Visible light communication (VLC) systems have emerged as a promising solution to radio frequency (RF) spectrum scarcity, providing wide, unlicensed bandwidth and enhanced security in RF-free environments. However, VLC systems are prone to significant signal degradation caused by receiver movement or rotation, which limits their applicability in dynamic or mobile scenarios. To address this challenge, we introduce the concept of liquid-based reconfigurable lens (LiqRL), an innovative reconfigurable optical architecture that leverages the adaptability and spatial diversity of liquid materials to enhance signal reception and mitigate the impact of blockage sensitivity in VLC networks. The key contribution of this work lies in the development of a comprehensive mathematical model to evaluate the performance of mobile user equipment (UE) in VLC environments with LiqRL-based orientation adjustable receivers (OAR). By employing stochastic geometry, we derive analytical and closed-form expressions for coverage probability and propose a novel distance-based orientation selection mechanism that optimizes spatial alignment for improved data transmission efficiency. We further account for temporal interference correlation caused by UE mobility and evaluate the probability of successful communication across different time slots. Our results show that the LiqRL-based OAR architecture improves network performance by approximately 15% compared to conventional VLC systems, demonstrating the potential of reconfigurable optical architectures for dynamic and mobile VLC scenarios.

In this paper, we investigate a simultaneous wireless information and power transfer (SWIPT)-assisted vehicular network. By utilizing the concept of SWIPT technology, batteryoperated road-side sensors (RSSs) simultaneously receive control information and harvest energy from cellular base stations (BSs), followed by their communication with vehicles by utilizing the harvested energy. By leveraging stochastic geometry tools, we establish a tractable framework, where the load of BSs and RSSs are taken into account. The analytical expressions for the active probability and average harvested energy of RSSs, as well as the information decoding (ID) success probability of vehicles are derived. The optimal RSSs' density and time splitting factor that maximize ID success probability are illustrated. Additionally, the optimal sensor density within vehicular networks dynamically adjusts in response to varying traffic congestion levels. These results offer invaluable insights for vehicular network design, highlighting the need for adaptive strategies that seamlessly respond to evolving network conditions and traffic patterns.

In this paper, we consider a tunable liquid convex lens-assisted imaging receiver for indoor multiple-input multiple-output (MIMO) visible light communication (VLC) systems. In contrast to existing MIMO VLC receivers that rely on fixed optical lenses, the proposed receiver leverages the additional degrees of freedom offered by liquid lenses via adjusting both focal length and orientation angles of the lens. This capability facilitates the mitigation of spatial correlation between the channel gains, thereby enhancing the overall signal quality and leading to improved bit-error rate (BER) performance. We present an accurate channel model for the liquid lens-assisted VLC system by using three-dimensional geometry and geometric optics. To achieve optimal performance under practical conditions such as random receiver orientation and user mobility, optimization of both focal length and orientation angles of the lens are required. To this end, driven by the fact that channel models are mathematically complex, we present two optimization schemes including a blockwise machine learning (ML) architecture that includes convolution layers to extract spatial features from the received signal, long-short term memory layers to predict the user position and orientation, and fully connected layers to estimate the optimal lens parameters. Numerical results are presented to compare the performance of each scheme with conventional receivers. Results show that a significant BER improvement is achieved when liquid lenses and presented ML-based optimization approaches are used. Specifically, the BER can be improved from 6 × 10−2to 1.4 × 10−3at an average signal-to-noise ratio of 30 dB.

The co-design of fluid antenna (FA) technology and simultaneous wireless information and power transfer (SWIPT) can be jointly beneficial. Specifically, SWIPT facilitates both data and energy transfer to low-power devices, while FA technology introduces a new dimension for optimizing SWIPT performance through intelligent port selection. Thus, in this work, we develop an analytical framework by employing stochastic geometry and copula theory to evaluate FA-enabled users’ performance in SWIPT networks. All users utilize successive interference cancellation and two novel port selection schemes, namely information decoding-focused (IDf) and energy harvest-focused (EHf), to leverage FAs’ liquid dimension for enhanced data or energy transfer, by considering the counterposed effects of multi-user interference. We derive closed-form expressions for signal-to-interference ratio and received signal power under correlated Nakagami-$\kappa $fading by using Student’s t copula. The developed framework assesses SWIPT performance meta-distribution of the proposed schemes and facilitates the performance evaluation of two user location-based classifications i.e., cell-center (CC) and cell-edge (CE) users. Results reveal the beneficial synergy of FAs and SWIPT, with around 29% improvement for CC and 133% for CE users compared to conventional static SWIPT communications, and highlight that the EHf scheme proves more efficient for CE users, while the IDf scheme benefits CC users.

