arXiv subjects

Josep Vidal

Publications and source records attributed to Josep Vidal.

At least 19 recordsLinked to original sources

arXiv2026

RIS-assisted Multiuser MISO Transmission and the Impact of Imperfect Channel Estimation

This paper proposes the joint design of reconfigurable intelligent surfaces (RIS) and zero-forcing (ZF) precoding for the downlink (DL) multiuser multiple-input single-output (MU-MISO) setup in millimeter-wave (mmWave) bands, where ZF is particularly attractive due to its ability to suppress inter-user interference by exploiting the large antenna arrays and sparse directional channels characteristic of mmWave systems. This ensures efficient spatial multiplexing with manageable complexity, making ZF a practical and in modern 5G/6G deployments. However, a careful design is necessary to overcome potential rank deficiency in the channel matrix. For the MU-MISO case, rank deficiency may arise if users exhibit significantly different channel gains or if, being in far-field, they are aligned with the position of the transmitter. On the other hand, the deployment of a RIS introduces artificial scattering which can shape the radio environment to address those situations. We explore the joint design under perfect channel knowledge, assess the impact of imperfect channel estimation on the bit error rate (BER) and propose a robust design of pilot transmissions that equalizes multiuser interference across users in the presence of channel errors in the precoder design. This evaluation shows the advantages of optimized RIS-aided ZF MU-MISO communication for the DL of wireless systems.

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arXiv2025

Beyond Diagonal RIS-assisted MIMO Transmission: Beamforming Gain and Capacity Optimization

Reconfigurable Intelligent Surfaces (RIS) have emerged as a transformative technology in wireless communications, offering unprecedented control over signal propagation. This study focuses on passive beyond diagonal reconfigurable intelligent surface (BD-RIS), which has been proposed to generalize conventional diagonal RIS, in Multiple-Input Multiple-Output (MIMO) downlink (DL) communication systems. We compare the performance of transmit beamforming (TxBF) and MIMO capacity transmission with waterfilling power allocation in the millimeter wave (mmWave) band, where propagation primarily occurs under line-of-sight (LOS) conditions. In the lack of closed-form expressions for the optimal RIS elements in either case, our approach adopts a gradient-based optimization approach requiring lower complexity than the solution in arXiv:2406.02170. Numerical results reveal that BD-RIS significantly outperforms traditional diagonal RIS in terms of spectral efficiency and coverage

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arXiv2025

Contextual Bandits and Reconfigurable Intelligent Surfaces for Predictive LTM Handover Decisions

This article addresses the challenge of optimizing handover (HO) in next-generation wireless networks by integrating Reconfigurable Intelligent Surfaces (RIS), predicting received signal power, and utilizing learning-based decision-making. A conventional reactive HO mechanism, such as lower-layer triggered mobility (LTM), is enhanced through linear prediction to anticipate link degradation. Additionally, the use of RIS helps to mitigate signal blockage and extend coverage. An online trained non-linear Contextual Multi-Armed Bandit (CMAB) agent selects target gNBs based on context features, which reduces unnecessary HO and signaling overhead. Extensive simulations evaluate eight combinations of these techniques under realistic mobility and channel conditions. Results show that CMAB and RSRP prediction consistently reduce the number of HO, ping-pong rate and cell preparations, while RIS improves link reliability.

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arXiv2025

HMM for short independent sequences: Multiple sequence Baum-Welch application

In the classical setting, the training of a Hidden Markov Model (HMM) typically relies on a single, sufficiently long observation sequence that can be regarded as representative of the underlying stochastic process. In this context, the Expectation Maximization (EM) algorithm is applied in its specialized form for HMMs, namely the Baum Welch algorithm, which has been extensively employed in applications such as speech recognition. The objective of this work is to present pseudocode formulations for both the training and decoding procedures of HMMs in a different scenario, where the available data consist of multiple independent temporal sequences generated by the same model, each of relatively short duration, i.e., containing only a limited number of samples. Special emphasis is placed on the relevance of this formulation to longitudinal studies in population health, where datasets are naturally structured as collections of short trajectories across individuals with point data at follow up.

