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Intelligent connected objects, the building blocks of IoT, represent battery supplied electronic devices. These devices are expected to be deployed in very large numbers, and manual replacement of their batteries will severely restrict their large-scale or wide area deployments. Therefore, energy efficiency is of the utmost importance in the design of the IoT devices. The wireless communication between the distributed sensor devices and the host stations can consume significant energy, even more when larger coverage is required. Ultra-low-power wake up radio (WuR) represent one of the most prominent solutions for energy efficiency in IoT. However, the WuR devices have several limitations that bound their practical applicability and usage, such as short range capabilities and low signal sensitivity. As a result, the WuR devices commonly misinterpret their wake up address and inevitably lead to overall performance degradation of the system. This work, introduces the concept of error correction codes in the wake up address. It is envisioned that the error correction codes can increase the overall robustness and sensitivity of the WuR devices. The work also analyses the potential energy efficiency gains and the energy-latency tradeoff degradation of the WuR based IoT system when utilizing the error correction codes.

End-to-end network slicing is a novel concept based on virtualization and softwarization technology that can efficiently address the problems of legacy networks. It can leverage agile physical and network layer adaptability, and foster optimal user and system performance. These features make end-to-end network slicing suitable for scenarios such as flash crowds and emergency situations. This article presents an end-to-end network slicing framework capable of addressing the demands of flash crowd and emergency scenarios. The article provides details about these scenarios, and it introduces an end-to-end agile, flexible, and scalable wireless system architecture consisting of softwarized components that can be orchestrated to fulfill the underlying system requirements. By addressing important key performance indicators with experimental measurements, the article demonstrates the applicability of our slicing framework for flash crowd scenarios.

This paper presents the generic definitions, basic functionalities and current research trends in Cloud Radio Access Networks and its derivatives, Virtual Radio Access Networks and Open Radio Access Networks. Moreover, the paper provides practical results, insights, and lessons learned regarding the limitations and unforeseen issues of Radio Access Networks virtualization. The paper also discusses the potential developments and possibilities for commercial roll out of novel Radio Access Networks approaches.

The concept of virtualization has contributed to improved structural functionality especially in modern telecom­munications networks. The introduction of Software-Defined Networks (SDN) and Network Functions Virtualization (NFV), es­pecially in mobile and wireless networks, marks the era of softwarization, centralized control and programmability of network entities. Various software platforms that support the concept of virtualization, provide a range of auspicious features such as modu­larity, multiplicity, interoperability, reliability. All of these features represent the building blocks of current fifth generation of mobile networks (5G). This paper focuses on the wireless (radio) virtualization. The paper gives the short overview of the latest and most important concepts related to wireless system virtualization and presents a platform operating a fully virtualized LTE network, capable of dynamically reconfiguring its radio parameters. The performance analysis focuses on the deployment and reconfiguration of the presented system. The results clearly show that wireless virtualization fosters significantly improved deploy­ment and reconfiguration times, compared to conventional systems.

Increasing number of ubiquitous devices are being used in the medical field to collect patient information. Those connected sensors can potentially be exploited by third parties who want to misuse personal information and compromise the security, which could ultimately result even in patient death. This paper addresses the security concerns in eHealth networks and suggests a new approach to dealing with anomalies. In particular we propose a concept for safe in-hospital learning from internet of health things (IoHT) device data while securing the network traffic with a collaboratively trained anomaly detection system using federated learning. That way, real time traffic anomaly detection is achieved, while maintaining collaboration between hospitals and keeping local data secure and private. Since not only the network metadata, but also the actual medical data is relevant to anomaly detection, we propose to use differential privacy (DP) for providing formal guarantees of the privacy spending accumulated during the federated learning.

Wireless network (radio) virtualization and its synergy with ML/AI-based technologies is a novel concept that can efficiently address problems of legacy networks, such as flash crowds. This paper discusses the integration aspects of intelligence-based technologies with Sate-of-the-Art end-to-end reconfigurable, flexible and scalable network architecture, capable of handling demands in flash crowd scenarios. The presented results, demonstrate that advanced solutions based on ML can significantly improve the network proactivity and adaptivity by reliably predicting flash crowd scenarios. The results also show that in case of low dataset fidelity, conventional statistical models are a more suitable option.

The FALCON project, presented in this paper, focuses on dynamic on-demand virtual resource allocation for wireless network environments, leveraging a highly flexible and adaptable wireless network to provide reliable and efficient communications in flash crowd scenarios and emergency situations.