By utilizing the combination of two powerful tools i.e., stochastic geometry (SG) and copula theory (CT), in this paper, we assess the performance of fluid-based reconfigurable antenna (FA)-enabled user equipments (UEs) in the context of simultaneous wireless information and power transfer (SWIPT) networks. Particularly, by using CT tools, we initially derive a closed-form expression for the cumulative distribution function of the observed signal-to-interference ratio (SIR) under correlated Nakagami-μ fading channels by exploiting a well-investigated Archimedean copula, namely the Frank copula. According to the CT-based approach, a SG-based framework is presented to assess the SWIPT performance of FA-enabled UEs, that are equipped with a power splitting scheme to simultaneously extract information and harvest energy from the port with the strongest SIR. Our results reveal that FA-enabled SWIPT systems experience an improved information decoding performance of around 30% with a slight reduction in energy harvest performance of around 6% compared to conventional fixed-positioned antennas systems.

In this paper, we study the performance of fluid antenna (FA)-enabled user equipments (UEs) in the context of simultaneous wireless information and power transfer (SWIPT) networks. All UEs have successive interference cancellation (SIC) capabilities and employ a novel port selection (PS) scheme. In contrast to existing PS approaches, where the FA port with the highest signal-to-interference ratio (SIR) is selected, a UE communicates with its serving base station (BS) through the port that offers the minimum SIR. The proposed PS scheme leverages the additional degree of freedom offered by the FA technology to ensure the successful implementation of the SIC process, leading to an improved information decoding (ID) and energy harvest (EH) performance. By using stochastic geometry tools, analytical expressions for the ID and EH outage probability are derived. Our results illustrate that the employment of the proposed PS scheme leads to improved ID and EH performance of around 10% compared to conventional PS schemes.

Owing to the growing demand for ubiquitous connectivity, low earth orbit (LEO) satellite-based communication networks are envisioned as a key-enabling technology for the next-generation networks. However, the existing literature disregards the heterogeneous nature of the real-world LEO satellite networks. Motivated by this, in this paper, an analytical framework based on stochastic geometry is developed, aiming to assess the down-link coverage performance of the large-scale heterogeneous LEO satellite-based communication networks. Based on the proposed mathematical framework, we derive the analytical expressions for the coverage probability, by taking into account the existence of inter-cell interference. Our results show that the inter-cell interference and fading channels jeopardize the coverage performance. Moreover, increasing the transmit power can improve the coverage probability at the low signal-to-noise ratio regime. Finally, we demonstrate that a higher coverage probability is achieved by narrowing the beam and/or by lowering the altitude of the LEO satellites.

The concept of reconfigurable fluid antennas (FAs) is a potential and promising solution to enhance the spectral efficiency of wireless communication networks. Despite their many advantages, FA-enabled communications require a significant amount of spectral resources in order to select the most desirable position of the radiating element from a large number of prescribed locations. In this paper, we present an analytical framework for the outage performance of large-scale FA-enabled communications under limited coherence interval scenario. Under this framework, we propose a novel sequential linear minimum mean-squared error-based channel estimation method, that is performed for a limited number of FA ports, followed by data reception from the port with the strongest estimated channel. A complete analytical framework in terms of the outage probability is developed by using tools from stochastic geometry. Our results reveal that the proposed technique can provide significant performance gains, especially for FAs with a large number of ports.

The synergy of fluid-based reconfigurable antenna (FA) technology and full-duplex (FD) communications can be jointly beneficial, as FD can enhance the spectral efficiency of a point-to-point link, while the new degree of freedom offered by the FA technology can be exploited to handle the overall interference. Hence, in this paper, an analytical framework based on stochastic geometry is developed, aiming to assess both the outage and average sum-rate performance of large-scale FA-aided FD cellular networks. In contrast to existing studies, where perfect channel state information is assumed, the developed framework accurately captures the impact of channel estimation (CE) on the performance of the considered network deployments, as well as the existence of residual loop-interference (LI) at the FD transceivers. Particularly, we focus on a limited coherence interval scenario, where a novel sequential linear minimum-mean-squared-error-based CE method is performed for all FA ports and LI links, followed by data reception from the port with the strongest estimated channel. By using stochastic geometry tools, analytical expressions for the outage and the average sum-rate performance are derived. Our results reveal that FA-aided FD communications experience an improved average sum-rate performance of around 45% compared to conventional FD communications.