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arXiv2025

Deep Learning-Based Data Fusion of 6G Sensing and Inertial Information for Target Positioning: Experimental Validation

The sixth-generation (6G) cellular technology will be deployed with a key feature of Integrated Sensing and Communication (ISAC), allowing the cellular network to map the environment through radar sensing on top of providing communication services. In this regard, the entire network can be considered as a sensor with a broader Field of View (FoV) of the environment, assisting in both the positioning of active and detection of passive targets. On the other hand, the non-3GPP sensors available on the target can provide additional information specific to the target that can be beneficially combined with ISAC sensing information to enhance the overall achievable positioning accuracy. In this paper, we first study the performance of the ISAC system in terms of its achievable accuracy in positioning the mobile target in an indoor scenario. Second, we study the performance gain achieved in the ISAC positioning accuracy after fusing the information from the target's non-3GPP sensors. To this end, we propose a novel data fusion solution based on the deep learning framework to fuse the information from ISAC and non-3GPP sensors. We validate our proposed data fusion and positioning solution with a real-world ISAC Proof-of-Concept (PoC) as the wireless infrastructure, an Automated Guided Vehicle (AGV) as the target, and the Inertial Measurement Unit (IMU) sensor on the target as the non-3GPP sensor. The experimental results show that our proposed solution achieves an average positioning error of $3~\textrm{cm}$, outperforming the considered baselines.

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arXiv2024

A Survey of 5G-Based Positioning for Industry 4.0: State of the Art and Enhanced Techniques

The fifth generation (5G) mobile communication technology integrates communication, positioning, and mapping functionalities as an in-built feature. This has drawn significant attention from industries owing to the capability of replacing the traditional wireless technologies used in industries with 5G infrastructure that can be used for both connectivity and positioning. To this end, we identify the Automated Guided Vehicle (AGV) as a primary use case to benefit from the 5G functionalities. Given that there have been various works focusing on 5G positioning, it is necessary to analyze the existing works about their applicability with AGVs in industrial environments and provide insights to future research. In this paper, we present state of the art in 5G-based positioning, with a focus on key features, such as Millimeter Wave (mmWave) system, Massive Multiple Input Multiple Output (MIMO), Ultra-Dense Network (UDN), Device-to-Device (D2D) communication, and Reconfigurable Intelligent Surface (RIS). Moreover, we present the shortcomings in the current state of the art. Additionally, we propose enhanced techniques that can complement the accuracy of 5G-based positioning in controlled industrial environments.

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arXiv2024

Outlier Rejection for 5G-Based Indoor Positioning in Ray-Tracing-Enabled Industrial Scenario

The precise and accurate indoor positioning using cellular communication technology remains to be a prerequisite for several industrial applications, including the emergence of a new topic of Integrated Sensing and Communication (ISAC). However, the frequently occurring Non-Line-of-Sight (NLoS) conditions in a heavy multipath dominant industrial scenario challenge the wireless signal propagation, leading to abnormal estimation errors (outliers) in the signal measurements taken at the receiver. In this paper, we investigate the iterative positioning scheme that is robust to the outliers in the Time of Arrival (ToA) measurements. The Iteratively Reweighted Least Squares (IRLS) positioning scheme formulated on the Least Squares (LS) is implemented to reject the outlier measurements and reweight the available ToA samples based on their confidence. Our positioning scheme is validated under 5G frequency bands, including the C-band (3.7 GHz) and the mmWave-band (26.8 GHz) in a Ray-Tracing enabled industrial scenario with different emulation setups.

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arXiv2024

Slice-aware Resource Allocation and Admission Control for Smart Factory Wireless Networks

The 5th generation (5G) and beyond network offers substantial promise as the ideal wireless technology to replace the existing inflexible wired connections in traditional factories of today. 5G network slicing allows for tailored allocation of resources to different network services, each with unique Quality of Service (QoS) requirements. This paper presents a novel solution for slice-aware radio resource allocation based on a convex optimisation and control framework for applications in smart factory wireless networks. The proposed framework dynamically allocates minimum power and sub-channels to downlink mixed service type industrial users categorised into three slices: Capacity Limited (CL), Ultra Reliable Low Latency Communication (URLLC), and Time Sensitive (TS) slices. Given that the base station (BS) has limited transmission power, we enforce admission control by effectively relaxing the target rate constraints for current connections in the CL slice. This rate readjustment occurs whenever power consumption exceeds manageable levels. Simulation results show that our approach minimises power, allocates sub-channels to users, maintains slice isolation, and delivers QoS-specific communications to users in all the slices despite time-varying number of users and changing network conditions.

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arXiv2024

Slicing for Dense Smart Factory Network: Current State, Scenarios, Challenges and Expectations

In the era of Industry 4.0, smart factories have emerged as a paradigm shift, redefining manufacturing with the integration of advanced digital technologies. Central to this transformation is the deployment of 5G networks, offering unprecedented levels of connectivity, speed, reliability, and ultra-low latency. Among the revolutionary features of 5G is network slicing, a technology that offers enhanced capabilities through the customization of network resources by allowing multiple logical networks (or slices) to run on top of a shared physical infrastructure. This capability is particularly crucial in the densely packed and highly dynamic environment of smart factories, where diverse applications - from robotic automation to real-time analytics - demand varying network requirements. In this paper, we present a comprehensive overview of the integration of slicing in smart factory networks, emphasizing its critical role in enhancing operational efficiency and supporting the diverse requirements of future manufacturing processes. We elaborate on the recent advances, and technical scenarios, including indoor factory propagation conditions, traffic characteristics, system requirements, slice-aware radio resource management, network elements, enabling technologies and current standardisation efforts. Additionally, we identify open research challenges as well as key technical issues stifling deployments. Finally, we speculate on the future trajectory of slicing-enabled smart factories, emphasizing the need for continuous adaptation to emerging technologies.