Machine-type communications (MTC) represent a novel wireless communication paradigm that incorporates large number of devices and triggers several communication challenges. The MTC virtualization can overcome some of these challenges, provisioning decreased deployment costs, improved energy efficiency, improved coexistence with existing radio technologies, easy extensions of novel MTC technologies, etc. This paper discusses the virtualization approaches for MTC in a multi-RAT environment. The paper discusses the benefits and practical aspects of MTC virtualization, and evaluates the advantages and disadvantages of the Docker and OpenStack virtualization frameworks. The evaluation of both virtualization frameworks is conducted on a novel virtualized multi-RAT cloud-based demo platform that incorporates three distinct MTC technologies (SigFox, Z-Wave and LTE-M).

The very high commercial exploitation of the WiFi based technologies in recent years and the absence of solutions for optimal WiFi orchestration, usually leads to suboptimal spectrum usage and user performances. The combination of WiFi based radio resource management (RRM) and the radio environmental maps (REMs) can provide an efficient solution for a Smart-WiFi technology, which improves the underlying spectrum usage as well as network performance. The REM facilitates efficient utilization of the radio environmental data, like device location, estimated channel models, real-time interference levels between the networks, WiFi channels occupancies etc. This information can be utilized for an intelligent and optimal RRM decision making in WiFi related scenarios. This paper proposes a novel REM based RRM approach for management and optimization of commercial WiFi devices that utilizes the available underlying radio environmental information. The paper demonstrates the proposed approach on a commercially available platform, conducting on-the-fly radio environmental data acquisition and optimized WiFi RRM allocation. The simulation analysis results also show that the proposed Smart-WiFi leverage noticeable performance gains for large scale scenarios, compared to conventional WiFi networks.

The legacy wireless systems are designed to exploit static configuration and deployment, and cannot handle the discrepancies of the spatio-temporal traffic demand. Cloud RAN (C-RAN) is a novel flexible radio technology that utilizes the virtualization concepts and can efficiently address the static deployment of conventional wireless systems. The C-RAN also leverages high radio network flexibility by introducing the network function virtualization approach to wireless networks. This paper presents a novel C-RAN platform that virtualizes and operates with full GSM and LTE systems. The presented platform is solely based on open-source and off the shelf solutions, providing easy implementation, low cost and high scalability. The paper also introduces a novel dynamic resource allocation algorithm that facilitates the C-RAN’s optimal performance in dynamic scenarios. The proposed algorithm is analyzed and validated on the presented C-RAN platform. The results of the performance analysis clearly show the advantages of the proposed dynamic resource allocation algorithm. Moreover, they prove the applicability of the C-RAN platform for variety of different scenarios.

The multi-sensory systems represent a paradigm where every-day objects and devices are consisted of identifying, sensing, networking and processing capabilities. This will allow them to communicate with each other as well as with other devices and services over the Internet, in order to accomplish a specific target or set of objectives. Ultimately, these sensory devices will be ubiquitous, context-aware and will facilitate ambient intelligence. This paper elaborates on the current state of research on with respect to the multi-sensory devices and supporting ICT technologies, by providing detailed literature overview as well as identifying the current trends and most prominent applications. The paper also presents the open issues and provides a discussion for the possible future directions.

Environment protection and climate changes are depending on the efficiency of the energy usage, electricity networks structure and consumer behavior. This paper is presenting the universal communication model of provider-consumer ICT ecosystem as a driver for energy efficiency. The system is analyzed with game theoretic approach and considers electricity market behavior of multiple players on both provider and consumer side, including the elements of variable price of production of electricity, renewable sources and bidirectional fluctuation of electricity in distributed networks. The main idea consists of the transfer of benefits of usage of the ICT energy efficiency system into investments for green energy and smart grid solution, which consequently will reduce carbon emission.

Energy efficiency is a process under development and execution in all levels of society and economy, mostly driven by the environment protection interests. One of dilemmas in this process is the interest of the electricity provider companies, what kind of model to use in order to secure their profitability and benefits from energy efficiency projects deployment? This paper is presenting an ICT model for energy efficiency, model with scalable development, starting on a level of fundamental and currently available resources. The model is consumer centric and integrates communication tools. Using the approach of cooperative game theory, we are analyzing if this model is beneficial for all stakeholders in energy efficiency chain, the providers and the consumers. Having in mind the diversity of markets for electricity, in our case we deal with the simplest scenario, considering provider – consumer relation in two regimes of electricity network stage, peak and normal load, as the baseline from where the specific commercial cases could be further developed.