The concept of reconfigurable fluid antennas (FA) is a potential and promising solution to enhance the spectral efficiency of wireless communication networks. Despite their many advantages, FA-enabled communications have limitations as they require an enormous amount of spectral resources in order to select the most desirable position of the radiating element from a large number of prescribed locations. In this paper, we present an analytical framework for the outage performance of large-scale FA-enabled communications, where all user equipments (UEs) employ circular multi-FA array. In contrast to existing studies, which assume perfect channel state information, the developed framework accurately captures the channel estimation errors on the performance of the considered network deployments. In particular, we focus on the limited coherence interval scenario, where a novel sequential linear minimum mean-squared error (LMMSE)-based channel estimation method is performed for only a very small number of FA ports. Next, for the communication of each BS with its associated UE, a low-complexity port-selection technique is employed, where the port that provides the highest signal-to-interference-plus-noise-ratio is selected among the ports that are estimated to provide the strongest channel from each FA. By using stochastic geometry tools, we derive both analytical and closed-form expressions for the outage probability, highlighting the impact of channel estimation on the performance of FA-based UEs. Our results reveal the trade-off imposed between improving the network’s performance and reducing the channel estimation quality, indicating new insights for the design of FA-enabled communications.

In this paper, we evaluate the performance of a linear minimum mean square error (MMSE) receiver in the context of simultaneous wireless information and power transfer (SWIPT)-enabled cellular networks. In contract to the existing works, where a single-antenna SWIPT architecture is mainly considered, we focus on the SWIPT performance of the multi-antenna receiver architecture, based on the antenna switching (AS) and power splitting (PS) techniques. Aiming to further boost the network performance, we investigate a scenario where the receivers have the capability to employ a successive interference cancellation (SIC) scheme. By leveraging tools from stochastic geometry, we establish an analytical and tractable framework to evaluate the information decoding (ID) and the energy harvesting (EH) success probabilities of the considered network topologies. Our results reveal that the ID performance achieved by the MMSE receiver outperforms that of the conventional maximum ratio combining, leading to an enhanced EH performance, for a given ID reliability constraint. Moreover, by allocating an equal fraction of resources for ID and EH purpose, the PS scheme outperforms the AS in terms of both ID and EH success probabilities.

In this paper, we investigate the outage performance of fluid antenna (FA)-based user equipments (UEs) in the context of large-scale downlink cellular networks, where all UEs employ linear minimum mean-squared error (LMMSE) channel estimation method. In contrast to existing studies, which assume the existence of perfect channel state information, we develop a novel mathematical framework that accurately captures the channel estimation errors on the performance of the considered network deployment. Specifically, we focus on the limited coherence interval scenario, where a sequential LMMSE-based channel estimation procedure is performed for all FA ports, followed by data reception from the port with the strongest estimated channel. By using stochastic geometry tools, we derive both analytical and closed-form expressions for the achieved outage probability, highlighting the impact of channel estimation on the performance of FA-based UEs. Our results reveal the trade-off imposed between improving the network’s outage performance and reducing the channel estimation quality, indicating new insights for the design of FA-based wireless systems.

In this paper, we investigate the performance of a linear minimum mean square error (MMSE) receiver in the context of simultaneous wireless information and power transfer (SWIPT)-enabled cellular networks. Specifically, the multi-antenna user equipments (UEs) are equipped with a linear MMSE receiver and employ either the time switching (TS), the power splitting (PS) or the antenna switching (AS) schemes to achieve the SWIPT capability, while a non-linear energy harvesting (EH) model is considered. The performance achieved by a linear MMSE receiver in the considered network deployment is evaluated in terms of multiple key performance metrics, e.g. information decoding (ID) and EH coverage probabilities, average spectral efficiency and average harvested energy. By leveraging tools from stochastic geometry, we establish an analytical and tractable framework to evaluate the aforementioned performance metrics, of which the analytical expressions are derived. Our results reveal that the ID performance achieved by the MMSE receiver outperforms that of the conventional maximum ratio combining, leading to an enhanced EH performance, for a given ID reliability constraint. Moreover, by using a linear MMSE receiver, PS scheme offers the best SWIPT performance compared to TS and AS schemes.

