Federated fine-tuning of pre-trained Large Language Models (LLMs) enables task-specific adaptation across diverse datasets while preserving privacy. However, challenges such as high computational and memory demands, heterogeneous client resources, bandwidth constraints, and ineffective global aggregation hinder its efficiency. To address these issues, we propose HAFLQ (Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization), featuring four technical innovations. First, a salience-driven adaptive quantization scheme ranks transformer blocks by Hessian-based importance scores, applying block-wise quantization (e.g., INT8 for low-salience blocks, FP32 for critical ones) tailored to each client’s GPU capacity. Second, an importance-based parameter management mechanism enables clients with limited resources to selectively freeze low-importance LoRA rank-1 matrices (identified via gradient-sensitivity metrics) while training only critical ones, avoiding truncation-induced performance loss. Third, bandwidth-adaptive communication quantization allocates higher precision (32/16-bit) to important parameters and lower precision (8/4-bit) to less critical ones based on wireless channel conditions, prioritizing transmission of high-impact rank-1 matrices. Fourth, adaptive rank-1 matrix-level aggregation weights client contributions by Frobenius norm and aggregates only updated matrices, preventing information dilution from zero-padding approaches. Experiments on text classification tasks show that HAFLQ outperforms existing heterogeneous federated learning baselines in convergence speed and accuracy under bandwidth-sufficient conditions. Under bandwidth-constrained scenarios, HAFLQ reduces memory usage by 31% via adaptive LLM quantization and communication cost by 49% via adaptive communication quantization, while the complete framework achieves 50% relative accuracy improvement over the zero-padding aggregation baseline (from 59% to 89%).

The Open Radio Access Network (Open RAN) vision is based on the three principles of (i) open interfaces; (ii) cloudification; and (iii) automation through closed-loop control. It is a network architecture paradigm embodied and augmented through technical reference specifications of the 3GPP and the O-RAN Alliance. At the centre of Open RAN are open, programmable, and virtualized components, connected to each other through open interfaces that enable closed-loop, data-driven, and intelligent control. For instance, the O-RAN Alliance introduced two RAN Intelligent Controllers (or RICs) that connect through open interfaces to the disaggregated components of the RAN, and implement control loops that run at different time scales.

Innovation and standardization in 5G have brought advancements to every facet of the cellular architecture. This ranges from the introduction of new frequency bands and signaling technologies for the radio access network (RAN), to a core network underpinned by micro-services and network function virtualization (NFV). However, like any emerging technology, the pace of real-world deployments does not instantly match the pace of innovation. To address this discrepancy, one of the key aspects under continuous development is the RAN with the aim of making it more open, adaptive, functional, and easy to manage. In this paper, we highlight the transformative potential of embracingnovel cellular architecturesby transitioning from conventional systems to the progressive principles of Open RAN. This promises to make 6G networks more agile, cost-effective, energy-efficient, and resilient. It opens up a plethora of novel use cases, ranging from ubiquitous support for autonomous devices to cost-effective expansions in regions previously underserved. The principles of Open RAN encompass: (i) a disaggregated architecture with modular and standardized interfaces; (ii) cloudification, programmability and orchestration; and (iii) AI-enabled data-centric closed-loop control and automation. We first discuss the transformative role Open RAN principles have played in the 5G era. Then, we adopt a system-level approach and describe how these Open RAN principles will support 6G RAN and architecture innovation. We qualitatively discuss potential performance gains that Open RAN principles yield for specific 6G use cases. For each principle, we outline the steps that research, development and standardization communities ought to take to make Open RAN principles central to next-generation cellular network designs.

Cellular-connected unmanned aerial vehicle (UAV) swarm is a promising solution for diverse applications, including cargo delivery and traffic control. However, it is still challenging to communicate with and control the UAV swarm with high reliability, low latency, and high energy efficiency. In this paper, we propose a two-phase command and control (C&C) transmission scheme in a cellular-connected UAV swarm network, where the ground base station (GBS) broadcasts the common C&C message in phase I. In phase II, the UAVs that have successfully decoded the C&C message will relay the message to the rest of UAVs via device-to-device (D2D) communications in either broadcast or unicast mode, under latency and energy constraints. To maximize the number of UAVs that receive the message successfully within the latency and energy constraints, we formulate the problem as a Constrained Markov Decision Process to find the optimal policy. To address this problem, we propose a decentralized constrained graph attention multi-agent Deep-Q-network (DCGA-MADQN) algorithm based on Lagrangian primal-dual policy optimization, where a PID-controller algorithm is utilized to update the Lagrange Multiplier. Simulation results show that our algorithm could maximize the number of UAVs that successfully receive the common C&C under energy constraints.

Authorship identification is the process of extracting and analysing the writing styles of authors to identify the authorship. From the writing style, the author and his/her different characteristics can be recognised, which is very useful in digital forensics and cyber investigations. In the literature, authorship identification tasks were addressed on both long and short documents and performed on different languages, such as English, Arabic, Chinese, and Greek. This survey has reviewed the authorship identification tasks for the Arabic language to contribute to this area of research by exploring Arabic language performance and challenges. A total of 27 prominent Arabic studies of each authorship identification domain were reviewed considering the used data, selected features, utilised methods, and results. After a review of the various studies, it was concluded that the results of authorship identification tasks vary based on mostly the selected features and used dataset. Furthermore, the effective features differ from one dataset to another based on the various types of the Arabic language. However, all authorship identification tasks involving the Arabic language face considerable challenges with data pre-processing due to the challenging Arabic concatenative morphology.

Fifth Generation (5G) New Radio (NR) does not support data transmission during random access (RA) procedures, which results in unnecessary control signalling overhead, especially for small data transmission (SDT). Motivated by this, 3GPP has proposed 4/2-step SDT RA schemes based on the existing grant-based (4-step) and grant-free (2-step) RA schemes, with the aim to enable data transmission during RA procedures in Radio Resource Control (RRC) Inactive state. To compare the 4/2-step SDT RA schemes with the benchmark 4/2-step RA schemes, we provide a spatio-temporal analytical framework to evaluate the RA schemes, which jointly models the preamble detection, Physical Uplink Shared Channel (PUSCH) decoding, and data transmission procedures. Based on this analytical model, we derive the analytical expressions for the overall packet transmission success probability in each RACH attempt. Our results show that 2-step SDT RA scheme provides the highest overall packet transmission success probability, but performance gain decreases with the increase of device intensity.

Mobile communications have been undergoing a generational change every ten years or so. However, the time difference between the so-called “G's” is also decreasing. While fifth-generation (5G) systems are becoming a commercial reality, there is already significant interest in systems beyond 5G, which we refer to as the sixth generation (6G) of wireless systems. In contrast to the already published papers on the topic, we take a top-down approach to 6G. More precisely, we present a holistic discussion of 6G systems beginning with lifestyle and societal changes driving the need for next-generation networks. This is followed by a discussion into the technical requirements needed to enable 6G applications, based on which we dissect key challenges and possibilities for practically realizable system solutions across all layers of the Open Systems Interconnection stack (i.e., from applications to the physical layer). Since many of the 6G applications will need access to an order-of-magnitude more spectrum, utilization of frequencies between 100 GHz and 1 THz becomes of paramount importance. As such, the 6G ecosystem will feature a diverse range of frequency bands, ranging from below 6 GHz up to 1 THz. We comprehensively characterize the limitations that must be overcome to realize working systems in these bands and provide a unique perspective on the physical and higher layer challenges relating to the design of next-generation core networks, new modulation and coding methods, novel multiple-access techniques, antenna arrays, wave propagation, radio frequency transceiver design, and real-time signal processing. We rigorously discuss the fundamental changes required in the core networks of the future, such as the redesign or significant reduction of the transport architecture that serves as a major source of latency for time-sensitive applications. This is in sharp contrast to the present hierarchical network architectures that are not suitable to realize many of the anticipated 6G services. While evaluating the strengths and weaknesses of key candidate 6G technologies, we differentiate what may be practically achievable over the next decade, relative to what is possible in theory. Keeping this in mind, we present concrete research challenges for each of the discussed system aspects, providing inspiration for what follows.