The next generation of mobile systems, the 5G, requires significant advances in system architecture design and development, as a result of the tremendous increase of mobile traffic, the omnipresence of mobile services and the ever-increasing number of connected devices. Several technologies, such as cloud computing, softwareization and virtualization have been identified to pave the road towards the efficient rollout and deployment of 5G. In order to address the strict service requirements, in terms of latency, reliability and throughput, they will have to be deployed at the radio access network edges. This paper discusses the importance and necessity for resource scaling in the mobile edge computing (MEC), as a promising technology approach for 5G. It also elaborates on the potential virtualization technologies, hypervisor-based and container-based, and the underlying resource scaling approaches for different relevant scenarios. The evaluation is performed on a laboratory demo platform capable of virtualizing several types of radio access systems, such as GSM, LTE, etc. The results clearly show that container-based virtualization provides the most efficient and robust resource scaling that does not significantly affect the communication performance of the mobile users.

The ICT technology expansion and rapid penetration supported by extensive research and innovations has started to change the users' requirements for novel services and applications. Up to now, the evolution of wireless communication systems only focused on improving the way the information is exchanged between two or a group of communication entities. However, emerging user expectations for novel personalized scenarios have driven the requirement for revolutionary and divergent approaches that will foster the virtualization of human emotions, senses, and thoughts. Human Bond Communication reflects this communications paradigm shift. It represents a holistic approach capable of describing and transmitting the features of an object in the way a human perceives it. Human Bond Communication incorporates all human senses for modeling a physical object into an information-digital domain. It also focuses on actuating and transmitting the data of the physical object through an underlying communication platform. This paper elaborates on the Human Bond Communication related topics, providing a comprehensive classification and survey of the current research works, as well as identifying the key challenges for future research.

The next generation communication networks are envisioned to be flexible, scalable, reliable and secure. Software Defined Networking introduces mechanisms to build and orchestrate efficient, flexible and adaptable networks. This is achieved by the separation of software and hardware functionalities in the network devices. This paper evaluates the overall Software Defined Networking performances with respect to the allocated network resources, i.e. different CPU’s and bandwidth’s allocations. The performance results clearly show that the overall system performances can be highly influenced by the network setup and chosen topology.

Most cooperative spectrum sensing research activities focus on maximizing the primary user detection and neglect the achieved secondary system performance. This paper proposes a novel capacity-aware cooperative spectrum sensing optimization method, capable of computing the optimal values for the cooperative sensing parameters (e.g., the number of sensed samples, the number of cooperating devices, control channel bandwidth) so that the secondary system capacity is maximized. The proposed method utilizes energy detection with estimated noise power (ENP). We derive and experimentally validate the analytical models for cooperative spectrum sensing based on the ENP method. Additionally, we evaluate the performance of the proposed capacity-aware spectrum sensing described in this paper. We show that the proposed capacity-aware cooperative spectrum sensing based on noise power estimation achieves enhanced secondary system capacity compared to the previous commonly proposed sensing processes that maximize the detection performance. Moreover, the results give insight into the optimal behavior of the proposed capacity-aware cooperative spectrum sensing based on noise power estimation regarding the common cooperative spectrum sensing parameters.

Compared to the previous generations of mobile networks, 5G will provide a significant paradigm shift by including beyond state of the art technical solutions, like very high carrier frequencies with massive bandwidths, extreme base station and device densities, and very high number of transceiver antennas. However, unlike the previous generations, it will also be highly integrative and backward compatible: combining the novel 5G air interface and spectrum together with legacy wireless systems like LTE/LTE-A and WiFi, in order to facilitate an umbrella of high-rate coverage and a seamless user experience. In order to support this advances in the radio interface, the core network will also have to reach unprecedented levels of elasticity and intelligence. Spectrum regulation will need to be rethought and significantly improved, whereas energy and cost efficiencies will become one of the key parameters that will steer the 5G design and development. This paper elaborates on the 5G related topics, identifying the key challenges for future research and preliminary 5G standardization activities, as well as providing a comprehensive survey of the current literature.