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arXiv2020

6G in the Sky: On-Demand Intelligence at the Edge of 3D Networks

6G will exploit satellite, aerial and terrestrial platforms jointly to improve radio access capability and to unlock the support of on-demand edge cloud services in the three dimensional space (3D) by incorporating Mobile Edge Computing (MEC) functionalities on aerial platforms and low orbit satellites. This will extend the MEC support to devices and network elements in the sky and will forge a space borne MEC enabling intelligent personalized and distributed on demand services. 3D end users will experience the impression of being surrounded by a distributed computer fulfilling their requests in apparently zero latency. In this paper, we consider an architecture providing communication, computation, and caching (C3) services on demand, anytime and everywhere in 3D space, building on the integration of conventional ground (terrestrial) base stations and flying (non-terrestrial) nodes. Given the complexity of the overall network, the C3 resources and the management of the aerial devices need to be jointly orchestrated via AI-based algorithms, exploiting virtualized networks functions dynamically deployed in a distributed manner across terrestrial and non-terrestrial nodes.

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arXiv2019

On the Degrees of Freedom of the MISO Interference Broadcast Channel with Delayed CSIT

The Maddah-Ali and Tse (MAT) scheme is a linear precoding strategy that exploits Interference Alignment and perfect, but delayed, channel state information at the transmitters (delayed CSIT), improving the degrees of freedom (DoF) that can be achieved for the broadcast channel (BC). Since its appearance, many works have extended the concept of Retrospective Interference Alignment (RIA) to other multi-user channel configurations. However, little is known about the broadcast channel with multiple cells, i.e. the interference broadcast channel (IBC). In this work, the DoF are studied for the $K$-user $C$-cell multiple-input single-output (MISO) IBC with delayed CSIT (with $K/C$ users per cell). We show that the straightforward application of the MAT scheme over the IBC fails because it requires all interference to be received from the same source. Hence, in this case not all the interference can be cancelled, thus blocking the decoding of the received messages. We call this phenomenon as \textit{interference coupling}, forcing to use the MAT scheme by serving just one cell at a time. In this work, we propose an extension, namely the uncoupled MAT scheme (uMAT), exploiting multiple cells, uncoupling the interference, and achieving the best known DoF inner bound for almost all settings.

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arXiv2018

Receive Spatial Modulation for Massive MIMO Systems

In this paper, we consider the downlink of a massive multiple-input-multiple-output (MIMO) single user transmission system operating in the millimeter wave outdoor narrowband channel environment. We propose a novel receive spatial modulation architecture aimed to reduce the power consumption at the user terminal, while attaining a significant throughput. The energy consumption reduction is obtained through the use of analog devices (amplitude detector), which reduces the number of radio frequency chains and analog-to-digital-converters (ADCs). The base station transmits spatial and modulation symbols per channel use. We show that the optimal spatial symbol detector is a threshold detector that can be implemented by using one bit ADC. We derive closed form expressions for the detection threshold at different signal-to-noise-ratio (SNR) regions showing that a simple threshold can be obtained at high SNR and its performance approaches the exact threshold. We derive expressions for the average bit error probability in the presence and absence of the threshold estimation error showing that a small number of pilot symbols is needed. A performance comparison is done between the proposed system and fully digital MIMO showing that a suitable constellation selection can reduce the performance gap.

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arXiv2016

Analysis of Downlink and Uplink Decoupling in Dense Cellular Networks

Decoupling uplink (UL) and downlink (DL) is a new architectural paradigm where DL and UL are not constrained to be associated to the same base station (BS). Building upon this paradigm, the goal of the present paper is to provide lower, albeit tight bounds for the ergodic UL capacity of a decoupled cellular network. The analysis is performed for a scenario consisting of a macro BS and a set of small cells (SCs) whose positions are selected randomly according to a Poisson point process of a given spatial density. Based on this analysis simple bounds in closed form expressions are defined. The devised bounds are employed to compare the performance of the decoupled case versus a set of benchmark cases, namely the coupled case, and the situations of having either a single macro BS or only SCs. This comparison provides valuable insights regarding the behavior and performance of such networks, providing simpler expressions for the ergodic UL capacity as a function of the distances to the macro BS and the density of SCs. These expressions constitute a simple guide to the minimum degree of densification that guarantees the Quality of Service (QoS) objectives of the network, thus, providing a valuable tool to the network operator of significant practical and commercial value.

