Packet repetitions combined with frequency channel hopping is a promising solution for improving reliability in dense in-X subnetwork deployments. In this paper, we propose a centralized repetition selection (C-Rep) scheme where a controller selects the number of packet repetitions to be used by each subnetwork based on the interference coupling. We first derive the optimal and near optimal average failure probability of the presented scheme, and propose a low complexity empirical cost function to be minimized via a genetic algorithm. Simulation results highlight the capability of C-Rep of reducing the failure probability in the subnetwork deployment by a factor of ∼ ×10 and above with respect to benchmark methods with optimized fixed number of packet repetitions. The empirically defined cost function leads to similar performance as when the near-optimal failure probability is used as a cost function, while reducing the number of calculations by a factor of above ∼ ×40. Robustness of the proposed scheme to different radio propagation conditions has also been verified.

This paper presents an energy-efficient transmission framework for federated learning (FL) in industrial Internet of Things (IIoT) environments with strict latency and energy constraints. Machinery subnetworks (SNs) collaboratively train a global model by uploading local updates to an edge server (ES), either directly or via neighboring SNs acting as decode-and-forward relays. To enhance communication efficiency, relays perform partial aggregation before forwarding the models to the ES, significantly reducing overhead and training latency. We analyze the convergence behavior of this relay-assisted FL scheme. To address the inherent energy efficiency (EE) challenges, we decompose the original non-convex optimization problem into sub-problems addressing computation and communication energy separately. An SN grouping algorithm categorizes devices into single-hop and two-hop transmitters based on latency minimization, followed by a relay selection mechanism. To improve FL reliability, we further maximize the number of SNs that meet the roundwise delay constraint, promoting broader participation and improved convergence stability under practical IIoT data distributions. Transmit power levels are then optimized to maximize EE, and a sequential parametric convex approximation (SPCA) method is proposed for joint configuration of system parameters. We further extend the EE formulation to the imperfect channel state information (ICSI). Simulation results demonstrate that the proposed framework significantly enhances convergence speed, reduces outage probability from 10−2in single-hop to 10−6and achieves substantial energy savings, with the SPCA approach reducing energy consumption by at least 2× compared to unaggregated cooperation and up to 6× over single-hop transmission.

6G In-Factory Subnetworks (InF-S) have recently been introduced as short-range, low-power radio cells installed in robots and production modules to support the strict requirements of modern control systems. Information freshness, characterized by the Age of Information (AoI), is crucial to guarantee the stability and accuracy of the control loop in these systems. However, achieving strict AoI performance poses significant challenges considering the limited resources and the high dynamic environment of InF-S. In this work, we introduce a proactive radio resource allocation approach to minimize the AoI violation probability. The proposed approach adopts a de-centralized learning framework using Bayesian Ridge Regression (BRR) to predict the future AoI by actively learning the system dynamics. Based on the predicted AoI value, radio resources are proactively allocated to minimize the probability of AoI exceeding a predefined threshold, hence enhancing the reliability and accuracy of the control loop. The conducted simulation results prove the effectiveness of our proposed approach to improve the AoI performance where a reduction of 98% is achieved in the AoI violation probability compared to relevant baseline methods.

The concept of subnetworks has been recently identified as a key component of 6 G, enabling mission-critical services with hyper-reliability. In this paper, we address the challenges posed by both inter-subnetwork interference and external interference in hyper-dense and dynamic industrial environments. We focus on in-factory subnetworks for industrial wireless control applications and propose an advanced frequency-power resource allocation scheme using Gradient Descent-based Resource Allocation (GDRA). The proposed GDRA scheme efficiently mitigates interference while optimizing resource allocation. We evaluate the performance of the proposed scheme and compare it with state-of-the-art approaches, demonstrating significant improvements in spectral efficiency and reliability.

Advances in communication technologies, such as cell-free massive multi-input multiple-output architecture and edge computing, are expected to support diverse heterogeneous service requirements in industrial use cases. However, the diverse communication demands of Industry 4.0 use cases make it essential to efficiently manage both radio and computational resources. This paper introduces a novel approach that addresses these challenges through a two-step sequential optimization process. First, we propose a genetic algorithm-based radio resource allocation scheme from a scheduling perspective. A second subproblem concerning computational resource allocation is also addressed sequentially. The numerical results demonstrate that our proposed algorithm significantly improves latency compliance and effectively reduces the percentage of packets that violate deadline constraints. Considering services with small packets and strict latency constraints, the proposed scheme achieves gains of 98.5% and 99.5% compared to the benchmarking schemes. Furthermore, the proposed solution has shown great adaptability to varying latency requirements and traffic with respect to state-of-the-art schemes.

In the era of Industry 4.0, precise indoor localization is vital for automation and efficiency in smart factories. Reconfigurable Intelligent Surfaces (RIS) are emerging as key enablers in 6G networks for joint sensing and communication. However, RIS faces significant challenges in Non-Line-of-Sight (NLOS) and multipath propagation, particularly in localization scenarios, where detecting NLOS conditions is crucial for ensuring not only reliable results and increased connectivity but also smart factory personnel's safety. This study introduces an AI-assisted framework employing a Convolutional Neural Network (CNN) customized for accurate Line-of-Sight (LOS) and NLOS classification to enhance RIS-based localization using measured, synthetic, mixedmeasured, and mixed-synthetic experimental data, that is, original, augmented, slightly noisy, and highly noisy data, respectively. Validated through such data from three different environments, the proposed customized-CNN (cCNN) model achieves$\mathbf{9 5. 0 \% - 9 9. 0 \%}$accuracy, outperforming standard pre-trained models like Visual Geometry Group 16 (VGG-16) with an accuracy of$\mathbf{8 5. 5 \% - 8 8. 0 \%}$. By addressing RIS limitations in NLOS scenarios, this framework offers scalable and highprecision localization solutions for 6G-enabled smart factories.

Channel State Information (CSI) is critical for optimizing wireless communication systems, particularly in Industrial Internet of Things (IIoT) networks where real-time performance and reliability are paramount. In high-density 6G-enabled factory environments, the mobility of subnetworks and dense deployments exacerbate interference, necessitating proactive and efficient resource management. This paper introduces a dual attention-based channel prediction framework, combined with an AI-driven resource allocation model, to mitigate the challenges of outdated CSI in IIoT subnetworks. By employing spatio-temporal attention mechanisms, the proposed framework effectively predicts CSI and integrates sub-band allocation with power control for optimized resource utilization. Simulation results highlight significant gains in spectral efficiency, enhanced Quality of Service (QoS) adherence, and superior robustness to delay, outperforming state-of-the-art methods. These advancements make the proposed solution a scalable and reliable choice for next-generation IIoT deployments.

The forthcoming sixth-generation (6G) Industrial Internet of Things (IIoT) subnetworks are expected to support ultrafast control communication cycles for numerous IoT devices. However, meeting the stringent requirements for low latency and high reliability poses significant challenges, particularly due to signal fading and physical obstructions. In this article, we propose novel time-division multiple access (TDMA) and frequency-division multiple access (FDMA) communication protocols for cooperative transmission in IIoT subnetworks. These protocols leverage secondary access points (sAPs) as decode-and-forward (DF) and amplify-and-forward (AF) relays, enabling shorter cycle times while minimizing overall transmit power. A classification mechanism determines whether the highest gain link for each IoT device is a single-hop or two-hop connection, and selects the corresponding sAP. We then formulate the problem of minimizing transmit power for DF/AF relaying while adhering to the delay and maximum power constraints. In the FDMA case, an additional constraint is introduced for bandwidth allocation to IoT devices during the first and second phases of cooperative transmission. To tackle the nonconvex problem, we employ the sequential parametric convex approximation (SPCA) method. We extend our analysis to a system model with reconfigurable intelligent surfaces (RISs), enabling transmission through direct and RIS-assisted channels, and optimizing for a multi-RIS scenario for comparative analysis. Simulation results show that our cooperative communication approach reduces the emitted power by up to 4.5 dB while maintaining an outage probability and a resource overflow rate below$10^{-6}$. While the RIS-based solution achieves greater power savings, the relay-based protocol outperforms RIS in terms of outage probability.