This paper reports recent prototyping efforts that show the feasibility of the radio environmental map to enable efficient exploitation of TV white spaces by a cellular LTE system. We describe a flexible REM backend implementation, fully integrated with standard-compliant operational LTE base station equipment. Simulations results indicate that REMs enhance white-space detection by their means to incorporate accurate and local channel propagation information, while experimental laboratory results illustrate the feasibility and performance of transmitter localization capabilities in a REM.

eHealth technology can bring a variety of benefits to patients, caregivers, and health institutions, by facilitating improved healthcare services through the utilization of Information and Communication Technologies (ICTs). The forthcoming generation of healthcare services will require advances in computing and Wireless Sensor Networks (WSNs) in order to leverage truly intelligent and adaptive features for smarter eHealth services. This paper proposes a multi-sensory cloud based system capable of monitoring and tracking the patient's behavior with respect to his vital signs. The paper also showcases the proposed system on a real testbed, performing real-time vital signs data acquisition, processing, and monitoring.

Most of the cooperative spectrum sensing related research assumes system models with perfect control channel (i.e. with unlimited channel bandwidth and no channel errors). However, the assumption is not realistic and can lead to incorrect conclusions regarding the performance analysis of the cooperative spectrum sensing detection capabilities. This paper proposes a novel cooperative spectrum sensing framework that mitigates the imperfect control channel features, like the limited control channel bandwidth and error proneness, and achieves the detection performances of cooperative spectrum sensing under ideal control channel. It utilizes node clustering and multi-antenna spatial multiplexing (i.e. beamforming) and provides a generic framework that can be exploited by any cooperative spectrum sensing and fusion technique. The performance analysis shows that the proposed framework alleviates the control channel bandwidth limitation and significantly decreases the control channel error rate. The performance evaluation results also show that the proposed framework achieves the upper bound detection performances, i.e. achieves the same detection performances as the conventional cooperative spectrum sensing with ideal control channel.

The Cognitive Radio and the Cognitive Radio Networks have recently become one of the most intensively studied paradigms in wireless communications. The main distinctive characteristic with respect to the radio environmental conditions in which the Cognitive Radio Network operates is the time/frequency/space-dependent availability of the spectral resources, a phenomenon commonly referred as spectrum hete-rogeneity. This phenomenon imposes redefinition of the protocol stack by introducing new communication protocols for the Cognitive Radio Network including new Medium Access Control protocols. The Cognitive MAC (C-MAC) protocols employ number of mechanisms that address spectrum heterogeneity and provide technical strategies for smart exploitation of spectrum's current underutilized time/space/frequency regions that enables large spectrum efficiency gains while maximizing the transparency of the Cognitive Radio Networks to the primary system. The classification and systematization of the existing C-MAC proposals is a complex task due to many C-MAC related aspects. This survey introduces and develops generic, modular and easily extensible layout for classification and systematization of C-MAC protocols referred as C-MAC cycle. Each C-MAC protocol can be easily fragmented, mapped and visualized using the C-MAC cycle, regardless of the operational scenario and settings. The survey offers extensive overview on the state-of-the-art advances in C-MAC protocol engineering by reviewing existing and up-to-date technical solutions, identifies their basic characteristics and maps them into the C-MAC cycle. The survey also highlights the role of regulative and standardization activities on C-MAC cycle.

The significant penetration of the WiFi technology in the last decade and the lack of solutions for coordinated and efficient interference management between WiFi networks in unlicensed bands often lead to poor spectrum utilization and network performances. The synergy between Radio Environmental Maps (REMs) and Radio Resource Management (RRM) can offer a viable solution for so called Smart-WiFi that significantly improves the ISM spectrum utilization and the overall WiFi performances. REMs enable efficient usage of environmental data sets, such as WiFi device locations, estimated pathloss models, real-time interference levels, statistical channels occupancies etc. for an intelligent RRM in WiFi related scenarios. This paper proposes a novel RRM approach for WiFi coordination and optimization that exploits the available REM information. The paper also showcases the proposed approach on a real prototype, performing real-time REM data acquisition/ processing and enhanced WiFi coordination and optimization.