The exploding volumes of mobile video traffic call for deploying content caches inside mobile operator networks. With in-network caching, users' requests for popular content can be served from a content cache deployed at mobile gateways in vicinity to the end user. This inherently reduces the load on the content servers and the backbone of operator's network. In light of the increasing trend in virtualization of network functions, we propose a cost-effective caching as a service (CaaS) framework for virtual video caching in 5G mobile networks. In order to evaluate the pros and cons of our CaaS approach, we formulate two virtual caching problems, namely maximum return on investment(MRI) and maximum offloaded traffic (MOT). MRI aims at maximizing return on caching investment by finding the best trade-off between the cost of cache storage and bandwidth savings from caching video contents in the mobile network operator (MNO)'s cloud. Likewise, MOT aims to maximize the traffic offloaded from the MNO's core and backhaul within given budget constraints. More specifically, taking the popularity and size of video contents into account, MRI and MOT aim to find the optimal caching tables which maximize the ratio of transmission bandwidth cost to storage cost and the offloaded traffic for a given budget, respectively. We reduce the complexity of the proposed problem formulated as a binary-integer programming (BIP) by using canonical duality theory (CDT). Experimental results obtained using the invasive weed optimization (IWO) have shown significant performance enhancement of the proposed system in terms of return on investment, quality, offloaded traffic, and storage efficiency.

The emerging mulsemedia (MULtiple SEnsorial MEDIA) introduces new sensorial data (haptic, olfaction, gustation, etc.), significantly augmenting the conventional audio-visual communication. This can be used in many areas, such as immersive entertainment and innovative education. Previous research has been dedicated to evaluating the impact of other sensorial data on conventional multimedia; however, standalone quality evaluation of new sensorial data, especially vibrotactile data (a type of haptic data), has not been covered. To the best of our knowledge, this paper is the first to empirically demonstrate that the common statistical metrics in audio and visual domains, i.e. signal-to-noise ratio (SNR) and Structural SIMilarity (SSIM), are highly correlated with human vibrotactile perception as well. To be specific, we propose a testing protocol for vibrotactile quality evaluation and conduct subjective experiments. The results suggest that SNR and SSIM are applicable to vibrotactile quality assessment. We also consider a practical scenario where the quality of vibrotactile data varies with time. Based on the validation of SNR and SSIM in the first part, we present an objective metric as a hybrid composition of SNR and SSIM. Instead of assessing the quality of data using an overall score, the hybrid metric evaluates the quality in a time-varying manner. Subjective experiments are conducted and the results demonstrate that the correlation coefficient can be significantly increased using the hybrid metric.

In emergency medical services, the lag time between injury and treatment is one of the most critical parameters with respect to patient survivability. Ambulance services aim to maximize the likelihood of prompt medical treatment to prevent death and/or potential non-reversible damages. The emerging Tactile Internet has a vital role to play on that frontier by allowing next generation of ambulances to be equipped with advanced haptic/tactile devices to allow pre-hospital treatment/diagnosis or even remote surgery while en route. In this paper we propose a novel reliable multi-modal e- health high mobility service optimization framework for ambulances utilizing mobile edge clouds to efficiently transport real time patient information to the hospital. The main challenge of the proposed e-health service is to guarantee the heterogeneous QoS requirements of all involved data flows between the ambulance and the medical personnel. To this end, we formulate the service configuration problem as an optimization problem. In addition, a set of low- complexity algorithms are proposed to provide competitive solutions in real-time. A comprehensive set of numerical investigations are presented to characterize the attainable system performance of the proposed schemes.

Narrowband-Internet of Things (NB-IoT) has been released by 3GPP to provide extended coverage and low energy consumption for low-cost machine-type devices. Requiring only a reasonably low-cost hardware update to the already deployed long term evolution base stations and being compatible with current core network and enhanced core solutions that aim to reduce the battery consumption and minimize the signaling, NB-IoT deployments are quickly increasing, making NB-IoT a dominating technology for low-power wide area networks. To this aim, in this paper, we focus on group communications (i.e., multicast) in NB-IoT to efficiently support the transmission of firmware, software, task updates, or commands toward a large set of devices. We discuss the architectural and procedural enhancements needed to support the unique features of group communications in machine-type environments, such as customer-driven group formation. We also extend the NBIoT frame to include a channel for multicast transmissions. Finally, we propose two transmission strategies for multicast content delivery and evaluate their performance considering the impact on the downlink background traffic and the channel occupancy.

Network softwarization is a major paradigm shift, which enables programmable and flexible system operation in challenging use cases. In the fifth-generation (5G) mobile networks, the more advanced scenarios envision transfer of high-rate mission-critical traffic. Achieving end-to-end reliability of these stringent sessions requires support from multiple radio access technologies and calls for dynamic orchestration of resources across both radio access and core network segments. Emerging 5G systems can already offer network slicing, multi-connectivity, and end-to-end quality provisioning mechanisms for critical data transfers within a single software-controlled network. Whereas these individual enablers are already in active development, a holistic perspective on how to construct a unified, service-ready system as well as understand the implications of critical traffic on serving other user sessions is not yet available. Against this background, this paper first introduces a softwarized 5G architecture for end-to-end reliability of the mission-critical traffic. Then, a mathematical framework is contributed to model the process of critical session transfers in a softwarized 5G access network, and the corresponding impact on other user sessions is quantified. Finally, a prototype hardware implementation is completed to investigate the practical effects of supporting mission-critical data in a softwarized 5G core network, as well as substantiate the key system design choices.

Splitting functionalities of radio access network (RAN) and cloudification of such functionalities is considered as one of the key enablers of the next generation mobile and wireless networking, i.e. 5G, and is often referred to as software-defined RAN, virtualized RAN or Cloud RAN. Defining the splitting point, and maintaining the tight interaction between different functionalities in the RAN is, however, critical. Success of such cloudification depends on the availability of high speed fronthaul, while high speed fronthauling is costly. In this paper we experiment splitting MAC and PHY layer with fronthauling through Ethernet that allows using commodity and low-cost industry standard equipment. We examine the effect of packetization on latency, and study the pros and cons of splitting MAC and PHY layer, within a hardware-based testbed.

Multimedia communication in the Internet of Things (IoT) can potentially reach into a vast array of areas and touch people’s lives in profound and different ways. For example, real-time multimedia communication could be applied in the current U.S. 911 system to provide responders with detailed information about the nature and severity of an incident before they arrive on the scene, if the callers can transmit image and/or video of the incident site. City governments can also allow citizens to report traffic and road conditions by uploading real-time multimedia data via a specific smartphone app.

Leveraging multiple simultaneous small cell connections is an emerging and promising solution to enhance session continuity in millimeter-wave (mmWave) cellular systems that suffer from frequent link interruptions due to blockage in ultra-dense urban deployments. However, the available performance benefits of feasible multi-connectivity strategies as well as the tentative service quality gains that they promise remain an open research question. Addressing it requires the development of a novel performance evaluation methodology, which should consider: 1) the intricacies of mmWave radio propagation in realistic urban environments; 2) the dynamic mmWave link blockage due to human mobility; and 3) the multi-connectivity network behavior to preserve session continuity. In this paper, we construct this much needed methodology by combining the methods from queuing theory, stochastic geometry, as well as ray-based and system-level simulations. With this integrated framework, both user- and network-centric performance indicators together with their underlying scaling laws can be quantified in representative mmWave scenarios. To ensure modeling accuracy, the components of our methodology are carefully cross verified and calibrated against the current considerations in the standards. Building on this, a thorough comparison of alternative multi-connectivity strategies is conducted, as this paper reveals that even simpler multi-connectivity schemes bring notable improvements to session-level mmWave operation in realistic environments. These findings may become an important reference point for subsequent standardization in this area.

Machine-to-machine (M2M) constitutes the communication paradigm at the basis of Internet of Things vision. M2M solutions allow billions of multi-role devices to communicate with each other or with the underlying data transport infrastructure without, or with minimal, human intervention. Current solutions for wireless transmissions originally designed for human-based applications thus require a substantial shift to cope with the capacity issues in managing a huge amount of M2M devices. In this paper, we consider the multiple access techniques as promising solutions to support a large number of devices in cellular systems with limited radio resources. We focus on non-orthogonal multiple access (NOMA) where, with the aim to increase the channel efficiency, the devices share the same radio resources for their data transmission. This has been shown to provide optimal throughput from an information theoretic point of view. We consider a realistic system model and characterize the system performance in terms of throughput and energy efficiency in an NOMA scenario with a random packet arrival model, where we also derive the stability condition for the system to guarantee the performance.

Device-to-Device (D2D) communication is expected to enable a number of new services and applications in future mobile networks and has attracted significant research interest over the last few years. Remarkably, little attention has been placed on the issue of D2D communication for users belonging to different operators. In this paper, we focus on this aspect for D2D users that belong to different tenants (virtual network operators), assuming virtualized and programmable future 5G wireless networks. Under the assumption of a cross-tenant orchestrator, we show that significant gains can be achieved in terms of network performance by optimizing resource sharing from the different tenants, i.e., slices of the substrate physical network topology. To this end, a sum-rate optimization framework is proposed for optimal sharing of the virtualized resources. Via a wide site of numerical investigations, we prove the efficacy of the proposed solution and the achievable gains compared to legacy approaches.