In this paper, we study the co-design of full-duplex (FD) radio with joint communication and radar sensing (JCAS) techniques in millimeter-wave (mmWave) heterogeneous networks (HetNets). Spectral co-existence of radar and communication systems causes mutual interference between the two systems, compromising both the data exchange and sensing capabilities. Focusing on the detection performance, we propose a cooperative detection technique, which exploits the sensing information from multiple base stations (BSs), aiming at enhancing the probability of successfully detecting an object. Three combining rules are considered, namely theOR, theMajorityand theANDrule. In real-world network scenarios, the locations of the BSs are spatially correlated, exhibiting a repulsive behavior. Therefore, we model the spatial distribution of the BSs as a$\beta$-Ginibre point process ($\beta$-GPP), which can characterize the repulsion among the BSs. By using stochastic geometry tools, analytical expressions for the detection performance of$\beta$-GPP-based FD-JCAS systems are expressed for each of the considered combining rule. Furthermore, by considering temporal interference correlation, we evaluate the probability of successfully detecting an object over two different time slots. Our results demonstrate that our proposed technique can significantly improve the detection performance when compared to the conventional non-cooperative technique.

By utilizing the combination of two powerful tools i.e., stochastic geometry (SG) and evolutionary game theory (EGT), in this paper, we study the problem of mobile user (MU) mode selection in heterogeneous sub-6 GHz/millimeter wave (mmWave) cellular networks. Particularly, by using SG tools, we first propose an analytical framework to assess the performance of the considered networks in terms of average signal-to-interference-plus-noise (SINR) ratio, average rate, and mobility-induced time overhead, for scenarios with user mobility. According to the SG-based framework, an EGT-based approach is presented to solve the problem of access mode selection. Specifically, two EGT-based models are considered, where for each MU its utility function depends on the average SINR and the average rate, respectively, while the time overhead is considered as a penalty term. A distributed algorithm is proposed to reach the evolutionary equilibrium, where the existence and stability of the equilibrium is theoretically analyzed and proved. Moreover, we extend the formulation by considering information delay exchange and evaluate its impact on the convergence of the proposed algorithm. Our results reveal that the proposed technique can offer better spectral efficiency and connectivity in heterogeneous sub-6 GHz/mmWave cellular networks with mobility, compared with the conventional access mode selection techniques.

In this paper, we investigate a low complexity technique for simultaneous wireless information and power transfer (SWIPT) in the context of cellular networks, where the multiple-antenna user equipments (UEs) employ maximum ratio combining technique. In particular, our proposed technique allocates a subset of antennas for information decoding (ID), only when their post-combiner signal-to-interference ratio exceeds a certain threshold, while the remaining antennas are allocated for energy harvesting (EH). In contrast to conventional approaches, where an uncorrelated or a fully correlated interference is considered, we develop a realistic mathematical framework that accurately captures the interference correlation effects on the performance of the proposed technique. By using stochastic geometry tools, we derive analytical expressions for both the ID and EH success probability, as well as the joint ID and EH success probability. Our results demonstrate the impact of spatial interference correlation on both the ID and the EH success probability, and we establish the optimal threshold for the proposed antenna switching scheme, that maximizes the joint ID and EH success probability.

In this paper, we assess the effect of full-duplex (FD) radio in the context of millimeter-wave (mm-Wave) communications. Particularly, we propose an analytical framework, based on stochastic geometry, to evaluate the performance of heterogeneous FD-mm-Wave cellular networks for two user location-based classifications, namely cell-center users (CCUs) and cell-edge users (CEUs). Moreover, we evaluate the performance of the considered networks with successive interference cancellation (SIC) capabilities. Based on the proposed framework, analytical expressions for the coverage and sum-rate performance are derived. We investigate the impact of FD-mm-Wave communications on the network performance of CCUs/CEUs and quantify the associated performance gains under different network parameter settings. Our results demonstrate the beneficial combination of FD radio with heterogeneous mm-Wave cellular networks, since it increases the spectral efficiency but also alleviates the effects of the multi-user interference. Furthermore, we present the tradeoff between the coverage and sum-rate performance of heterogeneous FD-mm-Wave cellular networks for the considered user classifications. The results show that half-duplex mode is beneficial for the CEUs to achieve better network performance, as opposed to the CCUs for which FD mode is more efficient. Finally, we show the effectiveness of SIC on the network performance, with significant performance gains for the CEUs.