The unlicensed bands recently became overcrowded due to the WiFi networks, as the main populates of these bands. This is owed to the significant growth of WiFi users in the last decade, as well as the absence of solutions for coordinated and efficient interference management between WiFi devices. The synergy between Radio Environmental Maps (REMs) and Radio Resource Management (RRM) for Smart-WiFi, can be a viable solution to improve the spectrum utilization in the unlicensed bands and hence, WiFi performances. Environment data such as empirical propagation models, transmitters' locations, up-to-date interference levels, statistical channels occupancies, can serve as input to an enhanced RRM for these scenarios. The proposed demonstration aims to showcase the benefits of using REM information in the WiFi optimization. The demonstration utilizes a REM-facilitated Smart-WiFi prototype, performing real-time REM data acquisition, processing and inference as input to an enhanced WiFi optimization.

Due to the fundamental tradeoffs, achieving spectrum efficiency and energy efficiency are two contending design challenges for the future wireless networks. However, applying radio-frequency (RF) energy harvesting (EH) in a cognitive radio system could potentially circumvent this tradeoff, resulting in a secondary system with limitless power supply and meaningful achievable information rates. This paper proposes an online solution for the optimal time allocation (time sharing) between the EH phase and the information transmission (IT) phase in an underlay cognitive radio system, which harvests the RF energy originating from the primary system. The proposed online solution maximizes the average achievable rate of the cognitive radio system, subject to the $\varepsilon$-percentile protection criteria for the primary system. The optimal time sharing achieves significant gains compared to equal time allocation between the EH and IT phases., Proceedings of the 2015 IEEE International Conference on Communications (IEEE ICC 2015), 8-12 June 2015, London, UK

The CHEST demo platform facilitates a solution that can help patients suffering from COPD to adjust the conditions in their home environment and everyday life. The developed demo offers a simple and user-friendly solution, which consists of a sensor network that measures the relevant COPD parameters (number of steps; indoor temperature; level of carbon dioxide; air humidity; temperature), a developed cloud solution for data management, and a graphical user interface (GUI) that displays daily measured parameters, parameters’ statistics and interacts with the patients via specific notifications.

The beamforming techniques have been recently studied as possible enablers for underlay spectrum sharing. The existing beamforming techniques have several common limitations: they are usually system model specific, cannot operate with arbitrary number of transmit/receive antennas, and cannot serve arbitrary number of users. Moreover, the beamforming techniques for underlay spectrum sharing do not consider the interference originating from the incumbent primary system. This work extends the common underlay sharing model by incorporating the interference originating from the incumbent system into generic combined beamforming design that can be applied on interference, broadcast or multiple access channels. The paper proposes two novel multiuser beamforming algorithms for user fairness and sum rate maximization, utilizing newly derived convex optimization problems for transmit and receive beamformers calculation in a recursive optimization. Both beamforming algorithms provide efficient operation for the interference, broadcast and multiple access channels, as well as for arbitrary number of antennas and secondary users in the system. Furthermore, the paper proposes a successive transmit/receive optimization approach that reduces the computational complexity of the proposed recursive algorithms. The results show that the proposed complexity reduction significantly improves the convergence rates and can facilitate their operation in scenarios which require agile beamformers computation., Comment: 30 pages, 5 figures

The endeavor of categorizing the existing Cognitive-MAC (C-MAC) protocols requires definition of general classification frameworks or layouts that merge most of the aspects of the protocols in a single unified presentation. This chapter introduces the C-MAC cycle as a general classification and systematization layout for C-MAC protocols. The C-MAC cycle originates form the idea that the MAC layer in spectrally heterogeneous environments should provide support for three generic technical features: radio environmental data acquisition; spectrum sharing; and control channel management. The inclusion of these generic technical features is necessary in Cognitive Radio Networks (CRNs) for improving the network performance and achieving spectrum efficiency gain while providing maximal level of protection for the primary system. This chapter presents extensive survey on the state-of-art advances in C-MAC protocol engineering by reviewing existing technical solutions and proposals, identifying their basic characteristics and placing them into the C-MAC cycle, with emphasis on the modularity of the C-MAC cycle. It provides overview of large number of technical details concerning the three generic functionalities (i.e. the radio environmental data acquisition, the spectrum sharing and the control channel management) as the main building blocks of the C-MAC cycle. Three uses cases (each in different generic functional group), illustrate the capabilities of the proposed C-MAC cycle layout. In more detail, the first use case theoretically presents and practically evaluates cooperative spectrum sensing based on Estimated Noise Power. The results illustrate the effect of estimating the noise variance on the detection capabilities of the Majority Voting and Equal Gain Combining cooperative spectrum sensing strategies. The second use case presents advanced and computationally efficient horizontal spectrum sharing strategy for secondary systems based on Node Clustering and Beamforming. Finally, the last use case presents and assesses a multiuser quorum-based multiple rendezvous strategy for control channel establishment in distributed Cognitive Radio Networks.