Machine-to-machine (M2M) wireless systems aim to provide ubiquitous connectivity between machine-type communication (MTC) devices without any human intervention. Given the exponential growth of MTC traffic, it is of utmost importance to ensure that future wireless standards are capable of handling this traffic. In this paper, we focus on the design of a very efficient massive access strategy for highly dense cellular networks with M2M communications. Several MTC devices are allowed to simultaneously transmit in the same resource block by incorporating Raptor codes and a simple modulation scheme. This significantly reduces the access delay and improves the achievable system throughput. A simple yet efficient random access strategy is proposed to not only detect the selected preambles, but also estimate the number of devices which have chosen them. No device identification is needed in the random access phase which significantly reduces the signaling overhead. The proposed scheme is analyzed and the maximum number of MTC devices that can be supported in a resource block is characterized as a function of the message length, number of available resources, and the number of preambles. Simulation results show that the proposed scheme can effectively support a massive number of MTC devices for a limited number of available resources, when the message size is small.

Spectrum aggregation provides a promising approach to improve the network capacity for Cognitive Radio Ad-Hoc Networks (CRAHNs). Resource allocation for spectrum aggregation-based CRAHNs has become one of the main issues. In this paper, we propose a cross-layer optimization for CRAHNs with the spectrum aggregation. The main objective of our paper is to maximize the network throughput under the network resource constraints. In this regard, we investigate the joint optimization for channel allocation, power control and routing under signal-to-interference-and- noise ratio (SINR) model. This cross-layer optimization problem is decomposed into two sub-problems: a resource allocation at the physical (PHY) layer, and a throughput optimization at the network layer. At the PHY layer, the particle swarm optimization algorithm is proposed to find the suboptimal solution, then at the network layer, linear programming is applied to evaluate the particle's fitness value for throughput maximization. The simulation results demonstrate that the joint optimization of channel allocation and power control is an effective way to improve network throughput, especially when the network has sufficient power supply.

Cell association in cellular networks is an important aspect that impacts network capacity and eventually quality of experience. The scope of this work is to investigate the different and generalized cell association (CAS) strategies for Device-to-Device (D2D) communications in a cellular network infrastructure. To realize this, we optimize D2D-based cell association by using the notion of uplink and downlink decoupling that was proven to offer significant performance gains. We propose an integer linear programming (ILP) optimization framework to achieve efficient D2D cell association that minimizes the interference caused by D2D devices onto cellular communications in the uplink as well as improve the D2D resource utilization efficiency. Simulation results based on Vodafone's LTE field trial network in a dense urban scenario highlight the performance gains and render this proposal a candidate design approach for future 5G networks.

The Device-to-Device (D2D) communication principle is a key enabler of direct localized communication between mobile nodes and is expected to propel a plethora of novel multimedia services. However, even though it offers a wide set of capabilities mainly due to the proximity and resource reuse gains, interference must be carefully controlled to maximize the achievable rate for coexisting cellular and D2D users. The scope of this work is to provide an interference- aware real- time resource allocation (RA) framework for relay- aided D2D communications that underlay cellular networks. The main objective is to maximize the overall network throughput by guaranteeing a minimum rate threshold for cellular and D2D links. To this direction, genetic algorithms (GAs) are proven to be powerful and versatile methodologies that account for not only enhanced performance but also reduced computational complexity in emerging wireless networks. Numerical investigations highlight the performance gains compared to baseline RA methods and especially in highly dense scenarios which will be the case in future 5G networks.

Operating at ultra-high frequency (UHF), TV white space (TVWS) can achieve long-distance communication and good in-building penetration, and has attracted increasing attention of regulators, researchers and stakeholders. This paper explores the potential of TVWS for network provisioning within a cluster of buildings, through a succession of tests. Different transmission distances, from 10m to over 120m, and through multiple layers of walls as well as complex transmission environment imposed by other factors like office and construction facilities, are considered. Further, a compact ultra-wide band (UWB) printed monopole antenna is designed for the client white space terminal, and compared with a commercial directional UHF antenna on the same client. Measurement results show that the in-house compact antenna achieves fast network speed and a high signal-to-interference-plus-noise ratio (SINR), and it is orientation independent.

Powered by next generation mobile networking capabilities, the Tactile Internet will be able to transport touch and actuation in real-time. Enabled by suitable robotics and haptics equipment at the edges, and an unprecedented communications network, the Tactile Internet will provide a true paradigm in creating skill-set delivery networks. The fifth generation (5G) mobile communications systems will underpin this emerging Internet at the wireless edge. This paper presents the most important technology concepts which lay at the intersection of the larger Tactile Internet and the emerging 5G systems. Specifically, the paper presents some of the most important Tactile Internet applications, outlines the key technical requirements, and covers end-to-end architectural aspects of the Tactile Internet.

To underpin the predicted growth of the Internet of Things (IoT), a highly scalable, reliable and available connectivity technology will be required. Whilst numerous technologies are available today, the industry trend suggests that cellular systems will play a central role in ensuring IoT connectivity globally. With spectrum generally a bottleneck for 3GPP technologies, TV white space (TVWS) approaches are a very promising means to handle the billions of connected devices in a highly flexible, reliable and scalable way. To this end, we propose a cognitive radio enabled TD-LET test-bed to realize the dynamic spectrum management over TVWS. In order to reduce the data acquisition and improve the detection performance, we propose a hybrid framework for the dynamic spectrum management of machine-to-machine networks. In the proposed framework, compressed sensing is implemented with the aim to reduce the sampling rates for wideband spectrum sensing. A noniterative reweighed compressive spectrum sensing algorithm is proposed with the weights being constructed by data from geolocation databases. Finally, the proposed hybrid framework is tested by means of simulated as well as real-world data.

Maintaining multiple wireless connections is a promising solution to boost capacity in fifth-generation (5G) networks, where user equipment is able to consume radio resources of several serving cells simultaneously and potentially aggregate bandwidth across all of them. The emerging dual connectivity paradigm can be regarded as an attractive access mechanism in dense heterogeneous 5G networks, where bandwidth sharing and cooperative techniques are evolving to meet the increased capacity requirements. Dual connectivity in the uplink remained highly controversial, since the user device has a limited power budget to share between two different access points, especially when located close to the cell edge. On the other hand, in an attempt to enhance the uplink communications performance, the concept of uplink and downlink decoupling has recently been introduced. Leveraging these latest developments, this paper significantly advances prior art by proposing and investigating the concept of flexible cell association in dual connectivity scenarios, where users are able to aggregate resources from more than one serving cell. In this setup, the preferred association policies for the uplink may differ from those for the downlink, thereby allowing for a truly decoupled access. With the use of stochastic geometry, the dual connectivity association regions for decoupled access are derived, and the resultant performance is evaluated in terms of capacity gains over the conventional downlink received power access policies.

The IoT paradigm holds the promise to revolutionize the way we live and work by means of a wealth of new services, based on seamless interactions between a large amount of heterogeneous devices. After decades of conceptual inception of the IoT, in recent years a large variety of communication technologies has gradually emerged, reflecting a large diversity of application domains and of communication requirements. Such heterogeneity and fragmentation of the connectivity landscape is currently hampering the full realization of the IoT vision, by posing several complex integration challenges. In this context, the advent of 5G cellular systems, with the availability of a connectivity technology, which is at once truly ubiquitous, reliable, scalable, and cost-efficient, is considered as a potentially key driver for the yet-to emerge global IoT. In the present paper, we analyze in detail the potential of 5G technologies for the IoT, by considering both the technological and standardization aspects. We review the present-day IoT connectivity landscape, as well as the main 5G enablers for the IoT. Last but not least, we illustrate the massive business shifts that a tight link between IoT and 5G may cause in the operator and vendors ecosystem.

The long-term ambition of the Tactile Internet is to enable a democratization of skill, and how it is being delivered globally. An integral part of this is to be able to transmit touch in perceived real-time, which is enabled by suitable robotics and haptics equipment at the edges, along with an unprecedented communications network. The fifth generation (5G) mobile communications systems will underpin this emerging Internet at the wireless edge. This paper presents the most important technology concepts, which lay at the intersection of the larger Tactile Internet and the emerging 5G systems. The paper outlines the key technical requirements and architectural approaches for the Tactile Internet, pertaining to wireless access protocols, radio resource management aspects, next generation core networking capabilities, edge-cloud, and edge-AI capabilities. The paper also highlights the economic impact of the Tactile Internet as well as a major shift in business models for the traditional telecommunications ecosystem.