Subnetworks are expected to enhance wireless pervasiveness for critical applications such as wireless control of plants, however, they are interference-limited due to their extreme density. This paper proposes a goal-oriented joint power and multiple sub-bands allocation policy for interference coordination in 6G in-factory subnetworks. Current methods for interference coordination in subnetworks only focus on optimizing communication metrics, such as the block error rate, without considering the goal of the controlled plants. This oversight often leads to inefficient allocation of the limited radio resources. To address this, we devise a novel decentralized inter-subnetwork interference coordination policy optimized using a Bayesian framework to ensure the long-term stability of the subnetwork-controlled plants. Our results show that the proposed decentralized method can support more than twice the density of subnetwork-controlled plants compared to centralized schemes that aim to minimize the block error rate while reducing execution complexity significantly.

In this paper, we develop a novel power control solution for subnetworks-enabled distributed control systems in factory settings. We propose a channel-independent control-aware (CICA) policy based on the logistic model and learn the parameters using Bayesian optimization with a multi-objective tree-structured Parzen estimator. The objective is to minimize the control cost of the plants, measured as a finite horizon linear quadratic regulator cost. The proposed policy can be executed in a fully distributed manner and does not require cumbersome measurement of channel gain information, hence it is scalable for large-scale deployment of subnetworks for distributed control applications. With extensive numerical simulation and considering different densities of subnetworks, we show that the proposed method can achieve competitive stability performance and high availability for large-scale distributed control plants with limited radio resources.

In this paper, we present an unsupervised approach for frequency sub-band allocation in wireless networks using a graph-based learning method. We consider a scenario of dense deployment of subnetworks in the factory environment. The limited number of sub-bands must be optimally allocated to coordinate inter-subnetwork interference. Traditional iterative solutions may not scale to the large scale and density of subnetwork deployment due to their execution overhead limitations. Hence, we consider a data-driven approach based on graph neural networks. We model the subnetwork deployment as an interference graph and propose an unsupervised learning approach to optimize the sub-band allocation using graph neural networks. This approach is inspired by the graph colouring heuristic and the Potts model. The numerical evaluation shows that the proposed method achieves close performance to the centralized greedy colouring sub-band allocation heuristic with lower computational time complexity. In addition, it incurs reduced signalling overhead compared to iterative optimization heuristics that require all the mutual interfering channel information. We further demonstrate that the method is robust to different network settings.

Wi-Fi is one of the WLANs technologies with the highest penetration in society worldwide. In recent years, Wi-Fi 6E has been defined, which uses the 6 GHz band with higher bandwidth and resource availability. However, the range for this band decreases due to the increase in frequency compared to 2.4 GHz and 5 GHz bands, hence the proposal for the use of mesh networks to overcome the limited range. Therefore, this work empirically assesses the network performance through different setups in indoor scenarios to determine the optimal placement of extender nodes in a Wi-Fi 6E mesh network. The experimental methodology follows a dual approach, studying the channel propagation conditions in the 6 GHz band versus 2.4 GHz and 5 GHz, as well as the throughput reported through connectivity with Wi-Fi 6E. The results quantitatively show the reduction in effective network range in the 6 GHz band, due to the increase in frequency, and its influence on effects such as blocking or around-corner propagation. Based on this analysis, a set of guidelines is developed for positioning the extender nodes in the network to maximize network performance according to the propagation channel conditions.

Industry 4.0 requires wireless solutions to meet the demanding reliability and latency requirements of cyber-physical systems serving many industrial sensors and actuators. The cell-free massive multiple input multiple output (MIMO) paradigm, exploiting both massive MIMO gains and cell-free properties, is expected to play a crucial role in addressing Industry 4.0 communication requirements. However, finding an optimal user association to satisfy the quality of service (QoS) requirements is critical. In this article, we propose a novel centralized probabilistic user association algorithm to identify and maximize the number of served users without relying on short-term channel state information to satisfy the QoS requirements. In larger factories, approximately 90% of the total users are satisfied. However, as the system becomes interference-limited and is expected to meet challenging requirements, the number of served users decreases. Nevertheless, the proposed solution exhibits adaptability in maximizing the number of satisfied users. Simulation results further prove the effectiveness of the proposed solution in terms of achievable spectral efficiency and maximizing the number of satisfied users across varying requirements and factory sizes.

6th Generation (6G) industrial wireless subnetworks are expected to replace wired connectivity for control operation in robots and production modules. Interference management techniques such as centralized power control can improve spectral efficiency in dense deployments of such subnetworks. However, existing solutions for centralized power control may require full channel state information (CSI) of all the desired and interfering links, which may be cumbersome and time-consuming to obtain in dense deployments. This paper presents a novel solution for centralized power control for industrial subnetworks based on Graph Neural Networks (GNNs). The proposed method only requires the subnetwork positioning information, usually known at the central controller, and the knowledge of the desired link channel gain during the execution phase. Simulation results show that our solution achieves similar spectral efficiency as the benchmark schemes requiring full CSI in runtime operations. Also, robustness to changes in the deployment density and environment characteristics with respect to the training phase is verified.

Sixth generation (6G) in-X subnetworks are recently proposed as short-range low-power radio cells for supporting localized extreme wireless connectivity inside entities such as industrial robots, vehicles, and the human body. The deployment of in-X subnetworks in these entities may lead to fast changes in the interference level and hence, varying risks of communication failure. In this paper, we investigate fully distributed resource allocation for interference mitigation in dense deployments of 6G in-X subnetworks. Resource allocation is cast as a multi-agent reinforcement learning problem and agents are trained in a simulated environment to perform channel selection with the goal of maximizing the per-subnetwork rate subject to a target rate constraint for each device. To overcome the slow convergence and performance degradation issues associated with fully distributed learning, we adopt a centralized training procedure involving local training of a deep Q-network (DQN) at a central location with measurements obtained at all subnetworks. The policy is implemented using Double Deep Q-Network (DDQN) due to its ability to enhance training stability and convergence. Performance evaluation results in an in-factory environment indicated that the proposed method can achieve up to 19% rate increase relative to random allocation and is only marginally worse than complex centralized benchmarks.

Future industrial applications will encompass compelling new use cases requiring stringent performance guarantees over multiple key performance indicators, such as reliability, dependability, latency, time synchronization, security, etc. Achieving such stringent and diverse service requirements necessitates the design of aspecial-purpose Industrial-Internet-of-Things (IIoT) networkcomprising a multitude of specialized functionalities and technological enablers. This article proposes an innovative architecture for such a special-purpose sixth generation (6G) IIoT network incorporating seven functional building blocks categorized intospecial-purpose functionalitiesandenabling technologies. The former consists ofWireless Environment Control,Traffic/Channel Prediction,Proactive Resource Management,andEnd-to-End Optimizationfunctions, whereas the latter includesSynchronization and Coordination,Machine Learning and Artificial Intelligence Algorithms, andAuxiliary Functions. The proposed architecture aims at providing a resource-efficient and holistic solution for the complex and dynamically challenging requirements imposed by future 6G industrial use cases. Selected test scenarios are provided and assessed to illustrate cross-functional collaboration and demonstrate the applicability of the proposed architecture in a wireless IIoT network.