Recent advances in cognitive radio have identified the small-cells among the most promising future wireless networking scenarios. Utilizing radio context information, smallcells should perform the most optimal radio resource management (RRM) to maximize performances and minimize inter-cell interference. Radio Environmental Maps (REM) data: empirical propagation models, active transmitters’ locations, upto-date interference levels, statistical channels occupancies, are especially beneficial in these scenarios. The proposed demonstration aims to showcase the benefits of using REM information in the small-cell optimization. The demonstration utilizes a modular/flexible REM prototype, performing a realtime REM data acquisition, processing and inference as input to an enhanced small-cell optimization.

The beamforming has been extensively studied as possible enabler of the underlay spectrum sharing and recently has been tightly related to the concept of cognitive small cells. This work proposes a more generic underlay sharing system model, which takes into consideration the interference caused to the secondary system and develops a combined (transmit and receive) beamforming design that is applicable in both uplink and downlink use cases. The paper presents a successive transmit/receive beamforming optimization algorithm, which substantially decreases the computational complexity of the combined beamforming design. The performance analysis results show that the proposed combined beamforming achieves satisfying performances (i.e. mitigating the interference from the primary to the secondary system, satisfying the interference constraints to the primary system etc.). The results show that the proposed successive optimization algorithm decreases the complexity of the combined beamforming without degrading the underlying system performances, which makes it applicable for scenarios such as HetNets and cognitive small cells, which require agile and real-time operation.

Spectrum sensing is a fundamental feature of cognitive radio technologies facilitating detection and localization of spectrum opportunities. Combined with centralized database storage, it fosters reliable spatial spectrum measurements and Radio Environmental Maps (REMs) construction that can provide an accurate insight in the spectrum utilization over time, space and frequency. The spectrum sensing process often combines different devices with different capabilities. This paper introduces novel REM construction platform that integrates several mid- and low-end spectrum sensing devices into a single heterogeneous testbed. The devices of interest are USRP2s, TI RF2500 and Sun SPOTs, which are upgraded with custom developed software for providing versatile spectrum sensing capabilities. The paper evaluates their performances and discusses their integration into a single heterogeneous testbed platform. Additionally, the paper evaluates the realized heterogeneous spectrum sensing testbed in terms of accurate REM derivation and additional statistics gathering for indoor environments.

The prospect of increasing wireless capacity via secondary access to spatio-temporally underutilized chunks of spectrum, so-called whitespaces, has been proposed as a central aspect of emerging radio systems in response to the imminent spectrum scarcity problem. In this demonstration we present a novel software tool that helps researchers, industry, and regulators in assessing the feasibility and value of secondary spectrum access beyond simple whitespace availability calculation. Whereas existing software applications merely provide visualization of estimated secondary spectrum over a geographic area, our tool uniquely enables a holistic evaluation of the realistic potential of whitespace technologies, by modelling the performance of entire secondary systems in the envisioned eco-system of dynamic spectrum access policy and technology. Our tool provides a unified and flexible software framework and assessment methodology to conduct such studies, and is composed of an extensive primary spectrum usage database, a graphical interface for user interaction, and an interface to an extensible MATLAB backend for numerical calculations. We showcase the deployment scenarios of cellular and Wi-Fi-like secondary networks in TVWS (TV whitespaces). We also compare the impact of employing FCC-type of regulatory rules (with a fixed power/no-talk distance configuration) against European WG-SE43 regulatory proposals (with probabilistic access and power control). The case studies we will demonstrate are based on real network configuration data of European and US TV networks.

Ad hoc networks are a popular wireless networking paradigm due to the infrastructure independency and dynamic network topology adaptation. Their characteristics make them suitable for emergency situations like natural disasters or military conflicts. The Radio Environmental Maps (REMs) have also become very prominent in the wireless communications and networks community lately. A general REM architecture comprises various toolboxes using signal processing algorithms, which generate/inference the radio environmental knowledge based on the radio environmental input. However, installing reliable and efficient REMs in dynamic ad hoc scenarios encounters many practical challenges, such as dynamic network topology, environment dynamism and uncertainty, device heterogeneity etc. This paper focuses on the transmitter localization toolbox of the REM framework, its comprising localization techniques and solutions and their applicability to ad hoc networking scenarios with particular focus on the arisen challenges and issues in such dynamic environments.