Millimeter wave (mmWave) links will offer high capacity but are poor at penetrating into or diffracting around solid objects. Thus, we consider a hybrid cellular network with traditional sub-6 GHz macrocells coexisting with denser mmWave small cells, where a mobile user can connect to either opportunistically. We develop a general analytical model to characterize and derive the uplink and downlink cell association in the view of the signal-to-interference-and-noise-ratio and rate coverage probabilities in such a mixed deployment. We offer extensive validation of these analytical results (which rely on several simplifying assumptions) with simulation results. Using the analytical results, different decoupled uplink and downlink cell association strategies are investigated and their superiority is shown compared with the traditional coupled approach. Finally, small cell biasing in mmWave is studied, and we show that unprecedented biasing values are desirable due to the wide bandwidth.

Until the 4thGeneration (4G) cellular 3GPP systems, a user equipment's (UE) cell association has been based on the downlink received power from the strongest base station. Recent work has shown that - with an increasing degree of heterogeneity in emerging 5G systems - such an approach is dramatically suboptimal, advocating for an independent association of the downlink and uplink where the downlink is served by the macro cell and the uplink by the nearest small cell. In this paper, we advance prior art by explicitly considering the cell-load as well as the available backhaul capacity during the association process. We introduce a novel association algorithm and prove its superiority w.r.t. prior art by means of simulations that are based on Vodafone's small cell trial network and employing a high resolution pathloss prediction and realistic user distributions. We also study the effect that different power control settings have on the performance of our algorithm.

This paper capitalizes on two emerging trends, i.e., the growing use of wireless at the edge of industrial control networks and the growing interest to integrate IP into said networks. This is facilitated by recent design contributions from the IEEE and the IETF, where the former developed a highly efficient deterministic time-frequency scheduled medium access control protocol in the form of IEEE 802.15.4e timeslotted channel hopping (TSCH) and the latter IPv6 networking paradigms in the form of 6LoWPAN/ROLL, and scheduling approaches in the form of 6TiSCH. The focus of the present work is on advancing the state-of-the-art of deterministic 6TiSCH schedules toward more flexible but equally reliable distributed approaches. In addition, this paper aims to introduce the first implementation of 6TiSCH networks for factory automation environments: it outlines the challenges faced to overcome the scalability issues inherent to multihop dense low-power networks; the experimental results confirm that the naturally unreliable radio medium can support time-critical and reliable applications. These developments pave the way for wireless industry-grade monitoring approaches.

The ongoing densification of small cells yields an unprecedented paradigm shift in user experience and network design. The most notable change comes from cellular rates being comparable to next-generation WiFi systems. Cellular-to-WiFi offloading, the standard modus operandi of recent years, is therefore shifting towards a true integration of both technology families. Users in future 5G systems will thus likely be able to use 3GPP, IEEE, and other technologies simultaneously, so as to maximize their quality of experience. To advance this high-level vision, we perform a novel performance analysis specifically taking the system-level dynamics into account and thus giving a true account on the uplink performance gains of an integrated multi radio access technology (RAT) solution versus legacy approaches. Further, we advocate for an enabling architecture that embodies the tight interaction between the different RATs, as we lay out a standardization roadmap able to materialize the envisaged design. 3GPP-compliant simulations have also been carried out to corroborate the rigorous mathematical analysis and the superiority of the proposed approach.

Cyber-physical technologies enable event-driven applications, which monitor in real-time the occurrence of certain inherently stochastic incidents. Those technologies are being widely deployed in cities around the world and one of their critical aspects is energy consumption, as they are mostly battery powered. The most representative examples of such applications today is smart parking. Since parking sensors are devoted to detect parking events in almost-real time, strategies like data aggregation are not well suited to optimize energy consumption. Furthermore, data compression is pointless, as events are essentially binary entities. Therefore, this paper introduces the concept of Lean Sensing, which enables the relaxation of sensing accuracy at the benefit of improved operational costs. To this end, this paper departs from the concept of instantaneous randomness and it explores the correlation structure that emerges from it in complex systems. Then, it examines the use of this system-wide aggregated contextual information to optimize power consumption, thus going in the opposite way; from the system-level representation to individual device power consumption. The discussed techniques include customizing the data acquisition to temporal correlations (i.e, to adapt sensor behavior to the expected activity) and inferring the system-state from incomplete information based on spatial correlations. These techniques are applied to real-world smart-parking application deployments, aiming to evaluate the impact that a number of system-level optimization strategies have on devices power consumption.

Future machine-to-machine (M2M) communications need to support a massive number of devices communicating with each other with little or no human intervention. Random access techniques were originally proposed to enable M2M multiple access, but suffer from severe congestion and access delay in an M2M system with a large number of devices. In this paper, we propose a novel multiple access scheme for M2M communications based on the capacity-approaching analog fountain code to efficiently minimize the access delay and satisfy the delay requirement for each device. This is achieved by allowing M2M devices to transmit at the same time on the same channel in an optimal probabilistic manner based on their individual delay requirements. Simulation results show that the proposed scheme achieves a near optimal rate performance and at the same time guarantees the delay requirements of the devices. We further propose a simple random access strategy and characterize the required overhead. Simulation results show that the proposed approach significantly outperforms the existing random access schemes currently used in long term evolution advanced (LTE-A) standard in terms of the access delay.

Cell association in cellular networks has traditionally been based on the downlink received signal power only, despite the fact that uplink and downlink transmission powers and interference levels differed significantly. This approach was adequate in homogeneous networks with macro base stations all having similar transmission power levels. However, with the growth of heterogeneous networks where there is a big disparity in the transmit power of the different base station types, this approach is highly inefficient. In this paper, we study the notion of Downlink and Uplink Decoupling (DUDe) where the downlink cell association is based on the downlink received power while the uplink is based on the pathloss. We present the motivation and assess the gains of this 5G design approach with simulations that are based on Vodafone's LTE field trial network in a dense urban area, employing a high resolution ray-tracing pathloss prediction and realistic traffic maps based on live network measurements.

Traditional cellular networks play an essential role in the evolution of machine-to-machine (M2M) networks, due to their ubiquitous network coverage. However, M2M communications have some unique characteristics, which are different from the conventional human to human communications, such as the massive number of connected machine type devices (MTD) and stringent QoS requirements. This requires an innovative design of cellular access networks in order to accommodate these requirements. In this paper, we consider the design of M2M communications by using the existing cellular network infrastructure. Since the MTDs do not have their own radio resources, they send their data through the cellular users' (CU) sub-channels. We propose a distributed algorithm that matches a group of MTDs with a particular CU that aims earning more profit by sharing its resources. Then the MTDs in each group access the sub-channels of their matched CU in a TDMA manner. We prove that the proposed algorithm results in a stable matching after a small number of iterations. It is shown that the weighted sum data rate of the MTDs in the proposed algorithm approaches that of the centralized algorithm as the price step-number is sufficiently small, with a significantly lower overhead than the centralized approach.

Machine-to-machine (M2M) communications have emerged as a flourishing technology for next-generation communications, and are undergoing rapid development while inspiring numerous applications. However, unique features of M2M communications, such as the massive number of machine type devices (MTD) and delay sensitive applications require specific considerations. To enhance the communication efficiency with delay sensitive short messages, a key strategy is to utilize data aggregation. To facilitate an efficient distributed data aggregation among MTDs with different urgency levels, we propose a game theoretic mechanism based on the coalitional game. Through the proposed algorithm, MTDs autonomously collaborate and self-organize into disjoint independent and stable coalitions, and send their data through a coalition head known as the aggregator. Within each coalition, the utility of the users is defined in such a way that maximum cooperation is compelled. Finally, we discuss the stability of the resulting network structure, and analyse the performance of the proposed scheme.

In this paper, we study the performance of mode selections in device-to-device (D2D) communications in terms of end-to-end average throughput, average delay, and dropping probability, considering dynamic data arrival with non-saturated buffers. We first introduce a general framework that includes three canonical routing modes, namely D2D mode, cellular mode, and hybrid mode, which can be combined with different resource allocation restrictions to represent the semi-static and dynamic selections of the three resource sharing modes. A queuing model is developed when the routing mode for every D2D connection is chosen, and an exact numerical analysis and an approximate decomposition and iteration approach are proposed. The performance measures are obtained from the decomposition approach and validated by means of simulation. We further introduce a mode selection scheme that adaptively chooses to semi-statically or dynamically select the resource sharing modes according to the estimated performance measures.