This paper investigates efficient deep learning based methods for interference mitigation in independent wireless subnetworks via dynamic allocation of radio resources. Resource allocation is cast as a mapping from interference power measurements at each subnetwork to a class of shared frequency channels. A deep neural network (DNN) is then trained to approximate this mapping using data obtained via application of centralized graph coloring (CGC). The trained network is then deployed at each subnetwork for distributed channel selection. Simulation results in an environment with mobile subnetworks have shown that relatively small-sized DNNs can be trained offline to perform distributed channel allocation. The results also show that regardless of the choice of initialization, a DNN for distributed channel selection can achieve similar performance as CGC up to a probability of loop failure (PLF) of 6 × 10–5in diverse environments with only aggregate interference power measurements as input.

Dense industrial wireless cells have to ensure minimum survival data rates such that the mission critical functionalities can at least be supported regardless of the deployment and interference conditions. In this paper, we propose a novel spectrum allocation mechanism meant to efficiently support minimum survival data rates but without compromising the average network performance. The presented approach is based on a two-phase graph construction and coloring, where cells that are still experiencing mutual interference upon a first frequency allocation are further orthogonalized. Simulation results show that our solution can lead to an increase of up to ~250% of the survival data rates with negligible impact on the average network throughput.

5th Generation (5G) millimeter wave (mmWave) communications rely on directive and narrow beams to circumvent its challenging propagation conditions. Therefore, Medium Access Control (MAC)-based Beam Management (BM) becomes essential to secure adequate beam alignment between the User Equipment (UE) and the Next Generation Node Base Station (gNodeB) beams. For dynamic environments, this can be challenging, potentially compromising control procedures such as Beam Tracking (BT) under the current 5G New Radio (NR) deployments for FR2. This paper presents a sensitivity study on the stability of the gNodeB selected beam - measured by the beam's time-of-stay (ToS) - and the resulting link quality under different operational conditions with respect to UE mobility, propagation environment and operational bands. Results show that the suitability of 5G NR BM procedures can be significantly affected by UE angular speed, channel's angular spread and availability of channel-adaptive BM parametrization.

5G New Radio (NR) technology is expected to enable the wireless transition of manufacturing processes in modern factories. In order to proper dimension the 5G system, accurate models of the data and control traffic in industrial use cases are needed. In this paper, we analyze the industrial traffic empirically measured in different Danish factories and compare its characteristics to the modeling assumptions used in the 3GPP for 5G NR performance analyses. In particular, three relevant use cases are studied: a unit test cell for actuator calibration, a visual inspection cell, and the control of an autonomous mobile robot (AMR). Our results indicate that some of the relevant 3GPP assumptions for industrial traffic such as exponential packet-interarrival time (PIAT) for aperiodic traffic and fixed packet sizes are only partially corroborated by experimental evidence. Moreover, industrial traffic can exhibit a large burstiness that may lead to conservative admission control and radio resource allocation.

Ultra-wideband (UWB) technology offers the potential for unparalleled support of short-range broadband communication over a multi-gigahertz spectrum and are expected to enable several applications with extreme requirements in future wireless networks. Enabling these systems in the unlicensed spectrum requires efficient co-existence management and adequate understanding of the characteristics and spatio-temporal dynamics of interference signals over the multi-GHz bandwidth. This paper investigates the suitability of Gaussian, Middleton canonical class A, symmetric alpha stable and Gaussian Mixture distributions for modelling radio frequency interference from systems in the UWB spectrum based on measurements. We evaluate the closeness of fit of the distributions to measured interference data and provide insights on the applicability of these models for characterizing interference in the UWB spectrum. Results show that the Gaussian Mixture distribution (GMD) yielded the best fit to the measured interference evaluated with Kullback-Leibler (KL) divergence below 0.05. Results also show that interference signals generated from the GMD agree closely with the measurements.

The usage of beamforming in Unmanned Aerial Vehicles (UAVs) has the potential of significantly improving the air-to-ground link quality. This paper presents the outcome of experimental trial of such a UAV-based beamforming system over live cellular networks. A testbed with directional antennas has been built for the experiments. It is shown that beamforming can extend the signal coverage due to antenna gain, as well as spatially reduce interference leading to higher signal quality. Moreover, it has a positive impact on the mobility performance of a flying UAV by reducing handover occurrences. It is also discussed, in which situations beamforming should translate into the uplink throughput gain.

5G networks should support heterogeneous services with an efficient usage of the radio resources, while meeting the distinct requirements of each service class. We consider the problem of multiplexing enhanced mobile broadband (eMBB) traffic, and grant-free ultra-reliable low-latency communications (URLLC) in uplink. Two multiplexing options are considered; either eMBB and grant-free URLLC are transmitted in separate frequency bands to avoid their mutual interference, or both traffic share the available bandwidth leading to overlaying transmissions. This work presents an approach to evaluate the supported loads for URLLC and eMBB in different operation regimes. Minimum mean square error receivers with and without successive interference cancellation (SIC) are considered in Rayleigh fading channels. The outage probability is derived and the achievable transmission rates are obtained based on that. The analysis with 5G new radio assumptions shows that overlaying is mostly beneficial when SIC is employed in medium to high SNR scenarios or, in some cases, with low URLLC load. Otherwise, the use of separate bands supports higher loads for both services simultaneously. Practical insights based on the approach are discussed.

5th generation radio networks should efficiently support services with diverse requirements. For achieving better resource utilization, the sharing of the radio channel between the different services is an attractive solution. While the downlink multiplexing can be well accomplished with dynamic scheduling, efficient multiplexing of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) in uplink is still an open problem. In particular, we consider the case of URLLC using grant-free allocation for sporadic transmissions, multiplexed on shared resources with eMBB with high data volume. Since the moment in which a grant-free transmission occurs is not known, URLLC and eMBB transmissions overlay. Power control settings are then assessed as a way to manage the performance trade-off between the services. Due to the complexity of 5G new radio, the evaluation is based on advanced system level simulations. Insights regarding the configuration of fractional power control settings upon the coexistence of the different services are presented.

Ultra-wide band (UWB) radio systems are expected to operate in co-existence with a myriad of other systems over a large unlicensed bandwidth. Thus, UWB devices need to incorporate efficient inter-system interference mitigation mechanisms. In this paper, we present interference measurements covering the UWB spectrum from 3GHz to 11GHz conducted at two locations (indoor and outdoor) on the campus of Aalborg University, Denmark. We analysed the measurements in terms of occurrence probability, interference power distribution and inter-arrival time statistics. The goal is to understand the characteristics of signals emanating from systems operating on this ultra-wide bandwidth as a basis for the development of models and methods for interference characterization and mitigation. Results indicate that signal activity vary significantly across the spectrum with the 5GHz - 6GHz and 9GHz - 10GHz sub-bands having the strongest power levels in the indoor and outdoor measurements, respectively. Statistical analysis results further show significant variation of the power distribution, occurrence probability and inter- arrival time statistics for the various signals detected in the measurements. Results also show that time between interference occurrence is exponentially distributed for most of the sources.