Multi-antenna-based spatial multiplexing exhibit high potential for enhancing the system performance of future cognitive radio networks [1]-[3]. This paper proposes a novel cooperative spectrum sensing approach that utilizes coordinated beamforming and node clustering. It provides a generic framework that can be exploited by any cooperative spectrum sensing and fusion technique. The performance analysis shows that the proposed approach decreases the average sensing Bayesian risk and can achieve higher detection probability of more than an order of magnitude.

In this demonstration paper we describe a prototype of an LTE system deployment that opportunistically exploits the spectral white spaces in the upper UHF TV bands, intelligently guided in its spectum access by a radio environment map (REM). The architecture is modular in the sense that interfaces are generic and minimal. In the proposed demo we will illustrate how information of primary transmitters and other secondary transmitters as well as estimates of the radio field strength over frequency, time and space can be made available and exploited by a secondary TDD-LTE base station to make judicious decisions on its spectral occupation.

Spectrum modeling represents an important tool, of the cognitive radio concept. Number of works have focused on developing accurate methods for modeling the spectrum usage in order to provide reliable and efficient assessment of the possible spectrum availabilities. This paper proposes a novel method for modeling of spectrum usage based on classification of measured quantities into multiple levels. The distribution of the measured quantities of each level is fitted using a known mathematical model. The proposed method utilizes practical measurements in different frequency bands focusing on both uplink and downlink channels. The validation results show that the proposed model performs more accurate fitting compared to the existing single-level models for each of the inspected frequency bands.

Detection of potential transmitters' location is one of the vital aspects for efficient practical deployment of secondary spectrum access solutions. It requires accurate and up-to-date radio environmental estimation. Spatial interpolation techniques can allow partial or complete insight into the radio field, the interference and the possible geo-locations of various field transmitters depending on the number of radio measurements performed in sparse locations. This paper presents an effective solution based on spatially interpolated Received Signal Strength (RSS) values for location estimation of radio transmitters, which operates on Radio Interference Field (RIF) maps obtained by interpolating measurement data from N sparsely distributed sensors. In contrast to the known range based localization methods the developed technique also achieves higher computational efficiency. The performance analysis shows that the proposed method is suitable for both outdoor and indoor environments and is capable of reliable detection of multiple sources even for low number of sensors.

One of the key challenges in cognitive radio is the problem of spectrum sharing. All sharing techniques proposed in the literature try to utilize the spectrum in the most efficient way, but they either lack on computational simplicity or on spectral efficiency. Network MIMO can be seen as a very promising method for spectrum sharing, because it enables multiple systems to use the same spectrum simultaneously, but requires high processing power. This paper proposes a novel cooperative technique for spectrum sharing between multiple secondary cognitive radio systems. The method, named Network Coordinated Beamforming with user Clustering (NCBC), is based on Network MIMO and utilizes Network Coordinated Beamforming (NCBF) and User Clustering (UC). The proposed NCBC approach decreases the computational complexity of NCBF making it suitable for real time spectrum sharing in cognitive radio. Monte Carlo simulations are carried out to examine the performance of the proposed technique in terms of Signal to Interference Ratio (SIR) and channel correlation. The results depict the superior performance of NCBC compared to a simple Frequency Division Spectrum Sharing (FDSS) technique in terms of aggregate system capacity and sum rate.

In this demonstration proposal we describe a prototype of a radio environment map (REM) for storing and reasoning about spectrum data obtained from heterogeneous sources. The architecture of the REM prototype is both modular and extendible, and can be used with very diverse spectrum sensors, ranging from high-fidelity spectrum analyzers to dedicated low-cost embedded solutions. In the proposed demonstration we will illustrate how information such as transmitter locations and estimates of spectrum occupancy over space and time can be inferred and made available through the REM, based on information obtained from a network of different spectrum sensors deployed specifically for the demonstration.