Despite its notable importance, backhauling has - thus far - been a largely overlooked issue. However, driven by the uptake of small cell networks, current dedicated backhaul solutions are no longer viable for mobile operators, calling for novel deployment and backhaul-aware access strategies. In this paper, following the market's latest developments in infrastructure sharing, we investigate the uplink performance improvement when using a spatially-close open access small cell over one operator's carrier and simultaneously a direct access over another carrier. An important constituent of our work is the optimization problem of joint access and in-band (over-the-air) backhaul for the small cell link. Given the large degree of parametric freedom, another important constituent is the use of cognitive self-organizing networking mechanisms in the form of reinforcement learning, to autonomously optimize the resources allocated to and within each carrier. Simulation results corroborate our findings, with reported performance improvements of 40% under completely autonomous operating conditions when compared to benchmark backhaul approaches.

In this paper, we evaluate the energy-efficiency of LTE for Machine-to-Machine (M2M) communications with small data transmissions. We quantify the minimum resources that can be allocated in LTE for the uplink and we show that the energy-efficiency of the transmissions of small blocks of data strongly depends on the transmission power and the Adaptive Modulation and Coding (AMC) procedure. Indeed, when an aggressive Modulation and Coding Scheme (MCS) is used thanks to good channel quality, the energy-efficiency of LTE decreases for the transmission of small amounts of data, as the physical resource blocks are under-utilized. In addition, we propose a solution to deal with this drawback by selecting an optimal MCS and utilizing the LTE Uplink Power Control (UPC) mechanism. The results presented in this paper are based on open-source ns-3 computer-based simulations.

A time-slotted multiple access wireless system with N transmitting nodes, each equipped with an energy harvesting (EH) device and a rechargeable battery of finite capacity, is studied. The energy arrival process at each node is modeled as an independent two-state Markov process, such that a node either harvests one unit of energy, or none, at each time slot (TS). The access point (AP) schedules a subset of K nodes to transmit over K orthogonal channels at each TS. The maximum total throughput is studied for a backlogged system without the knowledge of the EH processes and nodes' battery states at the AP. The problem is identified as a partially observable Markov decision process, and the optimal policy for the general model is studied numerically. Under certain assumptions regarding the EH processes and the battery sizes, the optimal scheduling policy is characterized explicitly, and is shown to be myopic.

The design of energy-efficient communication strategies is needed to extend the lifetime of Machine-to-Machine low power devices operating in realistic wireless fading and shadowing channels. In this paper, we assess the suitability of using cooperative and duty-cycled retransmissions (CDC-ARQ) in realistic low power networks to improve their energy-efficiency. A CDC-ARQ scheme achieves this goal by maintaining two interchangeable wireless links towards any intended destination and using the currently optimal link in an opportunistic manner. We perform comprehensive performance evaluation using the ns-3 simulator to verify a theoretical framework fitted to the reference IEEE 802.15.4e protocol and its cooperative extension. The ns-3 simulation outcomes confirm prior theoretical findings and indicate optimal operating regions with minimum energy consumption for the shadowed relay system under consideration. We establish that a significant energy improvement can be achieved in a typical three-node scenario when a duty-cycled opportunistic cooperative relaying protocol is used instead of a fixed two-hop relaying system.

The emerging IEEE802.15.4e standard and IETF RPL routing protocol are core to the organization of multi-hop Low-power and Lossy Networks. They provide key functionalities useful for a really viable Internet of Things. However, several open issues still remain and require research efforts to be solved. Among others, the design of effective scheduling schemes in such systems is one of the major problems; in fact, there are no specifications about how schedules should be realized. Trying to fill this gap, this paper presents a new Decentralized Traffic-Aware Scheduling algorithm, which is able to construct optimum multi-hop schedules in a distributed fashion. Its effectiveness has been proved by using simulation results and comparing it with a centralized scheme. The reported performance results encourage the use of the developed scheduling technique, since it allows a very efficient queue management, and thus it minimizes packet discards due to buffer overflows, while at the same time minimizing the network duty cycle.

With the advent of small‐cell networks (SCNs) to support growing wireless data volumes and thus reduced cell sizes, cooperative communications are significantly facilitated. Applicable to Third Generation Partnership Project long‐term evolution‐A, the authors propose a novel channel/queue‐aware user pairing and scheduling scheme in a cooperative virtual multiple‐input–multiple‐output (VMIMO) system. The queueing performance of the VMIMO system with the scheduling scheme is analysed based on the finite‐state Markov model (FSMM), and compared with that of non‐cooperative systems. Bounds on the average queuing delay of users are derived by using a semi‐definite programming (SDP) approach. The presented analyses are validated through comparing the analytical and simulation results. It is found that the introduced VMIMO pairing process is able to significantly reduce service delays, bringing on a positive impact of cooperative techniques on next generation wireless systems.

A point-to-point wireless communication system in which the transmitter is equipped with an energy harvesting device and a rechargeable battery, is studied. Both the energy and the data arrivals at the transmitter are modeled as Markov processes. Delay-limited communication is considered assuming that the underlying channel is block fading with memory, and the instantaneous channel state information is available at both the transmitter and the receiver. The expected total transmitted data during the transmitter's activation time is maximized under three different sets of assumptions regarding the information available at the transmitter about the underlying stochastic processes. A learning theoretic approach is introduced, which does not assume any a priori information on the Markov processes governing the communication system. In addition, online and offline optimization problems are studied for the same setting. Full statistical knowledge and causal information on the realizations of the underlying stochastic processes are assumed in the online optimization problem, while the offline optimization problem assumes non-causal knowledge of the realizations in advance. Comparing the optimal solutions in all three frameworks, the performance loss due to the lack of the transmitter's information regarding the behaviors of the underlying Markov processes is quantified.

In this paper, we consider the performance of coded wireless communication systems experiencing non-frequency selective fading channels in shadowed environments. The quality of service (QoS) in a wireless network is dependent on the packet error outage (PEO). We address the problem of finding a tractable expression for the coded PEO over Nakagami-m channels with shadowing, considering multilevel modulations, various block and convolutional channel coding schemes and hard decision decoding. In order to obtain the coded PEO, an inversion of the coded packet error probability (PEP) w.r.t. the signal to noise ratio (SNR) is needed. To this end, we propose an invertible approximation for the coded PEP w.r.t. the uncoded bit error probability (BEP) in Nakagami-m fading channels which is accurate for all BEPs of interest. The BEP itself depends on the average SNR and we hence make use of previous results on the inversion of the uncoded BEP w.r.t. the SNR in Nakagami-m fading channels, holding for M-PSK and M-QAM signals. We were thus able to obtain a reliable closed form expression for the coded PEO in flat fading and shadowing channels. The theoretical findings are verified by means of simulations.

The Time Synchronized Channel Hopping (TSCH) protocol is part of the newly defined IEEE 802.15.4e standard and represents the latest generation of highly reliable low-power MAC protocols. With implementation details left open, we conceive here a novel Traffic Aware Scheduling Algorithm (TASA) by extending the theoretically well-established graph theory methods of matching and coloring by means of an innovative approach based on network topology and traffic load. TASA is able to support emerging industrial applications requiring low latency at low duty cycle and power consumption. Preliminary simulation results have also been reported to highlight the effectiveness of the proposed algorithm.

Femtocells, despite their name, pose a potentially large disruption to the carefully planned cellular networks that now connect a majority of the planet's citizens to the Internet and with each other. Femtocells - which by the end of 2010 already outnumbered traditional base stations and at the time of publication are being deployed at a rate of about five million a year - both enhance and interfere with this network in ways that are not yet well understood. Will femtocells be crucial for offloading data and video from the creaking traditional network? Or will femtocells prove more trouble than they are worth, undermining decades of careful base station deployment with unpredictable interference while delivering only limited gains? Or possibly neither: are femtocells just a "flash in the pan"; an exciting but short-lived stage of network evolution that will be rendered obsolete by improved WiFi offloading, new backhaul regulations and/or pricing, or other unforeseen technological developments? This tutorial article overviews the history of femtocells, demystifies their key aspects, and provides a preview of the next few years, which the authors believe will see a rapid acceleration towards small cell technology. In the course of the article, we also position and introduce the articles that headline this special issue.

Feasibility of underground data communications by employing magnetic induction is investigated. Realizing an underground wireless sensor network for a district heating plant motivates this research challenge. The main contribution of the paper is finding the optimal designs for coil antennas at the transmitter and receiver sides of a magneto-inductive communication system.

We deal with the analytical performance study of orthogonal space-time block codes (OSTBC) applied to multiple-input multiple-output (MIMO) systems experiencing non-frequency selective fast fading and shadowing. We address the problem of finding a tractable closed-form expression for the symbol error outage (SEO) over Rice fading channels in shadowing environments. In order to obtain the SEO, a symbol error probability (SEP) inversion w.r.t. the average signal to noise ratio (ASNR) is needed since no invertible SEP approximations are available in literature. We propose an accurate approximation for the SEP in Rice fading channels. This new approximation is proved to be invertible w.r.t. the ASNR and this expression thus facilitates the derivation of a tight approximation of the SEO in lognormal shadowing environments.