This work evaluates the concept of uplink beamforming for vehicular communications in the sub-6 GHz frequency bands to improve throughput, latency and coverage of the vehicle to Base Station (BS) link. The data recorded in the experimental measurements using live cellular signals are used to study the performance of two direction acquisition methods: the Angle of Arrival (AoA) estimation and downlink-based beam sweep. Next, the feasibility of signal tracking techniques exploiting the location of the vehicle and the BS are investigated to alleviate the need for continuous direction acquisition. The results show that the downlink-based beam sweep leads to higher Signal to Interference and Noise Ratio (SINR) than beamforming based on the estimated AoA. Evaluated tracking techniques are shown to be capable of correctly estimating the beamforming angle for distances in order of hundreds of meters when BS's location is known to the vehicle.

Cellular Vehicle to Everything (C-V2X) communications with its safety and infotainment services will require a high performance receivers to cope with challenging throughput, latency and reliability requirements. With increasing levels of interference due to cell densification and introduction of the roadside units, single antenna receivers may not be able to provide the required quality of service. In this work we experimentally study the performance of multi antenna receivers based on more than 150 km of data recorded during experiments using a customized software defined radio testbed. The performance of sixteen antennas Maximum Ratio Combiner (MRC) is compared with the receive beamforming technique for the live cellular signals in the 1.8 GHz band. This study is followed by an analysis of the impact of interference and measurement environment on the receiver's performance. The results show that receive beamforming can outperform MRC in low-interfered scenarios with high Line of Sight (LoS) probability, like highways or rural areas, while ensuring comparable performance even in dense urban scenarios where LoS communication cannot be guaranteed.

In the last years, wireless communications in industrial scenarios are becoming an increasingly important market. Some of these communications have tight reliability requirements, but harsh propagation conditions in industrial scenarios represent a major challenge. In this paper, multi-connectivity is explored as a solution for assuring high reliability in industrial scenarios. Several multi-connectivity techniques are compared, using real channel measurements from two factories. Multiconnectivity comes at the cost of a reduced throughput in the mobile broadband services on the same network. In this paper, this impact is quantified to assess for the cost of implementing multi-connectivity.

This paper presents the implementation framework and performance evaluation of a wireless Manufacturing Execution System (MES) for Industry 4.0. The proposed solution is based on self- configuring multi-access gateways that enable seamless transport of delay-tolerant industrial Ethernet control data traffic over LTE or Wi-Fi (or both, using hybrid-access techniques). The wireless MES solution has been deployed at the Smart Production Lab facilities at Aalborg University, allowing the removal of Ethernet cables between modules in a production line setup, and thus enabling a faster re-configuration of the production facilities. The performance of the wireless MES solution is benchmarked against the reference Ethernet case in terms of latency and packet loss. The trials revealed that, despite the increase in latency and packet loss as compared to the reference operation over Ethernet, both LTE and Wi-Fi under different conditions were able to reliably support the production control operations at MES level without discernable difference on the overall functionality of the system.

This paper presents the results of wireless channel measurement campaign in the 3 GHz to 8 GHz frequency range. The measurements were performed with focus on the short-range with a transmitter-receiver separation distance less than 9 m in two typical industrial environments: a low clutter density manufacturing space, and a high clutter density one. We analyzed the statistical properties of the most important temporal and large-scale propagation characteristics including total received energy, path loss exponent, maximum excess delay (MED) and root mean square (RMS) delay spread based on the measurements. Statistical models for the RMS delay spread and MED are also presented using the log-normal and Gamma distributions.

In this paper, we discuss the achievable transmission rates over collision-prone radio resources shared by a number of devices, representative of novel Internet-of-Things (IoT) scenarios. We consider Maximum Ratio Combining (MRC) and Minimum Mean Square Error (MMSE) receivers at the base station, and derive the relationship between target failure probability and saturation rate, which represents the maximum achievable rate over shared resources in the interference limited regime. MRC receiver is shown to be sensitive to the presence of statistically relevant interferers operating over the same resources, rapidly leading to rate saturation. The MMSE receiver adds a tier of protection to collisions thanks to its interference suppression capabilities, suffering for a rate penalty only in case of a high number of users. A realistic system analysis in an indoor hotspot scenario validates the analytical trends and suggests insights on practical link adaptation strategies.

This work is related to 5G new radio concept design, with focus on ultra-reliable and low latency communication (URLLC) use cases. We mainly target to achieve the stringent latency and reliability requirements for transmissions over the air interface, such as 99.999% success probability within 1 ms. Meeting these requirements in an efficient way, that is, without draining the network capacity is one of the main challenges for the new radio standardization. In this work, we propose a scheme to perform blind retransmissions on shared radio resources together with the application of successive interference cancellation to receive remaining non-decoded data with low delay penalty. The method avoids control errors and extra delays existent on feedback-based retransmission schemes. The investigations also show that blind retransmission on shared resources is more resource efficient than a conservative single shot transmission, depending on the number of users sharing the resources.

One of the 5G use cases, known as ultra- reliable communication (URC), is expected to support very low packet error rate on the order of $10^{-5}$ with a 1 ms latency. In an industrial scenario, this would make possible replacing wired connections with wireless for controlling critical processes. Industrial environments with large metallic machinery and concrete structures can lead to deep shadowing and severe fading in the radio propagation channel, and thus pose a challenge for achieving the outage levels in connection with URC. In this paper, we present and analyze the large-scale propagation characteristics of two different industrial environments - open production space and dense factory clutter - based on measurements conducted at 2.3 and 5.7 GHz. By including a large number of spatially distributed samples, as per our experimental approach, we show the importance of properly characterizing the large-scale fading outage for URC. For instance, we show that based on a simple one-slope distance dependent path loss model, the conventional log-normal model for large-scale shadow fading is by far too simple for this environment. Our results show that at the 10^{-4} percentile, the tail of the shadow fading distribution can deviate by up to 10-20 dB from the log-normal model with respect to the average NLOS values (around 6 dB and 8 dB at 2.3 and 5.7 GHz, respectively). The simplicity of the one-slope path loss model, and its ability as we show, to express the trends with respect to scenarios, frequencies, and antenna heights, makes it an attractable option. However, there is a need for further experimental insight, possibly in combination with deterministic analysis, to get a better understanding of the large-scale fading for the study of URC in industrial environments.

Ultra-reliable and low latency communication (URLLC) presents the most challenging use cases for fifth generation (5G) mobile networks. Traditionally the focus for mobile broadband has been to optimize the system throughput for high speed data traffic. However the optimization criteria for URLLC should focus on achieving small packets transmissions under strict targets such as 99.999% reliability within 1 ms. Power control is one candidate technology component for improving reliability and latency. In this work we investigate the power control for grant-free URLLC transmissions through extensive system level simulations in a urban outdoor scenario. We initially compare different settings for open loop power control (OLPC) with full and with fractional path loss compensation. Then we evaluate whether power boosting the retransmission can reduce the probability of packets delays under the 1 ms constraint. We also discuss the practical implication of applying power boosting. With full path loss compensation and boosting retransmissions, we show that a URLLC load such as 1200 small packets per second per cell can be achieved in the considered scenario.

Full duplex communication promises system performance improvement over conventional half duplex communication by allowing simultaneous transmission and reception. However, such concurrent communication results in strong self interference and an increase in the overall network interference, and can only be exploited when traffic is available in both directions. The potential throughput gains of full duplex communication over conventional half duplex transmission in a small cell network with asymmetric traffic conditions is investigated in this contribution. The throughput performance gains are analysed using tools from stochastic geometry, and further confirmed through extensive system level simulations. Our findings explicitly quantify how the gains from full duplex communication depend on the traffic profile and the inter-cell interference coupling. The demonstrated throughput gains and delay reduction make full duplex communication an attractive potential technology component for the fifth generation dense small cell cellular system.