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arXiv2015

DoF-Delay Trade-Off for the $K$-user MIMO Interference Channel With Delayed CSIT

The degrees of freedom (DoF) of the $K$-user multiple-input multiple-output (MIMO) interference channel are studied when perfect, but delayed channel state information is available at the transmitter side (delayed CSIT). Recent works have proposed schemes that achieve increasing DoF values, but at the cost of long communication delays. This work proposes three linear precoding strategies, formulated in such a way that the achievable DoF can be derived as a function of the transmission delay, thus elucidating its achievable DoF-delay trade-off. All strategies are based on the concept of interference alignment, and built upon three main ingredients: delayed CSIT precoding, user scheduling, and redundancy transmission. In this respect, the interference alignment is realized by exploiting delayed CSIT in order to align the interference at the non-intended receivers along the space-time domain. Finally, the latter part of this work settles that all the proposed strategies work also for constant channels, except for SISO. In such a case, the schemes can be made feasible by resorting to asymmetric complex signaling concepts. This conclusion removes the time-varying channels assumption unnecessarily common along all the literature on delayed CSIT.

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arXiv2015

Retrospective Interference Alignment for the MIMO Interference Broadcast Channel

The degrees of freedom (DoF) of the multiple-input multiple-output (MIMO) Interference Broadcast Channel (IBC) with 2 cells and 2 users per cell are investigated when only delayed channel state information is available at the transmitter side (delayed CSIT). Retrospective Interference Alignment has shown the benefits in terms of DoF of exploiting delayed CSIT for interference, broadcast and also for the IBC. However, previous works studying the IBC with delayed CSIT do not exploit the fact that the users of each cell are served by a common transmitter. This work presents a four-phase precoding strategy taking this into consideration. Assuming that transmitters and receivers are equipped with $M,N$ antennas, respectively, new DoF inner bounds are proposed, outperforming the existing ones for $ρ= \frac{M}{N} > 2.6413$.

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arXiv2014

Optimization of Radio and Computational Resources for Energy Efficiency in Latency-Constrained Application Offloading

Providing femto-access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smart-phones to the so called femto-cloud. Such offloading promises to be beneficial in terms of battery saving at the mobile terminal (MT) and/or latency reduction in the execution of applications, whenever the energy and/or time required for the communication process are compensated by the energy and/or time savings that result from the remote computation at the FAPs. For this problem, we provide in this paper a framework for the joint optimization of the radio and computational resource usage exploiting the tradeoff between energy consumption and latency, and assuming that multiple antennas are available at the MT and the serving FAP. As a result of the optimization, the optimal communication strategy (e.g., transmission power, rate, precoder) is obtained, as well as the optimal distribution of the computational load between the handset and the serving FAP. The paper also establishes the conditions under which total or no offloading are optimal, determines which is the minimum affordable latency in the execution of the application, and analyzes as a particular case the minimization of the total consumed energy without latency constraints.

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arXiv2014

The DoF of the 3-user ($p,p+1$) MIMO Interference Channel

The \emph{degrees of freedom} (DoF) of the 3-user multiple-input multiple-output (MIMO) interference channel (IC) with full channel state information (CSI) and constant channel coefficients are characterized when linear filters are employed and $(p,p+1)$ antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al, which conjectured but not proved the DoF for the configuration tackled in this work. In this work we prove the optimal DoF by means of a transmission scheme based on asymmetric complex signaling (ACS) together with symbol extensions in time and interference alignment (IA) concepts. The paper deals with the $p=2,3$ cases, providing the transmit and receive filters and the tools needed for proving the achievability of the DoF for other values of $p$.

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arXiv2014

Retrospective Interference Alignment for the 3-user MIMO Interference Channel with delayed CSIT

The degrees of freedom (DoF) of the 3-user multiple input multiple output interference channel (3-user MIMO IC) are investigated where there is delayed channel state information at the transmitters (dCSIT). We generalize the ideas of Maleki et al. about {\it Retrospective Interference Alignment (RIA)} to be applied to the MIMO IC, where transmitters and receivers are equipped with $(M,N)$ antennas, respectively. We propose a two-phase transmission scheme where the number of slots per phase and number of transmitted symbols are optimized by solving a maximization problem. Finally, we review the existing achievable DoF results in the literature as a function of the ratio between transmitting and receiving antennas $ρ=M/N$. The proposed scheme improves all other strategies when $ρ\in \left(\frac{1}{2}, \frac{31}{32} \right]$.

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