We address the coexistence problem between macrocell and femtocell systems by controlling the aggregated interference generated by multiple femtocell base stations at the macrocell receivers in a distributed fashion. We propose a solution based on intelligent and self-organized femtocells implementing a realtime multi-agent reinforcement learning technique, known as decentralized Q- learning. We compare this cognitive approach to a non-cognitive algorithm and to the well known iterative water- filling, showing the general superiority of our scheme in terms of (non-jeopardized) macrocell capacity. Furthermore, in distributed settings of such femtocell networks, the learning may be complex and slow due to mutually impacting decision making processes, which results in a non-stationary environment. We propose a timely solution -referred to as docition- to improve the learning process based on the concept of teaching and expert knowledge sharing in wireless environments. We demonstrate that such an approach improves the femtocells' learning ability and accuracy. We evaluate the docitive paradigm in the context of a 3GPP compliant OFDMA (Orthogonal Frequency Division Multiple Access) femtocell network modeled as a multi-agent system. We propose different docitive algorithms and we show their superiority to the well known paradigm of independent learning in terms of speed of convergence and precision.

Machine-to-Machine (M2M), an emerging communications paradigm, is a facilitator of data flows between machines used, e.g., in mission-critical applications. Focusing in this paper on embedded multihop M2M implementations with myopic routing, a prime design aim is to jointly minimize energy expenditure and the end-to-end delay whilst not jeopardizing the network's operational reliability. We thus evaluate the achievable energy-delay tradeoff in such embedded multihop wireless networks with focus on channel coding. Supported by analytical as well as numerical evaluation, we show that channel coding has a profound impact on the end-to-end performance of M2M systems. We also detail some viable design guidelines which quantify which channel coder to use under which operating conditions. Finally, we formulate the problem in more general shadowing conditions.

The 25 papers in this special issue focus on simple wireless sensor networking solutions.

IETF ROLL has recently proposed gradient routing as a fundamental building block for data collection in Wireless Sensor Networks. This paper seconds this choice by presenting an implementation of gradient routing on current hardware, and by showing experimentally that gradient routing is robust against topological changes. To stress its self-healing quality, we design and implement a complete communication stack in which neighbor tables are built in a purely reactive fashion. We quantify the resulting topological changes, and show how gradient routing elegantly handles these dynamics. This paper presents, to the best of our knowledge, the first experimental study on gradient routing as advocated by IETF ROLL.

This letter addresses the problem of finding a tractable expression for the symbol error outage (SEO) in flat Nakagami-m fading and shadowing channels. We deal with M-ary phase shift keying (M-PSK) and quadrature amplitude modulation (M-QAM) which extends our previous results on BPSK signaling. We propose a new tight approximation of the symbol error probability (SEP) holding for M-PSK and M-QAM signals which is accurate over all signal to noise ratios (SNRs) of interest. We derive a new generic expression for the inverse SEP which facilitates the derivation of a tight approximation of the SEO in a lognormal shadowing environment.

In this paper we consider transmit and receive selection methods designed to achieve high channel capacities in a single-user MIMO link. A variety of radio channels are considered, including i.i.d. Rayleigh, correlated Rayleigh and Ricean fading environments. Also considered is the presence of imperfect channel state information (CSI) and a simplified waterfllling scheme. In all cases, we evaluate the performance of optimal selection, simple norm-based selection and other benchmark selection techniques. The major contribution is a general approach to analyzing the capacity of the norm-based selection schemes via a simple power scaling factor. We are able to assess the impact of different channels, imperfect CSI and power allocation using this power scaling factor. Furthermore, the analysis is valid for all scenarios: transmit selection, receive selection and joint transmit-receive selection. Results are shown which compare the capacity performance over a wide range of cases. A notable conclusion is that optimal selection, which is computationally intensive, is outperformed at low signal-to-noise- ratios by the simple norm-based approach with power allocation.

Wireless Sensor Networks have inherent constraints such as available bandwidth and energy. Communication protocols applying to those kind of networks need to be localized and distributed. When such a protocol needs to discriminate between several neighbor nodes (for example, the node with most remaining energy), an efficient approach is to ask the neighbors to encode information in backoff timers (in our example, the consumed energy), and respond to a question after having waited for the resulting duration. The node which answers first is elected. Whereas this technique is stateless and efficient, its inherent drawback is that response messages can collide. This paper addresses this issue by proposing a backoff function to alleviate this problem. Analytical results are presented, and confirmed using extensive simulations.

We consider a 2-hop wireless relay network. We explore transmit power allocation among the source and relays to maximize the received SNR at the destination. We consider two relaying protocols, "amplify and forward" (AAF) and "decode and forward" (DAF) and calculate the respective power allocations for both uncoded and coded system. For a 2- hop relay system with one relay node, we derive a closed-form power allocation solution and based on it we propose a relay active condition. If and only if the fading channel coefficients satisfy this condition, the relay transmits the signals to the destination; otherwise, the relay will stay in an idle state. For a system with more than one relay nodes, general closed-form power allocation solutions based on the extact SNR expression are not tractable, so we calculate a SNR upper bound and derive a sub-optimum power allocation solution based on this bound. The simulation results show that for a 2-hop relay channel, the proposed adaptive power allocation (APA) scheme can bring the system a considerable SNR gains compared to the equal power allocation scheme. This gain will be further monotonically increased as the number of relays increases.

We propose in this paper a low-energy address allocation scheme (LEADS). LEADS is a two-level hierarchical conflict- free address allocation scheme that provides validated address to each node in a wireless sensor network. LEADS provides a quick and energy-efficient self-configuration solution for WSN deployment. It takes the unsolved issues related to random arrival and abrupt departure of sensor nodes into account, both in partitions splitting and merging scenarios. Unlike most of the existing solutions, LEADS does not require any information from neither periodical control packet (HELLO message) (Nesargi and Prakash, 2002), nor routing protocols (Vaidya, 2002). In LEADS, the addresses space is divided into addresses pools which are managed by addresses agents. Every agent uses a stateful function to assign addresses to the nodes in its neighborhood. The uniqueness of assigned addresses is guaranteed by this two-level allocation strategy. Moreover, LEADS is a localized algorithm. Simulation results show that LEADS achieves the dynamic address allocation task with both lower message cost and lower energy consumption comparing to existing solutions. Our results illustrate the need for a dynamic and low-energy address allocation scheme to realize energy efficient sensor network applications and to extend network lifespan.

Geographic-based routing techniques are promising for wireless sensor networks, which suffer from severe energy constraints and a low throughput nature. In its simplest form, greedy geographic forwarding faces the problem of a low delivery ratio. Other protocols use the right hand rule to guarantee delivery. They nevertheless assume nodes know their exact position, whereas positioning systems offer only limited accuracy. In this paper, we propose to use path-recording mechanisms, where nodes append their identifier to the header of the message, together with geographic forwarding. While yielding a comparable number of hops for a message to reach destination than existing routing protocols with guaranteed delivery, this technique offers guaranteed delivery regardless of the positioning accuracy. This makes path-recording particularly suitable for real-world wireless sensor network implementations.

For low-energy, low-throughput Wireless Sensor Networks, geographic forwarding avoids creating and maintaining a structure using clustering or gradient construction. Yet, geographic forwarding assumes position-awareness, which may be not realistic. In this paper, we propose to use virtual coordinates. Each node determines its [x,y] position in a virtual space based on a random or pseudo-random process. It uses these coordinates to route information with geographical-inspired routing protocols. Extensive simulation shows that this approach can be very efficient for low-throughput WSN.

The roll-out density of wireless local area networks (WLANs) has recently witnessed a dramatic increase and is currently reaching saturation levels. The frequency bands designated to WLANs does not suffice any more to provide non-overlapping, and hence interference-free, communication bands. A large body of research has been dedicated to a wide variety of optimum maximum likelihood sequence estimation (MLSE) and sub-optimum in-band interference mitigation techniques. Our contribution lies in a reduction of the state-space of a MLSE detector in the case of a desired WLAN receiver experiencing delayed interference from some other transmitters operating in partially overlapping spectral bands and over independent frequency-selecting block-fading channels. Based on the formulation of the optimum receiver, we derive a sub-optimum receiver of reduced complexity and demonstrate its satisfactory performance in the context of strong interference.