Unique Word Discrete Fourier Transform -spread - Orthogonal Frequency Division Multiplexing (UW DFT-s-OFDM) waveform replaces the Cyclic Prefix (CP) with a known sequence which is contained in the symbol itself rather than being appended to it. In this paper, we propose a new UW DFT-s-OFDM design which aims at exploiting such known sequence at the tail of the signal for tracking the variations of the radio channels on a symbol basis, thus overcoming the limited flexibility of DFT-s-OFDM waveforms in multiplexing reference sequences and data. Further, we also present a criterion for efficiently selecting the reference sequences to be adopted by users experiencing fast time-varying channel conditions. Initial simulation results show the capability of the proposed design of improving the link performance of high speed users, even without additional overhead.

Big expectations are put into vehicular communications (V2X) for a safer and more intelligent driving. With human lives at risk, the system cannot afford to fail, which translates into very stringent reliability and latency requirements to the radio network. One of the challenges is to find efficient radio resource management (RRM) strategies for direct vehicle-to-vehicle (V2V) communication that can fulfil the requirements even with high traffic density. In cellular networks, a device-to-device (D2D) communication is usually split into two phases: the discovery process, for node awareness of each other; and the communication phase itself, where data exchange takes place. In the case of V2V, the discovery phase can utilize the status information that cars broadcast periodically as the beacons to detect the presence of neighbouring cars. For the delivery of specific messages (e.g., a hazardous event), direct communications can then be set up in a very fast way, based on the previously collected information. Several aspects have been revealed as essential to ensure the reliability and latency requirements of the discovery, such as the autonomous selection of the resources, the duplexing mode and the interference cancellation receivers

Besides coping with the increasing demand of broadband services, 5th Generation (5G) radio access technology is expected to support mission critical communication (MCC) services targeting very low latencies. In this paper, we investigate the feasibility of the usage of an early Hybrid Automatic Repeat reQuest (HARQ) feedback for reducing the latency of acknowledged transmissions without disregaring spectral efficiency. As enabler of such early feedback, a new technique for predicting the decoder outcome before decoding occurs, is proposed. This technique is intended to generate an early ACK/NACK, or an uncertain feedback in case a reliable prediction cannot be achieved. Simulation results show a very limited occurrence of false positives and false negatives, and uncertain feedback rates not exceeding 6% when adaptive modulation and coding (AMC) and a 10% Block Error Rate (BLER) target is assumed. A correct early ACK/NACK can be generated for around 90% of the transmissions or more.

Achieving the trade-off between coverage, ultra-low latency and capacity is a major challenge for a 5th Generation (5G) wide area concept, especially when operating in Time Division Duplex (TDD) mode. In this paper, we focus on the design of the Guard Period (GP) which is needed to accommodate the transition between downlink (DL) and uplink (UL) transmissions in a 5G TDD wide area system operating at below 6 GHz carrier frequencies. The necessity of serving cell edge users with long propagation delays while coping with latency constraints may lead to a large GP overhead, thus reducing the resource utilization in the cell. We propose a distance-dependent scheduling technique which is meant at reducing the GP overhead while ensuring sufficient coverage. Numerical analysis shows the benefits of the proposed techniques in terms of available radio resources, especially for very large cells operating with short frames.

Full duplex transmission is envisioned as one of the potential breakthrough for a 5th Generation (5G) radio access technology. In this paper, we evaluate the performance of full duplex transmission in a network of dense small cells by using real channel measurements. A large measurement campaign is carried out in an indoor office and an open hall scenario, and such measurements are then fed to a system level simulator for offline analysis. Cell throughput results show that the promised 100% performance gain of full duplex over traditional half duplex transmission is significantly jeopardized by the increase of the intercell interference due to the simultaneous transmission and reception, and is further reduced in case of low cell activity factor.

It is generally recognized that efficient multiplexing of users with highly diverse requirements needs a flexible frame structure. For a new 5th generation mobile networks (5G) air interface, the hybrid automatic repeat request (HARQ) solution should also be revised to harvest all possible performance benefits that can be obtained with a flexible frame structure. In this paper, we outline a number of HARQ enhancements and design principles for a 5G wide area solution. This includes a flexible asynchronous HARQ scheme with options for dedicated per-link configurations of feedback timing and multi-bit richness. Among others, the proposed solution supports asymmetric link operation, network implementations with different fronthaul latencies, and multi-bit feedback to facilitate variable block length HARQ retransmissions for improved resource utilization. Numerical results are presented for different link configurations.

In addition to higher data rates and lower latency the 5G Radio Access Technology concepts are targeting to provide better battery life for mobile broadband and Machine Type Communication users. In this overview paper we analyze how microsleep, Discontinuous Reception and Transmission, and a wake-up receiver concept can be combined to enhance the battery life of 5G mobile terminals. Due to the short and pipelined 5G frame structure microsleep provides 20 % energy savings as compared to LTE. The Discontinuous Reception and Transmission modes also benefit from the new frame structure leading to faster connection setup and up to 80 % lower energy consumption depending on the traffic type. Finally we estimate that the wake-up receiver concept, when adapted to scheduled and cellular communication, can provide 90 % lower energy consumption and ensure a predictable and consistent latency.

Research in 5G has so far been aimed towards laying out a conceptual vision and the engineering requirements. The focus is now shifting towards standardization through evaluation of potential solutions. 5G wireless communication system is expected to serve a diverse range of services with different design requirements. Dense small cells with multiple antenna nodes are believed to be key elements in meeting these challenging requirements. 5G will thus feature an adaptable air interface with carefully designed radio resource management techniques that can optimize each link according to its service requirements. This article provides an overview of key radio resource management techniques for 5G dense small cells and demonstrates how these techniques can contribute to fulfilling some of the important 5G requirements. Preliminary system level simulation results indicate that a mean throughput gain of around 63 %, and up to 84 % in latency reduction can be achieved utilizing the discussed resource management techniques.

In this paper we present a novel configurable 5G time division duplex (TDD) frame structure, including a flexible scheduling (resource allocation) framework for wide area scenarios. The unavoidable tradeoffs between coverage, latency, and capacity are studied with the objective of deriving a 5G air interface solution that is capable of serving users with highly diverse service requirements. Among others, it is shown that coverage challenged users will experience larger latency, while other users can still be served with shorter latency if adopting the proposed 5G solution. Achieving low latency, does, however, come at cost of lower spectral efficiency, so our solution includes control mechanisms for determining on a per user basis if the link shall be optimized for latency or capacity.

Given the recent advances in system and antenna design, practical implementation of full duplex (FD) communication is becoming increasingly feasible. In this paper, the potential of FD in enhancing the performance of 5thgeneration (5G) ultra-dense small cell networks is investigated. The goal is to understand whether FD is able to boost the system performance from a throughput and delay perspective. The impact of having symmetric and asymmetric finite buffer traffic is studied for two types of FD: when only the base station is FD capable, and when both the user equipment and base station are FD nodes. System level results indicate that there is a trade- off between multiple-input multiple-output (MIMO) spatial multiplexing and FD in achieving the optimal system performance. Moreover, results show that FD may be useful for asymmetric traffic applications where the lightly loaded link requires high level performance. In such cases, FD can provide an average improvement of up to 116% in session throughput and 77% in packet delay compared to conventional half duplex transmissions.

