problem, but the associated overhead would make this approach infeasible in practical systems. Ongoing fifth-generation (5G) standardisation activities are debating the amount of resources to be dedicated to the transmission of pilot sequences, focussing on uplink sounding reference signals (UL SRSs) design. In this paper, we extensively evaluate the performance of various UL SRS allocation strategies in practical deployments, shedding light on their strengths and weaknesses. Furthermore, we introduce a novel UL SRS fractional reuse (FR) scheme, denoted neighbour-aware FR (FR-NA). The proposed FR-NA generalizes the fixed reuse paradigm, and entails a tradeoff between i) aggressively sharing some UL SRS resources, and ii) protecting other UL SRS resources with the aim of relieving neighbouring BSs from pilot contamination. Said features result in a cell throughput improvement over both fixed reuse and state-of-the-art FR based on a cell-centric perspective.

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arXiv2017

Indoor Massive MIMO Deployments for Uniformly High Wireless Capacity

Providing consistently high wireless capacity is becoming increasingly important to support the applications required by future digital enterprises. In this paper, we propose Eigen-direction-aware ZF (EDA-ZF) with partial coordination among base stations (BSs) and distributed interference suppression as a practical approach to achieve this objective. We compare our solution with Zero Forcing (ZF), entailing neither BS coordination or inter-cell interference mitigation, and Network MIMO (NeMIMO), where full BS coordination enables centralized inter-cell interference management. We also evaluate the performance of said schemes for three sub-6 GHz deployments with varying BS densities -- sparse, intermediate, and dense -- all with fixed total number of antennas and radiated power. Extensive simulations show that: (i) indoor massive MIMO implementing the proposed EDA-ZF provides uniformly good rates for all users; (ii) indoor network densification is detrimental unless full coordination is implemented; (iii) deploying NeMIMO pays off under strong outdoor interference, especially for cell-edge users.

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arXiv2017

Resource Scheduling for Mixed Traffic Types with Scalable TTI in Dynamic TDD Systems

This paper analyses the performance benefits of a user-centric scheduling approach, exploiting the flexibility of both dynamic time division duplex (TDD) and a variable transmission time interval (TTI), where the downlink to uplink ratio and TTI duration can be adapted to the traffic load. The formulation of the joint optimisation problem takes into consideration the individual requirements of each single user in terms of sustainable latency and desired throughput, thus implementing a real user-centric scheduling approach. Moreover, the developed solution is evaluated in a scenario with mixed traffic types, mobile broadband (MBB) and mission critical communications (MCC), showing remarkable performance enhancement of the proposed scheme over baseline dynamic TDD schemes with a fixed TTI in terms of both achievable throughput of the MBB users and guaranteed latency for the MCC users.

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