To enable spontaneous communications in wireless sensors networks, both self-configuration and self-organization appear to be two fundamental mechanisms. However, the majority of prior contributions in ad hoc network suffer from the low processing capability, limited storage space, energy constraint and large number of nodes when being applied in wireless sensor networks. Moreover, self-configuration and self-organization have been always considered as two independent mechanisms. The authors believe that this consideration leads to inefficient network and redundant protocol cost. Hence, in this paper a fully integrated scheme of self-configuration and self-organization was proposed. It can better resolve the distributed address allocation using the structure generated by itself with low message overhead. It also provides significant energy savings comparing to other schemes and low latency.

The deployment of wireless local area networks (WLANs) has recently gained in popularity with roll-out densities often reaching saturation levels. The frequency bands designated to WLANs do thus not suffice anymore to provide non-overlapping, and hence interference-free, communication. Prior research has therefore been dedicated to a wide variety of mainly cochannel interference mitigation techniques. Our contribution lies in the performance analysis of the more realistic case of spatially close WLAN systems interfering asynchronously in DSSS mode and on adjacent channels. The authors expose the performance of optimum and sub-optimum multiuser detection maximum likelihood sequence estimators (MUD-MLSEs) under varying conditions, e.g. level of interference, degree of spectral overlap, etc. This facilitates a better understanding and design of future interference-limited WLAN systems. The performance results are also important to spectrum policy makers, allowing to knowledgeably estimate the degree of tolerated interference in license exempt bands.

In this paper, we consider a 2-hop wireless diversity relay network. We explore transmit power allocation among the source and relays to maximize the received signal to noise ratio (SNR) at the destination. We consider two relay protocols, "amplify and forward" (AAF) and "decode and forward" (DAF) and design the respective power allocations for both uneeded and coded systems. For a 2-hop relay system with one relay node, we derive a closed-form power allocation solution and, based on it, we propose a relay activation condition. If and only if the fading channel coefficients satisfy this condition, the relay transmits the signals to the destination; otherwise, the relay will stay in the idle state. For a system with more than one relay node, general closed-form power allocation solutions based on an exact SNR expression are difficult to derive; we hence, calculate a SNR upper bound and derive a sub-optimum power allocation solution based on this bound. The simulation results show that for a 2-hop diversity relay channel with one relay node the proposed adaptive power allocation (APA) scheme yields about 1- 2 dB SNR gains compared to the equal power allocation. This SNR gain increases monotonically as the number of relays increases

In this paper, we address the issue of co-existence of Bluetooth (BT) and Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA)-based Wireless Local Area Networks (WLANs) in the license free 2.4 GHz band. Specifically, the probabilistic treatment presented in the following investigates the effect of the slotted p-persistent CSMA/CA system on a co-existing BT piconet. A closed-form expression for packet error probability (PEP) in BT as a function of CSMA/CA parameters such as the persistence probability, probability of packet generation and the number of users is derived. The analytical model entails different BT packet types, frequency hopping guard time, and different traffic models in the BT piconet.

In this paper we consider transmit and receive selection methods designed to achieve high channel capacities in a single-user MIMO link. A variety of radio channels are considered, including i.i.d. Rayleigh, correlated Rayleigh and Ricean fading environments. Also considered is the presence of imperfect channel state information (CSI) and a simplified waterfilling scheme. In all cases, we evaluate the performance of optimal selection, simple norm based selection and other benchmark selection techniques. The major contribution is a general approach to analyzing the capacity of the selection schemes via a simple power scaling factor. We are able to assess the impact of different channels, imperfect CSI and power allocation using this power scaling factor. Furthermore, the analysis is valid for all scenarios: transmit selection, receive selection and joint transmit-receive selection. Results are shown which compare the capacity performance over a wide range of cases. A notable conclusion is that optimal selection, which is computationally intensive, is outperformed at low SNR by the simple, norm based approach with power allocation.

Wireless sensor networks (WSNs) have witnessed a tremendous upsurge in recent years, both in academia and industry; this is mainly attributed to their unprecedented operating conditions and a variety of commercially viable applications. Because of their dependence on scarce battery power, communication protocols need to be energy efficient. However, finding the optimal solution is challenging as it needs to consider the whole communication stack at once. In this paper, we propose an approach that aims at optimizing jointly L2 (link) and L3 (routing) protocols. We design 1-hopMAC, a communication architecture grouping MAC and routing layers which avoids 1-hop neighborhood knowledge. 1-hopMAC can be combined, among others, with a geographic or gradient based routing protocols. We present an analytical study of energy consumption to point out the optimal configuration of 1-hopMAC

Orthogonal space-time block codes allow utilising the diversity provided by multiple-input-multiple-output communication channels, thereby decreasing the error probability for a given communication rate. The contribution of this paper is the derivation of closed-form expressions of the symbol error probability of distributed codes deployed over Nakagami flat fading channels with different channel gains and fading parameters

The performance of a space-time block coded (STBC) multicarrier code division multiple-access (MC- CDMA) system operating in Nakagami-m fading channel with correlated subcarriers is investigated. Independency among MC-CDMA subcarriers is often assumed in literature which leads to idealistic performance bounds. The contribution of this paper is the derivation of closed-form expressions of the symbol error probabilities. We use the moment generating function (MGF) of the correlated Nakagami-m random variable (RV) to calculate the closed-form average symbol error rates (SERs) of binary and M-QAM signals with maximum ratio combining detection technique. Both, numerical and simulation results are presented, showing an excellent agreement.

This paper presents the exact bit error rate (BER) analysis of a cyclic delay diversity (CDD) multicarrier code division multiple-access (MC-CDMA) system. By using the moment generating function (MGF) of the correlated Nakagami-mrandom variable and considering the realistic case of frequency-correlated MC-CDMA subcarriers (which is often ignored in literature), closed-form BER expressions are obtained with maximum ratio combining (MRC) detection technique for both uplink and downlink scenarios. Simulation results are also presented which show excellent agreement with the analytical framework.

In this paper, we study the effect of channel estimation error at the receiver on the mutual information of a multi user multiple input multiple output (MIMO) channel obeying Rayleigh fading. We assume that imperfect knowledge of the channel is available at the receiver and find the upper bound and the lower bound on mutual information for Gaussian input signals for the uplink of this system. We prove that when the input power at each user is uniformly distributed over its transmit antennas, the bounds on the mutual information are asymptotically tight for Gaussian input signals and this tightness increases when the number of users increases. Numerical simulations are conducted to corroborate theoretical results.

Random access MAC protocols for radio environments are prone to collisions without offering a way to successfully avoid or identify them and thus fail to achieve the performance required by a multitude of applications. However, in some cases it is possible to use collision detection in order to reduce the time spent on collisions and improve the system efficiency. In this paper we provide an analytical framework for WCSMA/CD with a finite user population. The expected channel throughput is then derived for different design parameters and compared against p-persistent CSMA/CA.

It has been shown that distributed turbo coding (DTC) can approach the capacity of a wireless relay network. In the existing DTC schemes, it is usually assumed that error-free decoding is performed at a relay. We refer to this type of DTC schemes as perfect DTC. In this paper, we propose a novel DTC scheme. For the proposed scheme, instead of making a decision on the transmitted information symbols at the relay as in perfect DTC, we calculate and forward the corresponding soft information. We derive parity symbol soft estimates for the interleaved source information when only the a posteriori probabilities of the information symbols are known. The results show that the proposed scheme can effectively mitigate error propagation due to erroneous decoding at the relay. Simulation results also confirm that the proposed scheme approaches the outage probability bound of a distributed two-hop relay network at high signal-to-noise ratios

In this paper, we study the effect of channel estimation error on transmitter design in a multiple input multiple output (MIMO) channel. We assume that only knowledge of either the channel correlation or mean is available at the transmitter and find the transmitting strategy. Under covariance feedback, at the transmitter the channel is modelled as a matrix of zero mean circularly symmetric complex Gaussian (ZMCSCG) random variables with known covariances. We assume that only rows of channel matrix are correlated. Under mean feedback the covariance of channel is modelled as white. We determine the necessary and sufficient conditions under which a unit rank input covariance matrix, i.e. eigen-beamforming, can achieve capacity lower bound. Numerical simulations are conducted to corroborate theoretical results.

This paper develops a feasible architecture for end-to-end QoS management over B3G networks where multiple heterogeneous radio access networks (RAN) can be coordinated at radio level by means of supporting common radio resource management (CRRM) functionalities. The presented approach is claimed to be innovative as long as it is inspired in the most relevant trends being developed in different fields and forums and come up with a global solution capturing such partial concepts. A key point of the architecture is the introduction of a wireless QoS broker entity that becomes the link between CRRM and E2E QoS management. In the paper, after introducing the proposed QoS framework, the signaling and procedures to support such architecture in the B3G network are addressed. Over such a basis, a connection establishment procedure is discussed to show how the problem of initial RAN selection can be managed by the proposed architecture.