Full duplex (FD) communication has attracted the attention of the industry and the academia as an important feature in the design of the future 5th generation (5G) wireless communication system. Such technology allows a device to simultaneously transmit and receive in the same frequency band, with the potential of providing higher throughput and lower latency compared to traditional half duplex (HD) systems. In this paper, the interaction between Transport Control Protocol (TCP) and FD in 5G ultra- dense small cell networks is studied. TCP is a well- known transport layer protocol for providing reliability, which comes at the price of increased delay and reduced system throughput. FD is expected to accelerate the TCP congestion control mechanism and hence mitigate such consequences. System level results show that FD can outperform HD and alleviate the TCP drawbacks when the inter-cell interference is not the main limiting factor. On the other hand, under strong inter-cell interference, results show that the capabilities of the system to cope with such interference dictates the gain that FD may provide over HD.

Zero-tail Discrete Fourier Transform-spread OFDM (ZT DFT-s-OFDM) modulation replaces the Cyclic Prefix (CP) with a low power tail whose length can be dynamically configured to cope with the instantaneous delay spread of the channel. In this paper, we discuss the reference sequence design for ZT DFT-s-OFDM. Our proposed approach is based on a deliberate distortion of the known Zadoff-Chu (ZC) sequences aiming at adapting them to the ZT DFT-s-OFDM waveform while preserving their attractive properties. A numerical analysis confirms the validity of our design in generating ZT DFT-s-OFDM reference sequences with zero autocorrelation, limited cross-correlation, flat frequency response and low Peak-to-Average Power Ratio (PAPR).

Full duplex communication promises a theoretical 100% throughput gain by doubling the number of simultaneous transmissions. Such compelling gains are conditioned on perfect cancellation of the self interference power resulting from simultaneous transmission and reception. Generally, self interference power is modelled as a noise-like constant level interference floor. However, experimental validations have shown that the self interference power is in practice a random variable depending on a number of factors such as the surrounding wireless environment and the degree of interference cancellation. In this study, we derive an analytical model for the residual self interference power, and demonstrate various applications of the derived model in analysing the performance of a Full Duplex radio. In general, full duplex communication is found to provide only modest throughput gains over half duplex communication in a dense network scenario with practical self interference cancellation models.

The further densification of small cells impose high and undesirable levels of inter-cell interference. Multiple Input Multiple Output (MIMO) systems along with advanced receiver techniques provide us with extra degrees of freedom to combat such a problem. With such tools, rank adaptation algorithms allow us to use our antenna resources to either exploit multiple spatial streams in low interference scenarios, or suppress interference in high interference scenarios. In this paper, we propose and evaluate an interference-aware distributed rank adaptation algorithm. The concept behind our approach is to discourage the choice of transmitting with multiple spatial streams in highly interfered scenarios, and to exploit and encourage the usage of multiple spatial transmission streams in low interference scenarios. We show that our proposed algorithm can be adjusted to preserve and guarantee a good outage performance, while providing the benefit of higher average throughputs, in both low and highly interfered scenarios, when compared to fixed rank configurations, and distributed selfish schemes.

Time division duplex (TDD) systems offer a substantial amount of freedom to deal with downlink (DL) and uplink (UL) traffic asymmetries. Most TDD-based systems define either multiple static configurations or adaptive approaches to deal with such asymmetries. Our envisioned 5G concept embraces the flexibility brought along by TDD, and allows us to switch the link direction on a slot by slot basis. In this paper we study the interaction of Transmission Control Protocol (TCP) traffic, with a fully flexible UL/DL TDD allocation scheme. We show that flexibility is not only beneficial for exploiting the different instantaneous UL and DL traffic variations, but also performs well with TCP traffic, where the protocol behaviour plays an important role in throughput performance. The advantages of full flexibility compared to fixed static allocations for TCP traffic are reported for both small and large payloads, and for multi-cell scenarios where both DL and UL traffic are present.

Full duplex communication promises a 100% throughput gain by doubling the number of simultaneous transmissions. In a multi-cell scenario, increasing the number of simultaneous transmissions correspondingly increases the number of interference streams observed at a particular receiver. As such, the potential throughput gain may not be 100% as promised. In this study, we evaluate the performance of full duplex communication in a dense small cell scenario as targeted by future 5th Generation (5G) radio access technology under the ideal assumptions of a full buffer, always active traffic model and perfect self interference cancellation. Advanced interference suppression/cancellation receivers are featured as well. Full duplex communication is found to provide about 30-40% mean throughput gain over half duplex transmissions for indoor scenarios, which provides an indication of the maximum throughput gains that can be achieved with full duplex communication in indoor scenarios under such idealized assumptions.

In this paper we present a 5G frame structure designed for efficient support of users with highly diverse service requirements, including mobile broadband (MBB) data, mission critical communication (MCC), and massive machine communication (MMC). The proposed solution encompasses flexible multiplexing of users on a shared channel with dynamic adjustment of the transmission time interval (TTI) in coherence with the service requirements per link. This allows optimization of the fundamental trade-offs between spectral efficiency, latency, and reliability for each link. The frame structure is based on in-resource physical layer control signaling that follows the corresponding data transmission for each individual user. The principle of in-resource control signaling has numerous advantages; it presents a highly flexible and scalable solution, it allows joint beamforming for control and data transmission, as well as efficient time-frequency inter-cell interference coordination. Numerical results are presented, including simple comparison against LTE.

Full duplex (FD) communication promise of doubling the throughput of half duplex (HD) communication makes such type of system an attractive solution to cope with the expected mobile data traffic increase. Nevertheless, simultaneous transmission and reception in dense deployment scenarios increases the inter- cell interference compared to a traditional HD communication, due to a larger number of nodes simultaneously transmitting. Moreover, FD communication can only be exploited when there is traffic in both uplink and downlink directions simultaneously. In this paper, FD communication is studied within the framework of 5th generation (5G) small cell systems in order to address its effective gain in such specific scenarios. The factors that affect FD performance are analysed, and its performance is evaluated against a traditional HD communication. System level simulations show that the gain of FD over HD in the considered scenarios is lower than the expected 100% gain, with a strong dependency on the traffic and the interference conditions.

Advanced receivers are a key component of the 5th Generation (5G) ultra-dense small cells concept given their capability of efficiently dealing with the ever-increasing problem of inter-cell interference. In this paper, we evaluate the potential of interference suppression receivers in real network scenarios using a software defined radio (SDR) testbed. The experimentation is carried out in an indoor office and open hall scenarios. In particular, we study to what extent the interference suppression receiver is an alternative to traditional frequency reuse techniques. To this end we evaluate the Interference Rejection Combining (IRC) and Successive Interference Cancellation (SIC) receivers and different rank adaptation approaches. Each node in our software defined radio (SDR) testbed features a 2×2 MIMO transceiver built with the USRP N200 hardware by Ettus Research. Our experimental results confirm that interference suppression receivers can be a valid alternative to frequency reuse, by achieving nearly the same outage and higher peak throughput performance.

Inter-cell interference is the main performance limiting factor in the dense deployment of small cells targeted by the upcoming 5th Generation (5G) radio access technology. In this paper, we present an experimental evaluation of inter-cell interference mitigation techniques in a real indoor office deployment with four cells, where each cell features one Access Point (AP) and one User Equipment (UE). In particular, we compare traditional Frequency Reuse Planning (FRP) with the recently proposed Maximum Rank Planning (MRP) technique, which relies on the degrees of freedom offered by the multi-antenna transceivers for suppressing a number of interfering streams. Different receiver types are also considered, namely Interference Rejection Combining (IRC) and the interference unaware Maximum Ratio Combining (MRC). Each node in our software defined radio (SDR) testbed features a 2 x 2 MIMO transceiver built with the USRP N200 hardware by Ettus Research. The experimental results in a fully loaded network reveal the capability of the MRP technique to achieve higher throughput performance than FRP for 90% of the cases when IRC receivers are used. Lower network loads lead to further performance improvements for MRP.