The different wireless and wired communication technologies are converging towards a heterogeneous communication network, requiring comprehensive resource management. This paper summarizes the development of a reconfigurable mobile multi-interface terminal, enabled with efficient heterogeneous resource management architecture, called RIWCoS. The created terminal prototype is able to perform seamless vertical handovers among three different networks: Ethernet, WLAN and UMTS. RIWCoS platform utilizes IEEE 802.21 defined entities in combination with Network Driver Interface Specification (NDIS) application programming interface (API). The functional testing is performed through specially developed graphical user interface (GUI). The paper presents an insight of the terminal architecture and the measured results regarding the throughput and average inter-packet delay. The results can also be observed on a specially designed GUI.

The concept of wireless heterogeneous networks is based on the coexistence and interoperability of different types of radio access technologies in a unified wireless heterogeneous platform. A key process in the wireless heterogeneous networks is the initiation and execution of vertical handovers. Variety of mechanisms are proposed in the literature that are tailored to optimize the choice of radio access network in the process of vertical handover initialization. This paper proposes a novel mechanism for radio access technology (RAT) selection, the Hopfield neural network Rat selection Mechanism (HRM), that utilizes the Hopfield neural networks as a powerful decision making tool. The main advantage of the proposed mechanism lays in its ability of Artificial Intelligence (AI) reasoning and the use of multi-parameter decision by exploiting the options of IEEE 802.21 protocol. This approach allows improvements in terms of service retainability, decreased packet loss, jitter, etc. The performance of the novel mechanism is compared with two other types of RAT selection mechanisms (RSS based, and Multi-criteria policy based mechanism) throughout extensive simulations. The results clearly show the benefits of the proposed new mechanism and its justified usage in wireless heterogeneous systems.

Convergence of different wireless access networks and development towards 4G yields a necessity for more efficient resource management procedures in the integrated heterogeneous platform. The notion of resource is fundamentally different in heterogeneous environments (compared to homogeneous ones) as it is spanned across several different wireless solutions. This paper summarizes the development process of a novel architecture for resource management in heterogeneous wireless networks named RIWCoS. The architectural focal point is on the emerging IEEE 802.21 standard because of its ability to enable seamless and transparent vertical handovers. The paper shows simulation results of the IEEE 802.21 benefits and reports on a novel simulation analysis (using newly introduced metrics) of the RIWCoS architecture showing that it outperforms traditional serving policies of users in heterogeneous wireless environments. Moreover, the paper elaborates on a distinguished RIWCoS feature (the SAES algorithm) that enables efficient handling of emergency situations making the RIWCoS architecture suitable for military communications.

This paper presents a prototyping and optimization approach for reconfigurable mobile multi-interface terminal. The mechanism that controls the operation of the available miniport drivers on the mobile device utilizes IEEE 802.21-defined entities in combination with Network Driver Interface Specification (NDIS) application programming interface (API). The created terminal prototype is able to perform seamless vertical handovers among three different networks: Ethernet, WLAN and UMTS. The testing of the developed prototype with different traffic generators resulted in optimization of its transmission parameters. Furthermore, the paper proposes an optimization of the handover procedure from a local to global wireless network by implementing intelligent prediction of imminent handovers. The results show that this optimization reduces the handover latency and the average inter-packet delay.

The development of new network communication protocols has to include a process of concept evaluation in order to prove its soundness. Simulation-based techniques provide assessment of communication quality in complex and realistic working conditions. This paper introduces a novel and unique simulation technique, by merging QualNet simulator and SDL protocol developer. Many complex modifications of the QualNet nodes can be efficiently implemented, which is very difficult by a straightforward re-coding of QualNet components. The proposed methodology was utilized in the development of a wireless heterogeneous IEEE 802.21-based network. The paper provides a detailed insight of the model's three basic parts: QualNet environment, SDL resource manager and the novel SDL2QualNet interface. We present useful information for 802.21 simulation implementation, data acquisition from QualNet and calculation of dynamic network parameters, information and buffer management, methods for improvement of simulation efficiency, and many other modeling hints which enable a comprehensive simulation platform.

The rapid growth of diverse wireless communication networks, each with its own unique characteristics, led to proliferation of the wireless heterogeneous network concept. The integration of various networks is not trivial, especially if one targets high performances. Modeling and simulation — based analysis provides sufficient means for performance evaluation, even in the abstract phases of the network development. This paper provides a unique combination of protocol development and network simulation method by merging the Specification and Description Language (SDL) developer and QualNet simulator. Moreover, the paper gives a detailed insight of the modeling process of novel resource management architecture (RIWCoS), along with valuable SDL codes and sequences.