A novel approach is proposed and analysed in this paper, where the micro-cell utilises the same frequency band as the macro-cell to transmit non-real time data. The main idea is that, whenever the macro-cell interference falls below a given threshold, the micro-cell schedules data with a transmission rate dependent on the micro-cell signal strength and the macro-cell interference level. We prove analytically that utilizing the hence created micro-cell transmission scheme non-real time data can be transmitted at micro-cells. We also derive the average duration and the frequency of transmit event for non-real time data transmission at micro-cells, all of which is verified by means of a dynamic CDMA system level simulator

In this paper, we propose a novel distributed turbo coding (DTC) scheme which can be used in a system where imperfect decoding occurs at a relay. For the proposed scheme, rather than making a decision on the transmitted information symbols at the relay as in the conventional DTC, we calculate and forward the corresponding soft information at the relay. For the proposed scheme, we derive the parity symbols soft estimates for the interleaved source information when only the a posteriori probabilities (APP) of the information symbols are known. Analytical results show that the performance of the proposed scheme, at high SNR, is limited by the ratio of the received SNR at the relay and that at the destination. In order to make the performance loss of the proposed scheme, compared to the perfect DTC as small as possible, the relay should be placed closer to the source than to the destination and/or make the transmit power from the source larger than that from the relay.

In the B3G system considered, which is based on the 3GPP UMTS architecture, the initial hypothesis made in this paper, is that the QoS management of the IP access network is taken in charge by a bandwidth broker. A pre-handover signalling for QaS-aware path selection is investigated with the goal of achieving the "always best connected" paradigm. Furthermore, the scalability of the proposed scheme is analysed taking into account the overhead due to IP micromobility, QoS routing, CRRM and bandwidth broker

The paper presents a detailed analysis of the properties of the cost function vital to WCDMA radio network optimization. The cost function for the downlink is carefully selected and analyzed numerically for three representative small network layouts and antenna orientation parameters (azimuth and tilt). The analysis includes local minima search, their distribution and their attraction regions. Based on obtained results, several notable conclusions about optimal solutions for network configuration are made as well as some directives for proper optimization algorithm design suggested

Common radio resource management strategies are devoted to achieve an efficient usage of the pool of radio resources available in a heterogeneous radio access network context. This paper describes the functionalities associated with the common vision of radio access technologies, the different possibilities in the functional model split and the corresponding implementation considerations.

The paper presents a brief survey of the methods for solving systems of linear equations (linear solvers), which could be useful in application to WCDMA network optimization. The methods are scored with respect to their computational cost when base stations are equipped with traditional antennas as well as with smart antennas. Preconditioning in the conjugate gradient square (CGS) method is discussed. We also analyze the technique, which without any loss of accuracy, may reduce dimensions of the power control problem in a multi-service network but is limited only to traditional antennas the smart antenna case must be solved with conventional solver. Theoretical considerations are confirmed experimentally.

A link adaptation schemes is proposed to improve the efficiency to support DiffServ traffic over CDMA air interface. To differentiate the resource allocation between DiffServ PHBs and between the in/out profile packets within each AF class, two-level differentiation is done in the proposed scheme: inter-class differentiation and infra-class differentiation. Through this interaction between the two levels, a better QoS balance between classes is achieved and therefore a higher capacity is gained as shown by our numerical evaluation.

Information theoretical optimization problems related to the resource allocation of wireless cellular and ad hoc networks are not solvable in closed form due to the nonlinear logarithmic representation of the Shannon capacity. This paper introduces functional approximations to the MIMO capacity over flat Rayleigh fading channels, which allow for analytical solutions to network resource optimization problems. The precision of the suggested approximations is assessed and is shown to provide a very close match to the exact capacity expression.

The performance of space time trellis codes (STTCs) can be further improved by utilizing the partial channel information and combining some precoding schemes at the transmitter. This paper presents a STTC scheme - hybrid STTC (HSTTC). For this scheme, the STTC signals are first linearly transformed and then transmitted through the single selected antenna. The upper bound on pairwise error probability (PEP) for HSTTC is derived. It is shown that by a proper code construction HSTTC can achieve not only a full spatial diversity order, but also a time diversity order, as well as a significant coding gain determined by the weighted square product distance (WSPD). A new design criterion for HSTTCs has been proposed and the optimum 4-state code, based on this criterion, has been found by systematic code search. Simulation results are provided for the quaternary phase-shift keying (QPSK) signal sets. They show that the proposed new code is superior by 9 dB and 11 dB to the conventional transmit antenna selection (TAS) and Tarokh-Seshadri-Calderbank codes (TSC), respectively, at a BER of 10e/sup -4/ over time-varying fading channels.

Distributed multi-hop communication systems have been introduced recently which allow the application of multiple-input-multiple-output (MIMO) capacity enhancement techniques over spatially separated relaying mobile terminals. They were shown to yield significant capacity gains over direct communication or non-distributed single-input-single-output (SlSO) relaying networks. The contribution of This work is the derivation of throughput-maximising resource allocation strategies in terms of fractional frame duration and transmission power. It is assumed that distributed terminals cooperate at each relaying stage and that the detection of packets is performed at each relaying stage.

We investigate the impact of power control on the performance of a multi-hop CSMA/CA system, also taking into account the additional traffic generated due to multi-hop transmissions. An analytical model is presented with emphasis on the influence of power, more specifically the number of nodes dwelling in the area covered by this power, on the number of hops and, consequently, on the end-to-end throughput. Unlike other works, a closed form solution is derived for the throughput performance of a multi-hop CSMA/CA system, as a function of the offered load, the nodes density and transmission power.

Mobility tracking yields efficient network resource management and enables very useful additional services, provided that accurate online estimations of both the location and the velocity of a mobile user are performed. We present a novel method for tracing a mobile user by subsequently estimating his/her position through a single base station positioning (SBSP) method designed for microcellular and third generation (3G) wireless communications systems. Raw data about user position are then smoothed through a linear regression setup which adaptively varies its inertia on the basis of the previous observations. This results in a tracking method which is able to estimate both the location and the velocity of a user with high accuracy, as proven by numerical results obtained in different microcellular scenarios.

An approximate but explicit fractional bandwidth and power allocation algorithm for orthogonal regenerative frequency-division multiple-access-based multihop communication systems over ergodic flat-fading channels is presented. The exposed algorithm is assessed for a two-hop scenario, where it is shown to operate within 10% of the optimum resource allocation. The achieved end-to-end capacity is up to 45% higher if compared to a trivial allocation strategy with equal resources.

Mesh connectivity is traditionally dealt with at IP-layer, where packets are relayed to adjacent network nodes according to prior specified rules. Recently, the concept of data relaying at PHY-layer has gained widespread interest, where regenerative and transparent relaying are feasible M. O. Hasna, M-S. Alouini (2002). In parallel, investigations into MIMO systems have become mature. The current paper introduces a generalised concept of data relaying at PHY layer, where relaying is combined with MIMO technology. The thus created distributed PHY-layer mesh network is a natural generalisation of previously introduced virtual antenna arrays.

A novel telecommunication system, termed virtual antenna arrays, was previously presented that allows the application of multiple-input-multiple-output (MIMO) capacity enhancement techniques to mobile terminals with a limited number of antenna elements. This paper introduces a novel approach extending the possible applicability of the space-time block codes (STBC) to such virtual antenna arrays. The main idea is to emulate the (2 transmit antennas, 2 receive antennas) diversity scheme developed by Alamouti (1998). This approach successfully deals with the problem of just one receiving antenna in a handset. Simulations results indicate an improvement in error performance over the simple (2,1) Alamouti scheme.

The objective of the IST project MIND (Mobile IP based network developments) is to facilitate IP-based broadband services for mobile users in various operating environments. Activities within MIND concentrate on the development, optimisation and harmonisation of the appropriate layers involved. The physical (PHY) layer was chosen to base on the high performance radio local area network type 2 standard (HIPERLAN/2). The work presented here demonstrates the applicability of HIPERLAN/2 to scenarios with increased mobility. Initially, HIPERLAN/2 was designed for rather static environments providing hot spot data rates of up to 54 Mbps. Mitigation techniques to overcome the drawbacks of a fast fading environment are thus studied within IST-MIND. The extracted transceiver structures allow the deployment of HIPERLAN/2 in almost any environments currently envisaged. Particularly, the system deployment of HIPERLAN/2 to a vehicle-to-vehicle communication scenario is studied and preliminary system level performance results presented.