The Interference Rejection Combining (IRC) receiver can significantly boost the network throughput in scenarios characterized by dense uncoordinated deployment of small cells, as targeted by future 5th generation (5G) radio access technology. This paper presents an experimental study on the potential benefit of IRC receiver in real deployment scenarios. The study is carried out using a software defined radio (SDR) testbed network with four cells, each featuring one Access Point (AP) and one User Equipment (UE) with two antennas. The testbed network was placed in an indoor office and open hall scenarios, respectively. In each scenario, the cells were arranged to characterize the propagation in different spatial configurations. Using the obtained propagation data, we analysed the cases of closed and open subscriber group for the respective scenarios, to compare the achievable throughput with IRC and Maximum Ratio Combining (MRC) receivers. Different frequency reuse schemes were also considered. The throughput results confirm the effectiveness of the IRC receiver in improving the network throughput with respect to the MRC receiver, under the assumption of single stream (rank 1) transmission. Results show average gains up to around 40% and outage gains up to 70% over the MRC receiver. The combination of the IRC receiver and frequency reuse achieves a favourable trade-off between the network throughput and fairness. Overall, due to the direct propagation, the open hall open subscriber group scenario is benefiting the most from the ability of the IRC receiver to cancel a strong dominant interferer.

The ideal radio waveform for an upcoming 5th Generation (5G) radio access technology should cope with a set of requirements such as limited complexity, good time/frequency localization and simple extension to multi-antenna technologies. This paper discusses the suitability of Orthogonal Frequency Division Multiplexing (OFDM) and its recently proposed enhancements as 5G waveforms, mainly focusing on their capability to cope with our requirements. Significant focus is given to the novel zero-tail paradigm, which allows boosting the OFDM flexibility while circumventing demerits such as poor spectral containment and sensitivity to hardware impairments.

Zero-tail Discrete Fourier Transform -spread OFDM (ZT DFT-s-OFDM) modulation allows to dynamically cope with the delay spread of the multipath channel, thus avoiding the limitations of hard-coded Cyclic Prefix (CP). In this paper, we discuss the potential of ZT DFT-s-OFDM modulation for the envisioned 5th generation (5G) radio access technology, characterized by an ultra-dense deployment of small cells and the support of novel paradigms such as Device-to-Device (D2D). We address the benefits of ZT DFT-s-OFDM in terms of coexistence among devices operating over adjacent frequency chunks, possibility of adopting unified radio numerology among different cells, reduced latency and support of agile link direction switching. The robustness of ZT DFT-s-OFDM towards non-idealities such as phase noise and non-linear power amplifier is also discussed.

Time synchronization in a large network of small cells enables efficient interference management as well as advanced transmission techniques which can boost the network throughput. In this paper, we focus on the distributed initial synchronization problem and propose different solutions aiming at reducing the residual asynchronous interference while limiting the number of large timing reconfigurations at each node. Simulation results show the effectiveness of an ID-based approach in limiting the asynchronous interference, however at the expense of a potential high number of timing reconfigurations. A pathlossbased solution limits such reconfigurations but also leads to a higher residual interference than the ID-based solution. An hybrid solution is shown to be an effective trade-off between the two former approaches.

5th Generation (5G) small cells are expected to satisfy the increasing demand for wireless data traffic. In the presence of large scale dense and randomly deployed cells, autonomous and distributed configuration mechanisms are highly desirable. However, small cells typically serve a small number of users, such that sudden traffic imbalances between downlink (DL) and uplink (UL) are expected in the new 5G system. We exploit the flexibility of time-division duplex (TDD) to deal with such imbalances by adapting swiftly to instantaneously varying traffic needs. In this paper we propose a distributed algorithm to deal with these varying traffic requirements. We also exploit the availability of interference rejection capable receivers. Simulation results show that in the presence of the aforementioned features, we can approximately double the session throughput and halve the packet delay in a large number of cases.

Research on fifth generation (5G) radio access technology (RAT) is ramping up, with the goal of significantly improving user data rates and latency compared to previous RAT generations. While energy efficiency (EE) of the user equipment (UE) was not a key optimization parameter for the current wireless standards, it is anticipated to become a distinguishing factor for 5G. In this paper, we analyze established and emerging technological solutions for features such as waveform, frame structure, duplexing and multiple antenna transmission from an EE perspective. Our contribution is to identify and discuss the features' pros and cons in achieving high performance in terms of data rate and/or latency while limiting their effect on the UE power consumption. Based on the discussion we give general recommendations for an energy efficient 5G design in the context of a previously proposed RAT concept.

Multiple transmit and receive antennas introduce additional degrees of freedom, which can be used to increase the number of spatial channels between a transmitter-receiver pair. Alternately, the additional degrees of freedom can be used to improve the interference resilience property with the help of linear interference rejection combining (IRC) receivers. Typically, rank adaptation algorithms are aimed at balancing the trade-off between increasing the spatial gain, and improving the interference resilience property. In this paper, we propose an efficient and computationally effective rank adaptation algorithm based on an estimate of the mean signal-to-interference-plus- noise ratio (SINR) at an IRC receiver; wherein, we use results from random matrix theory to derive the expression for the mean post-IRC SINR in the presence of interferers with unequal powers. The performance of the proposed algorithm is analysed through system level simulations. The results are found to be comparable to the optimum performance, and match closely to that of a more complex existing rank adaptation method.

Ultra-dense small cells are foreseen to play an essential role in the 5th generation (5G) of mobile radio access technology, which will be operating over different bands with respect to established systems. The natural step for exploring new spectrum is to look into the centimeter-wave bands as well as exploring millimeter-wave bands. This paper presents our vision on the technology components for a 5G centimeter-wave concept for ultra-dense small cells. Fundamental features such as optimized short frame structure, multi-antenna technologies, interference rejection, rank adaptation and dynamic scheduling of uplink/downlink transmission are discussed, along with the design of a novel flexible waveform and energy-saving enablers.

The usage of Minimum Mean Square Error - Interference Rejection Combining (MMSE-IRC) receivers is expected to be a significant performance booster in the ultra-dense deployment of small cells envisioned by an upcoming 5th generation (5G) Radio Access Technology (RAT). However, hardware limitations of the radio- frequency front-end and poor covariance matrix estimation may severely compromise its ideal gains. In this paper, we evaluate the network performance of MMSE-IRC receivers by including the effects of the receiver imperfections as well as realistic covariance matrix estimates. System level simulation results confirm that a realistic MMSE-IRC receiver can achieve throughput gains close to ideal, provided a reasonably high resolution Analog-to-Digital Converter (ADC) as well as a supportive radio frame format design are used.

The characteristics of the deployment scenario are fundamental elements in the performance evaluation of wireless networks inter-cell interference coordination (ICIC) schemes. The statistical validation of such concepts is typically achieved by means of system-level simulation campaigns where regular reference scenarios and stochastic channel models are employed. It is an important next step to verify that the trends observed in the reference scenarios compare equally well in more practical deployments. For such comparison, it is required to evaluate an extensive set of link conditions, reflecting the many possible configurations that can be experienced in a practical scenario. In this paper we adopt an experimental procedure, using a software defined radio testbed, for acquiring almost 1000 different radio link conditions between the nodes of a relevant wireless indoor network scenario. The acquired measurements, were used as input to a system level simulator in order to evaluate the performance of a local area decentralized ICIC scheme. The obtained performance results highlight the contribution of the selected scheme and provide a new insight for the validation of the related simulation-based studies, previously published in literature.