In this paper, we assess the effect of full-duplex (FD) communications in the context of millimeter-wave (mmWave) cellular networks. The FD radio can potentially double the spectral efficiency but its performance is compromised by the existence of loop- and multi-user interference compared to half-duplex radio. Using stochastic geometry tools, we propose an analytical framework to evaluate the performance of FD-mmWave cellular networks for two location-based user classifications, namely cell-center users (CCUs) and cell-edge users (CEUs). Based on the proposed framework, analytical expressions for the downlink and the uplink coverage performance are derived for each user classification. We evaluate the impact of the FD radio on the performance of CCUs/CEUs and quantify the associated performance gains under different network parameter settings. Our results demonstrate the significant impact of the user's location on the network performance and the beneficial combination of FD radio with mmWaves, which provides significant gains, as it alleviates the effects of multi-user interference.

In this paper, we study the performance of next-generation cellular networks in the context of a low-complexity base station (BS) selection scheme. In contrast to existing BS cooperation approaches, where multiple BSs jointly transmit to the user, by using our proposed low-complexity technique, a user communicates with the BS that provides the maximum signal-to-interference-plus-noise-ratio from a set formed according to a pre-selection policy. We consider three pre-selection policies based on: 1) the Euclidean distance; 2) the averaged received power; and 3) a random selection. Moreover, we consider the case where the users have the ability to employ the successive interference cancellation (SIC) scheme. Despite its high computational complexity, SIC can potentially decode and remove strong interfering signals from the aggregate received signal, which can significantly boost the user's performance. By using stochastic geometry tools, analytical expressions for the coverage performance are derived for each policy, by taking into account spatial randomness and blockage effects. Our proposed technique provides low computational and implementation complexity due to the two-level selection scheme. Furthermore, we show that our proposed scheme does not lose in diversity compared with existing cooperation techniques and that all policies can benefit by the employment of the SIC scheme.

In this paper, we study the problem of base station (BS) cooperation in millimeter wave multi- tier heterogeneous cellular networks. In contrast to conventional approaches, where a number of BSs jointly transmit data to a user, we investigate a low-complexity technique that enables the selection of a single BS for transmission. Specifically, a single BS that provides the highest instantaneous signal-to-interference-plus- noise ratio is selected, among the strongest BSs from each tier. By using stochastic geometry tools, we derive closed-form expressions for the coverage probability and the diversity gain of the system by taking into account spatial randomness and blockage effects. Our results show that the proposed scheme achieves full diversity and is appropriate for networks with strict computation constraints. In addition, we study the case where users employ successive interference cancellation (SIC) to further boost the achieved performance; SIC allows the mitigation of strong interference terms from the received signal. The impact of SIC on the coverage probability of the system is studied and closed-form expressions are provided.

Motivated by the effects of buildings/obstacles on the performance of high frequency cellular networks, this paper deals with the base station (BS) cooperation in heterogeneous cellular networks with blockages. Our main focus is a joint transmission scenario, where an ideal backhaul network allows a set of randomly located BSs belonging to different network tiers, to cooperate and jointly transmit data. By using concepts from random shape theory, we model the spatial randomness as well as the main characteristics of the blockages (e.g., size, orientation, etc). The outage probability performance of the system is analyzed for two low complexity transmission techniques with different channel state information requirements by using stochastic geometry tools. Our results show that the spatial diversity associated with the BS cooperation is an efficient technique to overcome the degradation effects of blockages and ensure connectivity.

This paper proposes a compiler-in-the-loop exploration framework during architectural DSP synthesis. We extend the conventional design space, considering code level transformations together with architectural level optimizations and their impact on the scheduled datapath. We show that the proposed methodology explores the design space more globally in comparison with existing methods. New trade-off points are revealed and Pareto curve shifting towards higher quality design solutions is performed.

The software cost estimation process is one of the most critical managerial activities related to project planning, resource allocation and control. As software development is a highly dynamic procedure, the difficulty of providing accurate cost estimations tends to increase with development complexity. The inherent problems of the estimation process stem from its dependence on several complex variables, whose values are often imprecise, unknown, or incomplete, and their interrelationships are not easy to comprehend. Current software cost estimation models do not inspire enough confidence and accuracy with their predictions. This is mainly due to the models' sensitivity to project data values, and this problem is amplified because of the vast variances found in historical project attribute data. This paper aspires to provide a framework for evolving value ranges for cost attributes and attaining mean effort values using the Al-oriented problem-solving approach of genetic algorithms, with a twofold aim. Firstly, to provide effort estimations by analogy to the projects classified in the evolved ranges and secondly, to identify any present correlations between effort and cost attributes.