Beyond 4th Generation (B4G) local area networks will be characterized by the dense uncoordinated deployment of small cells. This paper shows that inter-cell interference, which is a main limiting factor in such networks, can be effectively contained using Interference Rejection Combining (IRC). By simulation we investigate two significantly different interference scenarios with dense small cell deployment. The results show that IRC brings considerable improvement in outage as well as in peak and median throughputs in both scenarios, and thus has a big potential as a capacity and coverage enhancing technique for B4G. The IRC gain mechanism depends strongly on the interference scenario and to some extent on the use of frequency reuse. These results are achieved with no coordination between cells and suggests that MIMO rank adaptation and IRC can be done independently.

Next generation wireless networks aim at a significant improvement of the spectral efficiency in order to meet the dramatic increase in data service demand. In local area scenarios user- deployed base stations are expected to take place, thus making the centralized planning of frequency resources among the cells, a non-viable solution. Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) are the research paradigms which are expected to provide the network nodes the capabilities for an autonomous and efficient selection of the spectrum resources. In this paper we present the first experimental activities with the Autonomous Component Carrier Selection (ACCS) algorithm, a distributed solution for interference management among small neighboring cells. A preliminary evaluation of the algorithm performance is provided considering its live execution on a software defined radio network testbed. The obtained experimental results confirm the performance trends obtained from prior simulation studies. The analysis in dynamic environment conditions also allowed identifying the utilization of static thresholds in the decision making process, as a critical aspect for the optimization of network capacity.

The ambitious data rate target of the Long Term Evolution - Advanced (LTE-A) systems, which are currently being standardized by the 3rd Generation Partnership Project (3GPP), can only be achieved by using advanced Multiple Input Multiple Output (MIMO) antenna techniques on both uplink and downlink. In this paper, the focus is on LTE-A uplink and we discuss the suitability of two options for the closed loop precoded MIMO transmission. The first option is to use the same codebook of precoding matrices defined for LTE downlink, while the second option exploits the Singular Value Decomposition (SVD) of the channel matrix, which could theoretically achieve the MIMO capacity. Qualitative benefits of both solutions are discussed. Link level simulation results show that, the SVD-based approach only lead to a poor performance gain in terms of spectral efficiency over the LTE downlink codebook because of the losses due to the quantization of the right singular vectors of the channel matrix. Since SVD-based solution doesn't even exploit some useful properties (e.g., power balance over the antennas) which LTE Release 8 codebook offers, the latter results to be a better candidate for the closed loop MIMO transmission in LTE-A uplink.

A multiple component carrier (CC) solution has been agreed as the underlying structure of the Long Term Evolution - Advanced (LTE-A) systems, which are currently being standardized by the 3rd Generation Partnership Project (3GPP). In this deployment, the bundling of Modulation and Coding Scheme (MCS) and Hybrid Automatic Repeat Request (HARQ) parameters across multiple CCs is foreseen to maintain the feedback signaling comparable with the one of the previous LTE Release 8. This paper focuses on the transmission over multiple CCs in LTE-A Uplink. Issues related to the bundling of the link level parameters is discussed and a simple Codeword (CW) mixing strategy is proposed to boost the spectral efficiency performance while keeping low feedback overhead. Results show that, combined HARQ/MCS bundling can achieve the same performance of HARQ only bundling when used together with our proposed CW mixing strategy, with the advantage of a lower feedback overhead. CW mixing also leads to similar spectral efficiency when the bundling is performed over 2 and 3 CCs. The use of a turbo Successive Interference Cancellation (turbo SIC) receiver further improves the spectral efficiency, especially when antenna gain imbalance (AGI) occurs.

The paper deals with turbo detection techniques for Single User Multiple-Input-Multiple-Output (SU MIMO) antenna schemes. The context is on the uplink of the upcoming Long Term Evolution - Advanced (LTE-A) systems. Iterative approaches based on Parallel Interference Cancellation (PIC) and Successive Interference Cancellation (SIC) are investigated, and a low-complexity solution allowing to combine interstream interference cancellation and noise enhancement reduction is proposed. Performance is evaluated for Orthogonal Frequency Division Multiplexing (OFDM) and Single Carrier Frequency Division Multiplexing (SC-FDM) as candidate uplink modulation schemes for LTE-A. Simulation results show that, in a 2times2 antenna configuration, the turbo processing allows a consistent improvement of the link performance, being SC-FDM the one having higher relative gain with respect to linear detection. The turbo receiver's impact is however much reduced for both modulation schemes in a 2times4 configuration, due to the higher diversity gain provided by the additional receive antennas.

The 3rd generation partnership project (3GPP) defined the requirements for the upcoming long term evolution advanced (LTE-A) systems, aiming at peak spectral efficiencies of 30 bit/s/Hz in the downlink and 15 bits/s/Hz in the uplink. These ambitious targets can be accomplished only by using advanced multiple input multiple output (MIMO) antenna techniques. In this paper, we evaluate closed loop precoded multirank transmission for single carrier frequency division multiplexing (SC-FDM) as selected uplink modulation scheme by using the precoding codebook defined for LTE downlink. Its performance is compared with orthogonal frequency division multiplexing (OFDM). Results show that OFDM outperforms SC-FDM for medium-high ranks, but the gap can be reduced by adding further diversity branches. While narrowband precoding shows considerable gain over open loop transmission for all ranks, wideband precoding works with a very small feedback overhead but results to be a valid option mainly for low-rank transmission, where the low peak-to-average power ratio (PAPR) of SC-FDM signals is also preserved.

Single-carrier frequency division multiple access (SC-FDMA) has been selected as the uplink access scheme in the UTRA Long Term Evolution (LTE) due to its low peak-to-average power ratio properties compared to orthogonal frequency division multiple access. Nevertheless, in order to achieve such a benefit, it requires a localized allocation of the resource blocks, which naturally imposes a severe constraint on the scheduler design. In this paper, three new channel-aware scheduling algorithms for SC-FDMA are proposed and evaluated in both local and wide area scenarios. Whereas the first maximum expansion (FME) and the recursive maximum expansion (RME) are relative simple solutions to the above-mentioned problem, the minimum area-difference to the envelope (MADE) is a more computational expensive approach, which, on the other hand, performs closer to the optimal combinatorial solution. Simulation results show that adopting a proportional fair metric all the proposed algorithms quickly reach a high level of data-rate fairness. At the same time, they definitely outperform the Round-Robin scheduling in terms of cell spectral efficiency with gains up to 68.8% in wide area environments.

Turbo equalization is known as an advanced iterative equalization and decoding technique that allows to enhance the performance of the data transmission over a frequency selective fading channel. The turbo equalizer will result in extra receiver complexity, but isolated to the base-station, which does not have stringent power constraints. In this paper, a turbo equalization technique to improve Single Carrier Frequency Division Multiple Access (SC-FDMA) performance is proposed. A new adaptive coefficients solution for frequency domain equalization is considered. The work is in the context of UTRA Long Term Evolution (LTE) Uplink. The performance is evaluated for 1x2 Single Input Multiple Output (SIMO) antenna configuration in a 6 paths Typical Urban (TU-06) channel profile. For assessment purpose, the results are compared with SC-FDMA MMSE and OFDMA schemes. Simulation results show that the turbo equalizer can improve the BLER performance around 1 dB with only a few iterations, and improve the SC-FDMA performance over OFDM, especially at high coding rate.